From d4fe064a0b1c4f5b4ff4c61a2ac1f6d6f5b25eac Mon Sep 17 00:00:00 2001 From: Dimitar Slaev Date: Sat, 27 Jun 2026 21:49:41 +0200 Subject: [PATCH 01/42] feat(articles): add articles API with pgvector and public articles page Introduces the articles domain: Article model with a pgvector vector(256) column, Alembic migration that enables pgvector and creates an HNSW index, two public endpoints (filtered list + vector similarity search), a one-time import script, and a minimal frontend /articles page. Switches the Postgres image to pgvector/pgvector:pg17 and adds pgvector + model2vec deps. Also adds CLAUDE.md working agreements, CHANGES.md upstream divergence log, and a /prepare-pr slash command. Co-Authored-By: Claude Sonnet 4.6 --- .claude/commands/prepare-pr.md | 18 ++ CHANGES.md | 27 +++ CLAUDE.md | 17 ++ backend/.python-version | 1 + .../a1b2c3d4e5f6_add_articles_table.py | 56 +++++ backend/app/api/main.py | 3 +- backend/app/api/routes/articles.py | 109 ++++++++++ backend/app/models_agentique.py | 46 ++++ backend/pyproject.toml | 2 + backend/scripts/import_articles.py | 107 +++++++++ compose.yml | 2 +- frontend/src/client/sdk.gen.ts | 31 ++- frontend/src/client/types.gen.ts | 36 ++++ frontend/src/routeTree.gen.ts | 21 ++ frontend/src/routes/articles.tsx | 87 ++++++++ uv.lock | 204 +++++++++++++++++- 16 files changed, 756 insertions(+), 11 deletions(-) create mode 100644 .claude/commands/prepare-pr.md create mode 100644 CHANGES.md create mode 100644 CLAUDE.md create mode 100644 backend/.python-version create mode 100644 backend/app/alembic/versions/a1b2c3d4e5f6_add_articles_table.py create mode 100644 backend/app/api/routes/articles.py create mode 100644 backend/app/models_agentique.py create mode 100644 backend/scripts/import_articles.py create mode 100644 frontend/src/routes/articles.tsx diff --git a/.claude/commands/prepare-pr.md b/.claude/commands/prepare-pr.md new file mode 100644 index 0000000000..02e5808acf --- /dev/null +++ b/.claude/commands/prepare-pr.md @@ -0,0 +1,18 @@ +Prepare, commit, and open a pull request for the current branch. Do the following in order: + +1. Run `git status`, `git diff --cached`, `git log main..HEAD --oneline`, and `git diff main..HEAD` to understand what is staged and what the full branch diff looks like. + +2. Read `CHANGES.md` to understand the current upstream divergence state. + +3. Craft a conventional commit message for the staged changes: + - Format: `(): ` (under 72 chars) + - Types: feat, fix, chore, refactor, docs, style, test + - Focus on WHY and WHAT changed logically, not which files were touched + +4. Commit the staged changes with that message. + +5. Write the PR description — short, human-readable prose (2–4 sentences max). Explain what the change does and why, as if telling a teammate. No bullet lists of files. Capture intent and logic, not implementation details. + +6. Update `CHANGES.md` if any newly touched upstream files are not yet logged. Follow the existing table format. + +7. Push the branch and create the PR using `gh pr create` with the prose description. diff --git a/CHANGES.md b/CHANGES.md new file mode 100644 index 0000000000..28116ba9f4 --- /dev/null +++ b/CHANGES.md @@ -0,0 +1,27 @@ +# Upstream merge reference + +Changes made on top of `fastapi/full-stack-fastapi-template`. Upstream files are untouched unless noted. + +--- + +## 2026-06-27 + +### New files — no upstream conflict +| File | Why | +|---|---| +| `backend/app/models_agentique.py` | Article schema (ArticleBase → Article → ArticlePublic/ArticlesPublic) with pgvector vector(256) column | +| `backend/app/api/routes/articles.py` | Public GET /articles (filtered list) and GET /articles/search (vector) endpoints | +| `backend/app/alembic/versions/a1b2c3d4e5f6_add_articles_table.py` | Creates `article` table, enables pgvector extension, adds HNSW index | +| `backend/scripts/import_articles.py` | One-time migration: reads articles-export.json, re-embeds with model2vec, inserts into Postgres | +| `frontend/src/routes/articles.tsx` | Public /articles page rendering last 20 articles | + +### Modified upstream files — watch on merge +| File | Change | Conflict risk | +|---|---|---| +| `compose.yml` | db image `postgres:18` → `pgvector/pgvector:pg17` | Low — one line | +| `backend/pyproject.toml` | Added `pgvector`, `model2vec` deps | Low — additive | +| `uv.lock` | Regenerated to include above | Mechanical — re-run `uv lock` after merge | +| `backend/app/api/main.py` | Added `articles` router (items router kept) | Low — one additive line | +| `frontend/src/client/types.gen.ts` | Added Article* types | None — re-run `generate-client` after merge | +| `frontend/src/client/sdk.gen.ts` | Added ArticlesService | None — re-run `generate-client` after merge | +| `frontend/src/routeTree.gen.ts` | Registered /articles route | None — auto-regenerated by vite dev | diff --git a/CLAUDE.md b/CLAUDE.md new file mode 100644 index 0000000000..5f55a32ed6 --- /dev/null +++ b/CLAUDE.md @@ -0,0 +1,17 @@ +# agentique-next — working agreements + +## Upstream fork +This repo is a fork of `fastapi/full-stack-fastapi-template`. Keep that in mind for every change: + +- **Prefer adding new files over modifying upstream ones.** New Agentique code goes in `models_agentique.py`, `routes/articles.py`, etc. — not patched into `models.py`, `crud.py`, or other upstream files. +- **When you must touch an upstream file**, make the smallest possible change and note it in `CHANGES.md` with the conflict risk level. +- **Never delete upstream files** (routes, tests, utils). They may be needed for upstream merges and for the template to stay coherent. +- **Backend especially**: the Python backend is where upstream activity is highest. Treat every file in `backend/app/` that existed in the original template as upstream-owned. New domain logic belongs in new files. +- **Generated frontend files** (`types.gen.ts`, `sdk.gen.ts`, `routeTree.gen.ts`) are safe to patch manually — they get fully regenerated by `generate-client` and `vite dev`, so merge conflicts there are not real conflicts. +- Before starting any non-trivial backend task, check `CHANGES.md` to understand what is already diverged. + +## Plans +- When asked for a plan, save it to `plans/.md`. Keep the chat reply to a short summary + file path. + +## Skills +- `/prepare-pr` — generates a PR description (conventional commit format) and updates `CHANGES.md`. diff --git a/backend/.python-version b/backend/.python-version new file mode 100644 index 0000000000..6324d401a0 --- /dev/null +++ b/backend/.python-version @@ -0,0 +1 @@ +3.14 diff --git a/backend/app/alembic/versions/a1b2c3d4e5f6_add_articles_table.py b/backend/app/alembic/versions/a1b2c3d4e5f6_add_articles_table.py new file mode 100644 index 0000000000..4972eb0d6f --- /dev/null +++ b/backend/app/alembic/versions/a1b2c3d4e5f6_add_articles_table.py @@ -0,0 +1,56 @@ +"""Add articles table with pgvector + +Revision ID: a1b2c3d4e5f6 +Revises: fe56fa70289e +Create Date: 2026-06-27 00:00:00.000000 + +""" +import sqlalchemy as sa +from alembic import op + +revision = "a1b2c3d4e5f6" +down_revision = "fe56fa70289e" +branch_labels = None +depends_on = None + + +def upgrade() -> None: + op.execute("CREATE EXTENSION IF NOT EXISTS vector") + + op.create_table( + "article", + sa.Column("id", sa.Integer(), primary_key=True, autoincrement=True), + sa.Column("title", sa.String(), nullable=False), + sa.Column("source", sa.String(), nullable=False), + sa.Column("source_type", sa.String(), nullable=False), + sa.Column("url", sa.String(), nullable=True), + sa.Column("published_at", sa.DateTime(timezone=True), nullable=True), + sa.Column("score", sa.Integer(), nullable=True), + sa.Column("summary", sa.Text(), nullable=True), + sa.Column("categories", sa.JSON(), nullable=True), + sa.Column("kind", sa.String(), nullable=True), + sa.Column("content", sa.Text(), nullable=True), + sa.Column( + "embedding", + sa.VARCHAR(length=256), # placeholder; vector type applied below + nullable=True, + ), + sa.Column("created_at", sa.DateTime(timezone=True), nullable=True), + ) + + # Replace placeholder column with the real vector type + op.execute("ALTER TABLE article ALTER COLUMN embedding TYPE vector(256) USING NULL") + + op.create_index("ix_article_score", "article", ["score"]) + op.create_index("ix_article_published_at", "article", ["published_at"]) + op.execute( + """ + CREATE INDEX ix_article_embedding_hnsw + ON article + USING hnsw (embedding vector_cosine_ops) + """ + ) + + +def downgrade() -> None: + op.drop_table("article") diff --git a/backend/app/api/main.py b/backend/app/api/main.py index eac18c8e8f..1e2d6bb555 100644 --- a/backend/app/api/main.py +++ b/backend/app/api/main.py @@ -1,6 +1,6 @@ from fastapi import APIRouter -from app.api.routes import items, login, private, users, utils +from app.api.routes import articles, items, login, private, users, utils from app.core.config import settings api_router = APIRouter() @@ -8,6 +8,7 @@ api_router.include_router(users.router) api_router.include_router(utils.router) api_router.include_router(items.router) +api_router.include_router(articles.router) if settings.ENVIRONMENT == "local": diff --git a/backend/app/api/routes/articles.py b/backend/app/api/routes/articles.py new file mode 100644 index 0000000000..a7f27a00f4 --- /dev/null +++ b/backend/app/api/routes/articles.py @@ -0,0 +1,109 @@ +from datetime import UTC, datetime, timedelta +from typing import Any + +from fastapi import APIRouter, Query +from model2vec import StaticModel +from pgvector.sqlalchemy import Vector +from sqlalchemy import cast, func, or_ +from sqlmodel import col, select + +from app.api.deps import SessionDep +from app.models_agentique import Article, ArticlePublic, ArticlesPublic + +router = APIRouter(prefix="/articles", tags=["articles"]) + +# Loaded once at module import — model2vec is CPU-only and tiny (~30 MB) +_model: StaticModel | None = None + + +def get_model() -> StaticModel: + global _model + if _model is None: + _model = StaticModel.from_pretrained("minishlab/potion-base-8M") + return _model + + +def _embed(text: str) -> list[float]: + import numpy as np + + model = get_model() + vec = model.encode([text])[0] + norm = np.linalg.norm(vec) + if norm > 0: + vec = vec / norm + return vec.tolist() + + +@router.get("/", response_model=ArticlesPublic) +def read_articles( + session: SessionDep, + limit: int = Query(default=20, ge=1, le=50), + since: str | None = None, + min_score: int | None = Query(default=None, ge=1, le=10), + category: str | None = None, + kind: str | None = None, +) -> Any: + since_dt: datetime + if since: + try: + since_dt = datetime.fromisoformat(since) + except ValueError: + since_dt = datetime.now(UTC) - timedelta(days=30) + else: + since_dt = datetime.now(UTC) - timedelta(days=30) + + statement = ( + select(Article) + .where(Article.score.is_not(None)) # type: ignore[union-attr] + .where(col(Article.published_at) >= since_dt) + ) + + if min_score is not None: + statement = statement.where(Article.score >= min_score) # type: ignore[operator] + if kind is not None: + statement = statement.where(Article.kind == kind) + if category is not None: + statement = statement.where( + func.json_array_length(Article.categories) > 0 # type: ignore[arg-type] + ).where( + func.exists( + select(func.json_array_elements_text(Article.categories).label("cat")) # type: ignore[arg-type] + .correlate(Article) + .where(func.json_array_elements_text(Article.categories) == category) # type: ignore[arg-type] + ) + ) + + count_statement = select(func.count()).select_from(statement.subquery()) + count = session.exec(count_statement).one() + + statement = statement.order_by(col(Article.score).desc()).limit(limit) + articles = session.exec(statement).all() + + return ArticlesPublic( + data=[ArticlePublic.model_validate(a) for a in articles], + count=count, + ) + + +@router.get("/search", response_model=ArticlesPublic) +def search_articles( + session: SessionDep, + q: str, + limit: int = Query(default=20, ge=1, le=50), +) -> Any: + query_vec = _embed(q) + + statement = ( + select(Article) + .where(Article.score.is_not(None)) # type: ignore[union-attr] + .where(Article.embedding.is_not(None)) # type: ignore[union-attr] + .order_by(cast(Article.embedding, Vector(256)).cosine_distance(query_vec)) + .limit(limit) + ) + + articles = session.exec(statement).all() + + return ArticlesPublic( + data=[ArticlePublic.model_validate(a) for a in articles], + count=len(articles), + ) diff --git a/backend/app/models_agentique.py b/backend/app/models_agentique.py new file mode 100644 index 0000000000..71f895e613 --- /dev/null +++ b/backend/app/models_agentique.py @@ -0,0 +1,46 @@ +from datetime import UTC, datetime + +from pgvector.sqlalchemy import Vector +from sqlalchemy import Column, DateTime, JSON +from sqlmodel import Field, SQLModel + + +def get_datetime_utc() -> datetime: + return datetime.now(UTC) + + +class ArticleBase(SQLModel): + title: str + source: str + source_type: str + url: str | None = None + published_at: datetime | None = None + score: int | None = None + summary: str | None = None + categories: list[str] = Field( + default_factory=list, sa_column=Column(JSON, nullable=True) + ) + kind: str | None = None + + +class Article(ArticleBase, table=True): + id: int | None = Field(default=None, primary_key=True) + content: str | None = Field(default="") + # 256-dim model2vec vectors; nullable until the import script runs + embedding: list[float] | None = Field( + default=None, sa_column=Column(Vector(256), nullable=True) + ) + created_at: datetime | None = Field( + default_factory=get_datetime_utc, + sa_type=DateTime(timezone=True), # type: ignore + ) + + +class ArticlePublic(ArticleBase): + id: int + created_at: datetime | None = None + + +class ArticlesPublic(SQLModel): + data: list[ArticlePublic] + count: int diff --git a/backend/pyproject.toml b/backend/pyproject.toml index e4a7096696..4552d7483f 100644 --- a/backend/pyproject.toml +++ b/backend/pyproject.toml @@ -19,6 +19,8 @@ dependencies = [ "sentry-sdk[fastapi]>=2.0.0,<3.0.0", "pyjwt<3.0.0,>=2.13.0", "pwdlib[argon2,bcrypt]>=0.3.0", + "pgvector>=0.3.0", + "model2vec>=0.4.0", ] [dependency-groups] diff --git a/backend/scripts/import_articles.py b/backend/scripts/import_articles.py new file mode 100644 index 0000000000..8e3644a3fd --- /dev/null +++ b/backend/scripts/import_articles.py @@ -0,0 +1,107 @@ +""" +One-time migration: import articles from articles-export.json into Postgres, +re-embedding each article (title + summary) with model2vec potion-base-8M. + +Usage (from repo root, with .env sourced or DATABASE_URL set): + uv run python backend/scripts/import_articles.py [path/to/articles-export.json] + +Default input path: articles-export.json (repo root). +""" +import json +import sys +from datetime import datetime +from pathlib import Path + +import numpy as np +from model2vec import StaticModel +from sqlmodel import Session, create_engine + +# Allow running from repo root without installing the package +sys.path.insert(0, str(Path(__file__).parent.parent)) + +from app.core.config import settings # noqa: E402 +from app.models_articles import Article # noqa: E402 + +EXPORT_PATH = Path(sys.argv[1]) if len(sys.argv) > 1 else Path("articles-export.json") +BATCH_SIZE = 64 + + +def parse_dt(value: str | None) -> datetime | None: + if not value: + return None + try: + return datetime.fromisoformat(value.replace("Z", "+00:00")) + except ValueError: + return None + + +def embed_batch(model: StaticModel, texts: list[str]) -> list[list[float]]: + vecs = model.encode(texts) + norms = np.linalg.norm(vecs, axis=1, keepdims=True) + norms = np.where(norms == 0, 1, norms) + return (vecs / norms).tolist() + + +def main() -> None: + if not EXPORT_PATH.exists(): + print(f"Export file not found: {EXPORT_PATH}") + sys.exit(1) + + raw = json.loads(EXPORT_PATH.read_text()) + print(f"Loaded {len(raw)} articles from {EXPORT_PATH}") + + print("Loading model2vec model (minishlab/potion-base-8M)…") + model = StaticModel.from_pretrained("minishlab/potion-base-8M") + + engine = create_engine(str(settings.SQLALCHEMY_DATABASE_URI)) + + inserted = skipped = embedded = 0 + + with Session(engine) as session: + # Process in batches for embedding efficiency + embeddable = [ + r for r in raw if r.get("score") is not None and r.get("summary") + ] + non_embeddable = [ + r for r in raw if not (r.get("score") is not None and r.get("summary")) + ] + + # Build embedding map: id → vector + embedding_map: dict[int, list[float]] = {} + for i in range(0, len(embeddable), BATCH_SIZE): + batch = embeddable[i : i + BATCH_SIZE] + texts = [f"{r['title']}\n{r['summary']}" for r in batch] + vecs = embed_batch(model, texts) + for r, vec in zip(batch, vecs): + embedding_map[r["id"]] = vec + embedded += len(batch) + print(f" embedded {embedded}/{len(embeddable)}", end="\r") + + print(f"\nEmbedded {embedded} articles, skipping {len(non_embeddable)} (no summary)") + + all_rows = embeddable + non_embeddable + for row in all_rows: + article = Article( + title=row["title"], + source=row["source"], + source_type=row["source_type"], + url=row.get("url"), + published_at=parse_dt(row.get("published_at")), + score=row.get("score"), + summary=row.get("summary"), + categories=row.get("categories") or [], + kind=row.get("kind"), + content=row.get("content") or "", + embedding=embedding_map.get(row["id"]), + created_at=parse_dt(row.get("created_at")), + ) + session.add(article) + inserted += 1 + + session.commit() + + print(f"Done. Inserted {inserted} articles ({embedded} with embeddings, {skipped} skipped).") + + +if __name__ == "__main__": + main() diff --git a/compose.yml b/compose.yml index 2488fc007b..22b3a0d484 100644 --- a/compose.yml +++ b/compose.yml @@ -1,7 +1,7 @@ services: db: - image: postgres:18 + image: pgvector/pgvector:pg17 restart: always healthcheck: test: ["CMD-SHELL", "pg_isready -U ${POSTGRES_USER} -d ${POSTGRES_DB}"] diff --git a/frontend/src/client/sdk.gen.ts b/frontend/src/client/sdk.gen.ts index ba79e3f726..92a1745966 100644 --- a/frontend/src/client/sdk.gen.ts +++ b/frontend/src/client/sdk.gen.ts @@ -3,7 +3,36 @@ import type { CancelablePromise } from './core/CancelablePromise'; import { OpenAPI } from './core/OpenAPI'; import { request as __request } from './core/request'; -import type { ItemsReadItemsData, ItemsReadItemsResponse, ItemsCreateItemData, ItemsCreateItemResponse, ItemsReadItemData, ItemsReadItemResponse, ItemsUpdateItemData, ItemsUpdateItemResponse, ItemsDeleteItemData, ItemsDeleteItemResponse, LoginLoginAccessTokenData, LoginLoginAccessTokenResponse, LoginTestTokenResponse, LoginRecoverPasswordData, LoginRecoverPasswordResponse, LoginResetPasswordData, LoginResetPasswordResponse, LoginRecoverPasswordHtmlContentData, LoginRecoverPasswordHtmlContentResponse, PrivateCreateUserData, PrivateCreateUserResponse, UsersReadUsersData, UsersReadUsersResponse, UsersCreateUserData, UsersCreateUserResponse, UsersReadUserMeResponse, UsersDeleteUserMeResponse, UsersUpdateUserMeData, UsersUpdateUserMeResponse, UsersUpdatePasswordMeData, UsersUpdatePasswordMeResponse, UsersRegisterUserData, UsersRegisterUserResponse, UsersReadUserByIdData, UsersReadUserByIdResponse, UsersUpdateUserData, UsersUpdateUserResponse, UsersDeleteUserData, UsersDeleteUserResponse, UtilsTestEmailData, UtilsTestEmailResponse, UtilsHealthCheckResponse } from './types.gen'; +import type { ArticlesReadArticlesData, ArticlesReadArticlesResponse, ArticlesSearchArticlesData, ArticlesSearchArticlesResponse, ItemsReadItemsData, ItemsReadItemsResponse, ItemsCreateItemData, ItemsCreateItemResponse, ItemsReadItemData, ItemsReadItemResponse, ItemsUpdateItemData, ItemsUpdateItemResponse, ItemsDeleteItemData, ItemsDeleteItemResponse, LoginLoginAccessTokenData, LoginLoginAccessTokenResponse, LoginTestTokenResponse, LoginRecoverPasswordData, LoginRecoverPasswordResponse, LoginResetPasswordData, LoginResetPasswordResponse, LoginRecoverPasswordHtmlContentData, LoginRecoverPasswordHtmlContentResponse, PrivateCreateUserData, PrivateCreateUserResponse, UsersReadUsersData, UsersReadUsersResponse, UsersCreateUserData, UsersCreateUserResponse, UsersReadUserMeResponse, UsersDeleteUserMeResponse, UsersUpdateUserMeData, UsersUpdateUserMeResponse, UsersUpdatePasswordMeData, UsersUpdatePasswordMeResponse, UsersRegisterUserData, UsersRegisterUserResponse, UsersReadUserByIdData, UsersReadUserByIdResponse, UsersUpdateUserData, UsersUpdateUserResponse, UsersDeleteUserData, UsersDeleteUserResponse, UtilsTestEmailData, UtilsTestEmailResponse, UtilsHealthCheckResponse } from './types.gen'; + +export class ArticlesService { + public static readArticles(data: ArticlesReadArticlesData = {}): CancelablePromise { + return __request(OpenAPI, { + method: 'GET', + url: '/api/v1/articles/', + query: { + limit: data.limit, + since: data.since, + min_score: data.minScore, + category: data.category, + kind: data.kind, + }, + errors: { 422: 'Validation Error' }, + }); + } + + public static searchArticles(data: ArticlesSearchArticlesData): CancelablePromise { + return __request(OpenAPI, { + method: 'GET', + url: '/api/v1/articles/search', + query: { + q: data.q, + limit: data.limit, + }, + errors: { 422: 'Validation Error' }, + }); + } +} export class ItemsService { /** diff --git a/frontend/src/client/types.gen.ts b/frontend/src/client/types.gen.ts index 596b8fc476..3f2fabd119 100644 --- a/frontend/src/client/types.gen.ts +++ b/frontend/src/client/types.gen.ts @@ -1,5 +1,41 @@ // This file is auto-generated by @hey-api/openapi-ts +export type ArticlePublic = { + title: string; + source: string; + source_type: string; + url?: (string | null); + published_at?: (string | null); + score?: (number | null); + summary?: (string | null); + categories?: Array; + kind?: (string | null); + id: number; + created_at?: (string | null); +}; + +export type ArticlesPublic = { + data: Array; + count: number; +}; + +export type ArticlesReadArticlesData = { + limit?: number; + since?: (string | null); + minScore?: (number | null); + category?: (string | null); + kind?: (string | null); +}; + +export type ArticlesReadArticlesResponse = ArticlesPublic; + +export type ArticlesSearchArticlesData = { + q: string; + limit?: number; +}; + +export type ArticlesSearchArticlesResponse = ArticlesPublic; + export type Body_login_login_access_token = { grant_type?: (string | null); username: string; diff --git a/frontend/src/routeTree.gen.ts b/frontend/src/routeTree.gen.ts index 8849130b4c..7ec39d20d3 100644 --- a/frontend/src/routeTree.gen.ts +++ b/frontend/src/routeTree.gen.ts @@ -9,6 +9,7 @@ // Additionally, you should also exclude this file from your linter and/or formatter to prevent it from being checked or modified. import { Route as rootRouteImport } from './routes/__root' +import { Route as ArticlesRouteImport } from './routes/articles' import { Route as SignupRouteImport } from './routes/signup' import { Route as ResetPasswordRouteImport } from './routes/reset-password' import { Route as RecoverPasswordRouteImport } from './routes/recover-password' @@ -19,6 +20,11 @@ import { Route as LayoutSettingsRouteImport } from './routes/_layout/settings' import { Route as LayoutItemsRouteImport } from './routes/_layout/items' import { Route as LayoutAdminRouteImport } from './routes/_layout/admin' +const ArticlesRoute = ArticlesRouteImport.update({ + id: '/articles', + path: '/articles', + getParentRoute: () => rootRouteImport, +} as any) const SignupRoute = SignupRouteImport.update({ id: '/signup', path: '/signup', @@ -65,6 +71,7 @@ const LayoutAdminRoute = LayoutAdminRouteImport.update({ } as any) export interface FileRoutesByFullPath { + '/articles': typeof ArticlesRoute '/login': typeof LoginRoute '/recover-password': typeof RecoverPasswordRoute '/reset-password': typeof ResetPasswordRoute @@ -75,6 +82,7 @@ export interface FileRoutesByFullPath { '/': typeof LayoutIndexRoute } export interface FileRoutesByTo { + '/articles': typeof ArticlesRoute '/login': typeof LoginRoute '/recover-password': typeof RecoverPasswordRoute '/reset-password': typeof ResetPasswordRoute @@ -86,6 +94,7 @@ export interface FileRoutesByTo { } export interface FileRoutesById { __root__: typeof rootRouteImport + '/articles': typeof ArticlesRoute '/_layout': typeof LayoutRouteWithChildren '/login': typeof LoginRoute '/recover-password': typeof RecoverPasswordRoute @@ -99,6 +108,7 @@ export interface FileRoutesById { export interface FileRouteTypes { fileRoutesByFullPath: FileRoutesByFullPath fullPaths: + | '/articles' | '/login' | '/recover-password' | '/reset-password' @@ -109,6 +119,7 @@ export interface FileRouteTypes { | '/' fileRoutesByTo: FileRoutesByTo to: + | '/articles' | '/login' | '/recover-password' | '/reset-password' @@ -119,6 +130,7 @@ export interface FileRouteTypes { | '/' id: | '__root__' + | '/articles' | '/_layout' | '/login' | '/recover-password' @@ -131,6 +143,7 @@ export interface FileRouteTypes { fileRoutesById: FileRoutesById } export interface RootRouteChildren { + ArticlesRoute: typeof ArticlesRoute LayoutRoute: typeof LayoutRouteWithChildren LoginRoute: typeof LoginRoute RecoverPasswordRoute: typeof RecoverPasswordRoute @@ -203,6 +216,13 @@ declare module '@tanstack/react-router' { preLoaderRoute: typeof LayoutAdminRouteImport parentRoute: typeof LayoutRoute } + '/articles': { + id: '/articles' + path: '/articles' + fullPath: '/articles' + preLoaderRoute: typeof ArticlesRouteImport + parentRoute: typeof rootRouteImport + } } } @@ -224,6 +244,7 @@ const LayoutRouteWithChildren = LayoutRoute._addFileChildren(LayoutRouteChildren) const rootRouteChildren: RootRouteChildren = { + ArticlesRoute: ArticlesRoute, LayoutRoute: LayoutRouteWithChildren, LoginRoute: LoginRoute, RecoverPasswordRoute: RecoverPasswordRoute, diff --git a/frontend/src/routes/articles.tsx b/frontend/src/routes/articles.tsx new file mode 100644 index 0000000000..f385468959 --- /dev/null +++ b/frontend/src/routes/articles.tsx @@ -0,0 +1,87 @@ +import { useQuery } from "@tanstack/react-query"; +import { createFileRoute } from "@tanstack/react-router"; +import { ArticlesService, type ArticlePublic } from "@/client"; + +export const Route = createFileRoute("/articles")({ + component: ArticlesPage, + head: () => ({ + meta: [{ title: "Articles - Agentique" }], + }), +}); + +function ArticlesPage() { + const { data, isLoading, isError } = useQuery({ + queryKey: ["articles"], + queryFn: () => ArticlesService.readArticles({ limit: 20 }), + }); + + if (isLoading) { + return ( +
+ Loading… +
+ ); + } + + if (isError || !data) { + return ( +
+ Failed to load articles. +
+ ); + } + + return ( +
+

Latest articles

+
    + {data.data.map((article: ArticlePublic) => ( +
  • +
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    + {article.summary} +

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+0200 Subject: [PATCH 02/42] chore: ignore --- .gitignore | 2 ++ 1 file changed, 2 insertions(+) diff --git a/.gitignore b/.gitignore index f903ab6066..a52f7bb3dd 100644 --- a/.gitignore +++ b/.gitignore @@ -5,3 +5,5 @@ node_modules/ /playwright-report/ /blob-report/ /playwright/.cache/ +.ignored/ +.DS_Store \ No newline at end of file From 2c6791dc984b4b1bef062418134f83d82d6c4dec Mon Sep 17 00:00:00 2001 From: Dimitar Slaev Date: Sat, 27 Jun 2026 23:54:32 +0200 Subject: [PATCH 03/42] ci: manual staging workflow --- .github/workflows/deploy-staging.yml | 3 +++ .github/workflows/teardown-staging.yml | 20 ++++++++++++++++++++ 2 files changed, 23 insertions(+) create mode 100644 .github/workflows/teardown-staging.yml diff --git a/.github/workflows/deploy-staging.yml b/.github/workflows/deploy-staging.yml index f4cb222f2b..a7c601815d 100644 --- a/.github/workflows/deploy-staging.yml +++ b/.github/workflows/deploy-staging.yml @@ -4,6 +4,7 @@ on: push: branches: - master + workflow_dispatch: permissions: {} @@ -33,5 +34,7 @@ jobs: uses: actions/checkout@df4cb1c069e1874edd31b4311f1884172cec0e10 # v6.0.3 with: persist-credentials: false + - run: touch .env + - run: docker network create traefik-public 2>/dev/null || true - run: docker compose -f compose.yml --project-name ${{ secrets.STACK_NAME_STAGING }} build - run: docker compose -f compose.yml --project-name ${{ secrets.STACK_NAME_STAGING }} up -d diff --git a/.github/workflows/teardown-staging.yml b/.github/workflows/teardown-staging.yml new file mode 100644 index 0000000000..58f581d346 --- /dev/null +++ b/.github/workflows/teardown-staging.yml @@ -0,0 +1,20 @@ +name: Teardown Staging + +on: + workflow_dispatch: + +permissions: {} + +jobs: + teardown: + environment: staging + if: github.repository_owner != 'fastapi' + runs-on: + - self-hosted + - staging + steps: + - uses: actions/checkout@df4cb1c069e1874edd31b4311f1884172cec0e10 # v6.0.3 + with: + persist-credentials: false + - run: touch .env + - run: docker compose -f compose.yml --project-name ${{ secrets.STACK_NAME_STAGING }} down -v From fb8e19aa6c741b7bdba79d36e88661effdfd87a6 Mon Sep 17 00:00:00 2001 From: Dimitar Slaev Date: Sun, 28 Jun 2026 00:17:34 +0200 Subject: [PATCH 04/42] chore: gen files --- CLAUDE.md | 3 + frontend/src/client/schemas.gen.ts | 1133 +++++++++++++++------------- frontend/src/client/sdk.gen.ts | 57 +- frontend/src/client/types.gen.ts | 49 +- 4 files changed, 663 insertions(+), 579 deletions(-) diff --git a/CLAUDE.md b/CLAUDE.md index 5f55a32ed6..67c59a21c1 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -10,6 +10,9 @@ This repo is a fork of `fastapi/full-stack-fastapi-template`. Keep that in mind - **Generated frontend files** (`types.gen.ts`, `sdk.gen.ts`, `routeTree.gen.ts`) are safe to patch manually — they get fully regenerated by `generate-client` and `vite dev`, so merge conflicts there are not real conflicts. - Before starting any non-trivial backend task, check `CHANGES.md` to understand what is already diverged. +## Client generation +- `types.gen.ts`, `sdk.gen.ts`, `schemas.gen.ts` must be committed — Docker does not run `generate-client`, it builds from committed files. To regenerate after an API schema change: start the local Docker stack, then run `bash ./scripts/generate-client.sh` from repo root. Commit the result. + ## Plans - When asked for a plan, save it to `plans/.md`. Keep the chat reply to a short summary + file path. diff --git a/frontend/src/client/schemas.gen.ts b/frontend/src/client/schemas.gen.ts index ea7b4f5cff..0fcde54a94 100644 --- a/frontend/src/client/schemas.gen.ts +++ b/frontend/src/client/schemas.gen.ts @@ -1,571 +1,664 @@ // This file is auto-generated by @hey-api/openapi-ts +export const ArticlePublicSchema = { + properties: { + title: { + type: "string", + title: "Title", + }, + source: { + type: "string", + title: "Source", + }, + source_type: { + type: "string", + title: "Source Type", + }, + url: { + anyOf: [ + { + type: "string", + }, + { + type: "null", + }, + ], + title: "Url", + }, + published_at: { + anyOf: [ + { + type: "string", + format: "date-time", + }, + { + type: "null", + }, + ], + title: "Published At", + }, + score: { + anyOf: [ + { + type: "integer", + }, + { + type: "null", + }, + ], + title: "Score", + }, + summary: { + anyOf: [ + { + type: "string", + }, + { + type: "null", + }, + ], + title: "Summary", + }, + categories: { + items: { + type: "string", + }, + type: "array", + title: "Categories", + }, + kind: { + anyOf: [ + { + type: "string", + }, + { + type: "null", + }, + ], + title: "Kind", + }, + id: { + type: "integer", + title: "Id", + }, + created_at: { + anyOf: [ + { + type: "string", + format: "date-time", + }, + { + type: "null", + }, + ], + title: "Created At", + }, + }, + type: "object", + required: ["title", "source", "source_type", "id"], + title: "ArticlePublic", +} as const; + +export const ArticlesPublicSchema = { + properties: { + data: { + items: { + $ref: "#/components/schemas/ArticlePublic", + }, + type: "array", + title: "Data", + }, + count: { + type: "integer", + title: "Count", + }, + }, + type: "object", + required: ["data", "count"], + title: "ArticlesPublic", +} as const; + export const Body_login_login_access_tokenSchema = { - properties: { - grant_type: { - anyOf: [ - { - type: 'string', - pattern: '^password$' - }, - { - type: 'null' - } - ], - title: 'Grant Type' - }, - username: { - type: 'string', - title: 'Username' - }, - password: { - type: 'string', - format: 'password', - title: 'Password' - }, - scope: { - type: 'string', - title: 'Scope', - default: '' - }, - client_id: { - anyOf: [ - { - type: 'string' - }, - { - type: 'null' - } - ], - title: 'Client Id' - }, - client_secret: { - anyOf: [ - { - type: 'string' - }, - { - type: 'null' - } - ], - format: 'password', - title: 'Client Secret' - } - }, - type: 'object', - required: ['username', 'password'], - title: 'Body_login-login_access_token' + properties: { + grant_type: { + anyOf: [ + { + type: "string", + pattern: "^password$", + }, + { + type: "null", + }, + ], + title: "Grant Type", + }, + username: { + type: "string", + title: "Username", + }, + password: { + type: "string", + format: "password", + title: "Password", + }, + scope: { + type: "string", + title: "Scope", + default: "", + }, + client_id: { + anyOf: [ + { + type: "string", + }, + { + type: "null", + }, + ], + title: "Client Id", + }, + client_secret: { + anyOf: [ + { + type: "string", + }, + { + type: "null", + }, + ], + format: "password", + title: "Client Secret", + }, + }, + type: "object", + required: ["username", "password"], + title: "Body_login-login_access_token", } as const; export const HTTPValidationErrorSchema = { - properties: { - detail: { - items: { - '$ref': '#/components/schemas/ValidationError' - }, - type: 'array', - title: 'Detail' - } - }, - type: 'object', - title: 'HTTPValidationError' + properties: { + detail: { + items: { + $ref: "#/components/schemas/ValidationError", + }, + type: "array", + title: "Detail", + }, + }, + type: "object", + title: "HTTPValidationError", } as const; export const ItemCreateSchema = { - properties: { - title: { - type: 'string', - maxLength: 255, - minLength: 1, - title: 'Title' - }, - description: { - anyOf: [ - { - type: 'string', - maxLength: 255 - }, - { - type: 'null' - } - ], - title: 'Description' - } - }, - type: 'object', - required: ['title'], - title: 'ItemCreate' + properties: { + title: { + type: "string", + maxLength: 255, + minLength: 1, + title: "Title", + }, + description: { + anyOf: [ + { + type: "string", + maxLength: 255, + }, + { + type: "null", + }, + ], + title: "Description", + }, + }, + type: "object", + required: ["title"], + title: "ItemCreate", } as const; export const ItemPublicSchema = { - properties: { - title: { - type: 'string', - maxLength: 255, - minLength: 1, - title: 'Title' - }, - description: { - anyOf: [ - { - type: 'string', - maxLength: 255 - }, - { - type: 'null' - } - ], - title: 'Description' - }, - id: { - type: 'string', - format: 'uuid', - title: 'Id' - }, - owner_id: { - type: 'string', - format: 'uuid', - title: 'Owner Id' - }, - created_at: { - anyOf: [ - { - type: 'string', - format: 'date-time' - }, - { - type: 'null' - } - ], - title: 'Created At' - } - }, - type: 'object', - required: ['title', 'id', 'owner_id'], - title: 'ItemPublic' + properties: { + title: { + type: "string", + maxLength: 255, + minLength: 1, + title: "Title", + }, + description: { + anyOf: [ + { + type: "string", + maxLength: 255, + }, + { + type: "null", + }, + ], + title: "Description", + }, + id: { + type: "string", + format: "uuid", + title: "Id", + }, + owner_id: { + type: "string", + format: "uuid", + title: "Owner Id", + }, + created_at: { + anyOf: [ + { + type: "string", + format: "date-time", + }, + { + type: "null", + }, + ], + title: "Created At", + }, + }, + type: "object", + required: ["title", "id", "owner_id"], + title: "ItemPublic", } as const; export const ItemUpdateSchema = { - properties: { - title: { - anyOf: [ - { - type: 'string', - maxLength: 255, - minLength: 1 - }, - { - type: 'null' - } - ], - title: 'Title' - }, - description: { - anyOf: [ - { - type: 'string', - maxLength: 255 - }, - { - type: 'null' - } - ], - title: 'Description' - } - }, - type: 'object', - title: 'ItemUpdate' + properties: { + title: { + anyOf: [ + { + type: "string", + maxLength: 255, + minLength: 1, + }, + { + type: "null", + }, + ], + title: "Title", + }, + description: { + anyOf: [ + { + type: "string", + maxLength: 255, + }, + { + type: "null", + }, + ], + title: "Description", + }, + }, + type: "object", + title: "ItemUpdate", } as const; export const ItemsPublicSchema = { - properties: { - data: { - items: { - '$ref': '#/components/schemas/ItemPublic' - }, - type: 'array', - title: 'Data' - }, - count: { - type: 'integer', - title: 'Count' - } - }, - type: 'object', - required: ['data', 'count'], - title: 'ItemsPublic' + properties: { + data: { + items: { + $ref: "#/components/schemas/ItemPublic", + }, + type: "array", + title: "Data", + }, + count: { + type: "integer", + title: "Count", + }, + }, + type: "object", + required: ["data", "count"], + title: "ItemsPublic", } as const; export const MessageSchema = { - properties: { - message: { - type: 'string', - title: 'Message' - } - }, - type: 'object', - required: ['message'], - title: 'Message' + properties: { + message: { + type: "string", + title: "Message", + }, + }, + type: "object", + required: ["message"], + title: "Message", } as const; export const NewPasswordSchema = { - properties: { - token: { - type: 'string', - title: 'Token' - }, - new_password: { - type: 'string', - maxLength: 128, - minLength: 8, - title: 'New Password' - } - }, - type: 'object', - required: ['token', 'new_password'], - title: 'NewPassword' -} as const; - -export const PrivateUserCreateSchema = { - properties: { - email: { - type: 'string', - title: 'Email' - }, - password: { - type: 'string', - title: 'Password' - }, - full_name: { - type: 'string', - title: 'Full Name' - }, - is_verified: { - type: 'boolean', - title: 'Is Verified', - default: false - } - }, - type: 'object', - required: ['email', 'password', 'full_name'], - title: 'PrivateUserCreate' + properties: { + token: { + type: "string", + title: "Token", + }, + new_password: { + type: "string", + maxLength: 128, + minLength: 8, + title: "New Password", + }, + }, + type: "object", + required: ["token", "new_password"], + title: "NewPassword", } as const; export const TokenSchema = { - properties: { - access_token: { - type: 'string', - title: 'Access Token' - }, - token_type: { - type: 'string', - title: 'Token Type', - default: 'bearer' - } - }, - type: 'object', - required: ['access_token'], - title: 'Token' + properties: { + access_token: { + type: "string", + title: "Access Token", + }, + token_type: { + type: "string", + title: "Token Type", + default: "bearer", + }, + }, + type: "object", + required: ["access_token"], + title: "Token", } as const; export const UpdatePasswordSchema = { - properties: { - current_password: { - type: 'string', - maxLength: 128, - minLength: 8, - title: 'Current Password' - }, - new_password: { - type: 'string', - maxLength: 128, - minLength: 8, - title: 'New Password' - } - }, - type: 'object', - required: ['current_password', 'new_password'], - title: 'UpdatePassword' + properties: { + current_password: { + type: "string", + maxLength: 128, + minLength: 8, + title: "Current Password", + }, + new_password: { + type: "string", + maxLength: 128, + minLength: 8, + title: "New Password", + }, + }, + type: "object", + required: ["current_password", "new_password"], + title: "UpdatePassword", } as const; export const UserCreateSchema = { - properties: { - email: { - type: 'string', - maxLength: 255, - format: 'email', - title: 'Email' - }, - is_active: { - type: 'boolean', - title: 'Is Active', - default: true - }, - is_superuser: { - type: 'boolean', - title: 'Is Superuser', - default: false - }, - full_name: { - anyOf: [ - { - type: 'string', - maxLength: 255 - }, - { - type: 'null' - } - ], - title: 'Full Name' - }, - password: { - type: 'string', - maxLength: 128, - minLength: 8, - title: 'Password' - } - }, - type: 'object', - required: ['email', 'password'], - title: 'UserCreate' + properties: { + email: { + type: "string", + maxLength: 255, + format: "email", + title: "Email", + }, + is_active: { + type: "boolean", + title: "Is Active", + default: true, + }, + is_superuser: { + type: "boolean", + title: "Is Superuser", + default: false, + }, + full_name: { + anyOf: [ + { + type: "string", + maxLength: 255, + }, + { + type: "null", + }, + ], + title: "Full Name", + }, + password: { + type: "string", + maxLength: 128, + minLength: 8, + title: "Password", + }, + }, + type: "object", + required: ["email", "password"], + title: "UserCreate", } as const; export const UserPublicSchema = { - properties: { - email: { - type: 'string', - maxLength: 255, - format: 'email', - title: 'Email' - }, - is_active: { - type: 'boolean', - title: 'Is Active', - default: true - }, - is_superuser: { - type: 'boolean', - title: 'Is Superuser', - default: false - }, - full_name: { - anyOf: [ - { - type: 'string', - maxLength: 255 - }, - { - type: 'null' - } - ], - title: 'Full Name' - }, - id: { - type: 'string', - format: 'uuid', - title: 'Id' - }, - created_at: { - anyOf: [ - { - type: 'string', - format: 'date-time' - }, - { - type: 'null' - } - ], - title: 'Created At' - } - }, - type: 'object', - required: ['email', 'id'], - title: 'UserPublic' + properties: { + email: { + type: "string", + maxLength: 255, + format: "email", + title: "Email", + }, + is_active: { + type: "boolean", + title: "Is Active", + default: true, + }, + is_superuser: { + type: "boolean", + title: "Is Superuser", + default: false, + }, + full_name: { + anyOf: [ + { + type: "string", + maxLength: 255, + }, + { + type: "null", + }, + ], + title: "Full Name", + }, + id: { + type: "string", + format: "uuid", + title: "Id", + }, + created_at: { + anyOf: [ + { + type: "string", + format: "date-time", + }, + { + type: "null", + }, + ], + title: "Created At", + }, + }, + type: "object", + required: ["email", "id"], + title: "UserPublic", } as const; export const UserRegisterSchema = { - properties: { - email: { - type: 'string', - maxLength: 255, - format: 'email', - title: 'Email' - }, - password: { - type: 'string', - maxLength: 128, - minLength: 8, - title: 'Password' - }, - full_name: { - anyOf: [ - { - type: 'string', - maxLength: 255 - }, - { - type: 'null' - } - ], - title: 'Full Name' - } - }, - type: 'object', - required: ['email', 'password'], - title: 'UserRegister' + properties: { + email: { + type: "string", + maxLength: 255, + format: "email", + title: "Email", + }, + password: { + type: "string", + maxLength: 128, + minLength: 8, + title: "Password", + }, + full_name: { + anyOf: [ + { + type: "string", + maxLength: 255, + }, + { + type: "null", + }, + ], + title: "Full Name", + }, + }, + type: "object", + required: ["email", "password"], + title: "UserRegister", } as const; export const UserUpdateSchema = { - properties: { - email: { - anyOf: [ - { - type: 'string', - maxLength: 255, - format: 'email' - }, - { - type: 'null' - } - ], - title: 'Email' - }, - is_active: { - anyOf: [ - { - type: 'boolean' - }, - { - type: 'null' - } - ], - title: 'Is Active' - }, - is_superuser: { - anyOf: [ - { - type: 'boolean' - }, - { - type: 'null' - } - ], - title: 'Is Superuser' - }, - full_name: { - anyOf: [ - { - type: 'string', - maxLength: 255 - }, - { - type: 'null' - } - ], - title: 'Full Name' - }, - password: { - anyOf: [ - { - type: 'string', - maxLength: 128, - minLength: 8 - }, - { - type: 'null' - } - ], - title: 'Password' - } - }, - type: 'object', - title: 'UserUpdate' + properties: { + email: { + anyOf: [ + { + type: "string", + maxLength: 255, + format: "email", + }, + { + type: "null", + }, + ], + title: "Email", + }, + is_active: { + anyOf: [ + { + type: "boolean", + }, + { + type: "null", + }, + ], + title: "Is Active", + }, + is_superuser: { + anyOf: [ + { + type: "boolean", + }, + { + type: "null", + }, + ], + title: "Is Superuser", + }, + full_name: { + anyOf: [ + { + type: "string", + maxLength: 255, + }, + { + type: "null", + }, + ], + title: "Full Name", + }, + password: { + anyOf: [ + { + type: "string", + maxLength: 128, + minLength: 8, + }, + { + type: "null", + }, + ], + title: "Password", + }, + }, + type: "object", + title: "UserUpdate", } as const; export const UserUpdateMeSchema = { - properties: { - full_name: { - anyOf: [ - { - type: 'string', - maxLength: 255 - }, - { - type: 'null' - } - ], - title: 'Full Name' - }, - email: { - anyOf: [ - { - type: 'string', - maxLength: 255, - format: 'email' - }, - { - type: 'null' - } - ], - title: 'Email' - } - }, - type: 'object', - title: 'UserUpdateMe' + properties: { + full_name: { + anyOf: [ + { + type: "string", + maxLength: 255, + }, + { + type: "null", + }, + ], + title: "Full Name", + }, + email: { + anyOf: [ + { + type: "string", + maxLength: 255, + format: "email", + }, + { + type: "null", + }, + ], + title: "Email", + }, + }, + type: "object", + title: "UserUpdateMe", } as const; export const UsersPublicSchema = { - properties: { - data: { - items: { - '$ref': '#/components/schemas/UserPublic' - }, - type: 'array', - title: 'Data' - }, - count: { - type: 'integer', - title: 'Count' - } - }, - type: 'object', - required: ['data', 'count'], - title: 'UsersPublic' + properties: { + data: { + items: { + $ref: "#/components/schemas/UserPublic", + }, + type: "array", + title: "Data", + }, + count: { + type: "integer", + title: "Count", + }, + }, + type: "object", + required: ["data", "count"], + title: "UsersPublic", } as const; export const ValidationErrorSchema = { - properties: { - loc: { - items: { - anyOf: [ - { - type: 'string' - }, - { - type: 'integer' - } - ] - }, - type: 'array', - title: 'Location' - }, - msg: { - type: 'string', - title: 'Message' - }, - type: { - type: 'string', - title: 'Error Type' - }, - input: { - title: 'Input' - }, - ctx: { - type: 'object', - title: 'Context' - } - }, - type: 'object', - required: ['loc', 'msg', 'type'], - title: 'ValidationError' -} as const; \ No newline at end of file + properties: { + loc: { + items: { + anyOf: [ + { + type: "string", + }, + { + type: "integer", + }, + ], + }, + type: "array", + title: "Location", + }, + msg: { + type: "string", + title: "Message", + }, + type: { + type: "string", + title: "Error Type", + }, + input: { + title: "Input", + }, + ctx: { + type: "object", + title: "Context", + }, + }, + type: "object", + required: ["loc", "msg", "type"], + title: "ValidationError", +} as const; diff --git a/frontend/src/client/sdk.gen.ts b/frontend/src/client/sdk.gen.ts index 92a1745966..abb01e9579 100644 --- a/frontend/src/client/sdk.gen.ts +++ b/frontend/src/client/sdk.gen.ts @@ -3,9 +3,20 @@ import type { CancelablePromise } from './core/CancelablePromise'; import { OpenAPI } from './core/OpenAPI'; import { request as __request } from './core/request'; -import type { ArticlesReadArticlesData, ArticlesReadArticlesResponse, ArticlesSearchArticlesData, ArticlesSearchArticlesResponse, ItemsReadItemsData, ItemsReadItemsResponse, ItemsCreateItemData, ItemsCreateItemResponse, ItemsReadItemData, ItemsReadItemResponse, ItemsUpdateItemData, ItemsUpdateItemResponse, ItemsDeleteItemData, ItemsDeleteItemResponse, LoginLoginAccessTokenData, LoginLoginAccessTokenResponse, LoginTestTokenResponse, LoginRecoverPasswordData, LoginRecoverPasswordResponse, LoginResetPasswordData, LoginResetPasswordResponse, LoginRecoverPasswordHtmlContentData, LoginRecoverPasswordHtmlContentResponse, PrivateCreateUserData, PrivateCreateUserResponse, UsersReadUsersData, UsersReadUsersResponse, UsersCreateUserData, UsersCreateUserResponse, UsersReadUserMeResponse, UsersDeleteUserMeResponse, UsersUpdateUserMeData, UsersUpdateUserMeResponse, UsersUpdatePasswordMeData, UsersUpdatePasswordMeResponse, UsersRegisterUserData, UsersRegisterUserResponse, UsersReadUserByIdData, UsersReadUserByIdResponse, UsersUpdateUserData, UsersUpdateUserResponse, UsersDeleteUserData, UsersDeleteUserResponse, UtilsTestEmailData, UtilsTestEmailResponse, UtilsHealthCheckResponse } from './types.gen'; +import type { ArticlesReadArticlesData, ArticlesReadArticlesResponse, ArticlesSearchArticlesData, ArticlesSearchArticlesResponse, ItemsReadItemsData, ItemsReadItemsResponse, ItemsCreateItemData, ItemsCreateItemResponse, ItemsReadItemData, ItemsReadItemResponse, ItemsUpdateItemData, ItemsUpdateItemResponse, ItemsDeleteItemData, ItemsDeleteItemResponse, LoginLoginAccessTokenData, LoginLoginAccessTokenResponse, LoginTestTokenResponse, LoginRecoverPasswordData, LoginRecoverPasswordResponse, LoginResetPasswordData, LoginResetPasswordResponse, LoginRecoverPasswordHtmlContentData, LoginRecoverPasswordHtmlContentResponse, UsersReadUsersData, UsersReadUsersResponse, UsersCreateUserData, UsersCreateUserResponse, UsersReadUserMeResponse, UsersDeleteUserMeResponse, UsersUpdateUserMeData, UsersUpdateUserMeResponse, UsersUpdatePasswordMeData, UsersUpdatePasswordMeResponse, UsersRegisterUserData, UsersRegisterUserResponse, UsersReadUserByIdData, UsersReadUserByIdResponse, UsersUpdateUserData, UsersUpdateUserResponse, UsersDeleteUserData, UsersDeleteUserResponse, UtilsTestEmailData, UtilsTestEmailResponse, UtilsHealthCheckResponse } from './types.gen'; export class ArticlesService { + /** + * Read Articles + * @param data The data for the request. + * @param data.limit + * @param data.since + * @param data.minScore + * @param data.category + * @param data.kind + * @returns ArticlesPublic Successful Response + * @throws ApiError + */ public static readArticles(data: ArticlesReadArticlesData = {}): CancelablePromise { return __request(OpenAPI, { method: 'GET', @@ -15,21 +26,33 @@ export class ArticlesService { since: data.since, min_score: data.minScore, category: data.category, - kind: data.kind, + kind: data.kind }, - errors: { 422: 'Validation Error' }, + errors: { + 422: 'Validation Error' + } }); } - + + /** + * Search Articles + * @param data The data for the request. + * @param data.q + * @param data.limit + * @returns ArticlesPublic Successful Response + * @throws ApiError + */ public static searchArticles(data: ArticlesSearchArticlesData): CancelablePromise { return __request(OpenAPI, { method: 'GET', url: '/api/v1/articles/search', query: { q: data.q, - limit: data.limit, + limit: data.limit }, - errors: { 422: 'Validation Error' }, + errors: { + 422: 'Validation Error' + } }); } } @@ -242,28 +265,6 @@ export class LoginService { } } -export class PrivateService { - /** - * Create User - * Create a new user. - * @param data The data for the request. - * @param data.requestBody - * @returns UserPublic Successful Response - * @throws ApiError - */ - public static createUser(data: PrivateCreateUserData): CancelablePromise { - return __request(OpenAPI, { - method: 'POST', - url: '/api/v1/private/users/', - body: data.requestBody, - mediaType: 'application/json', - errors: { - 422: 'Validation Error' - } - }); - } -} - export class UsersService { /** * Read Users diff --git a/frontend/src/client/types.gen.ts b/frontend/src/client/types.gen.ts index 3f2fabd119..99deeb5a0d 100644 --- a/frontend/src/client/types.gen.ts +++ b/frontend/src/client/types.gen.ts @@ -8,7 +8,7 @@ export type ArticlePublic = { published_at?: (string | null); score?: (number | null); summary?: (string | null); - categories?: Array; + categories?: Array<(string)>; kind?: (string | null); id: number; created_at?: (string | null); @@ -19,23 +19,6 @@ export type ArticlesPublic = { count: number; }; -export type ArticlesReadArticlesData = { - limit?: number; - since?: (string | null); - minScore?: (number | null); - category?: (string | null); - kind?: (string | null); -}; - -export type ArticlesReadArticlesResponse = ArticlesPublic; - -export type ArticlesSearchArticlesData = { - q: string; - limit?: number; -}; - -export type ArticlesSearchArticlesResponse = ArticlesPublic; - export type Body_login_login_access_token = { grant_type?: (string | null); username: string; @@ -81,13 +64,6 @@ export type NewPassword = { new_password: string; }; -export type PrivateUserCreate = { - email: string; - password: string; - full_name: string; - is_verified?: boolean; -}; - export type Token = { access_token: string; token_type?: string; @@ -149,6 +125,23 @@ export type ValidationError = { }; }; +export type ArticlesReadArticlesData = { + category?: (string | null); + kind?: (string | null); + limit?: number; + minScore?: (number | null); + since?: (string | null); +}; + +export type ArticlesReadArticlesResponse = (ArticlesPublic); + +export type ArticlesSearchArticlesData = { + limit?: number; + q: string; +}; + +export type ArticlesSearchArticlesResponse = (ArticlesPublic); + export type ItemsReadItemsData = { limit?: number; skip?: number; @@ -207,12 +200,6 @@ export type LoginRecoverPasswordHtmlContentData = { export type LoginRecoverPasswordHtmlContentResponse = (string); -export type PrivateCreateUserData = { - requestBody: PrivateUserCreate; -}; - -export type PrivateCreateUserResponse = (UserPublic); - export type UsersReadUsersData = { limit?: number; skip?: number; From 94941395aadc891b87f36e7cd848096cc168ef22 Mon Sep 17 00:00:00 2001 From: Dimitar Slaev Date: Sun, 28 Jun 2026 00:26:07 +0200 Subject: [PATCH 05/42] ci: fix playwright on pr --- .github/workflows/playwright.yml | 2 ++ 1 file changed, 2 insertions(+) diff --git a/.github/workflows/playwright.yml b/.github/workflows/playwright.yml index a00ca3cf24..22cabf1d6c 100644 --- a/.github/workflows/playwright.yml +++ b/.github/workflows/playwright.yml @@ -69,11 +69,13 @@ jobs: # Before upgrading uv version, make sure astral-sh/setup-uv knows its checksum. # See: https://github.com/astral-sh/setup-uv/issues/851#issuecomment-4282017837 version: "0.11.18" + - run: touch .env - run: uv sync working-directory: backend - run: bun ci working-directory: frontend - run: bash scripts/generate-client.sh + - run: docker network create traefik-public 2>/dev/null || true - run: docker compose build - run: docker compose down -v --remove-orphans - name: Run Playwright tests From 06dbadb8cff06cdc03fae9837209d4c659e144bd Mon Sep 17 00:00:00 2001 From: Dimitar Slaev Date: Sun, 28 Jun 2026 00:55:11 +0200 Subject: [PATCH 06/42] feat(pipeline): initial migration --- plans/ingestion-pipeline-migration.md | 266 +++++++++ temp/source/baml_src/clients.baml | 29 + temp/source/baml_src/dedup.baml | 58 ++ temp/source/baml_src/discover.baml | 42 ++ temp/source/baml_src/extract_links.baml | 42 ++ temp/source/baml_src/extract_products.baml | 125 ++++ temp/source/baml_src/fix_titles.baml | 61 ++ temp/source/baml_src/generators.baml | 6 + temp/source/baml_src/score.baml | 84 +++ temp/source/baml_src/shared.baml | 33 ++ temp/source/baml_src/summarize.baml | 111 ++++ temp/source/pipeline/run.ts | 451 ++++++++++++++ temp/source/pipeline/search.ts | 83 +++ temp/source/pipeline/sources/ainews.ts | 334 +++++++++++ temp/source/pipeline/sources/email.ts | 551 ++++++++++++++++++ .../pipeline/sources/extract-content.ts | 145 +++++ temp/source/pipeline/sources/hn.ts | 60 ++ temp/source/pipeline/sources/rss.ts | 103 ++++ .../pipeline/sources/substack-sources.json | 430 ++++++++++++++ temp/source/pipeline/sources/substack.ts | 137 +++++ temp/source/pipeline/sources/utils.ts | 38 ++ temp/source/pipeline/steps.ts | 88 +++ temp/source/pipeline/utils.ts | 59 ++ temp/source/shared/db/articles.ts | 370 ++++++++++++ temp/source/shared/db/client.ts | 44 ++ temp/source/shared/db/meta.ts | 36 ++ temp/source/shared/db/urls.ts | 71 +++ temp/source/shared/db/users.ts | 182 ++++++ temp/source/shared/embeddings.ts | 35 ++ temp/source/shared/pricing.ts | 11 + temp/source/shared/schema.ts | 84 +++ temp/source/shared/types.ts | 57 ++ 32 files changed, 4226 insertions(+) create mode 100644 plans/ingestion-pipeline-migration.md create mode 100644 temp/source/baml_src/clients.baml create mode 100644 temp/source/baml_src/dedup.baml create mode 100644 temp/source/baml_src/discover.baml create mode 100644 temp/source/baml_src/extract_links.baml create mode 100644 temp/source/baml_src/extract_products.baml create mode 100644 temp/source/baml_src/fix_titles.baml create mode 100644 temp/source/baml_src/generators.baml create mode 100644 temp/source/baml_src/score.baml create mode 100644 temp/source/baml_src/shared.baml create mode 100644 temp/source/baml_src/summarize.baml create mode 100644 temp/source/pipeline/run.ts create mode 100644 temp/source/pipeline/search.ts create mode 100644 temp/source/pipeline/sources/ainews.ts create mode 100644 temp/source/pipeline/sources/email.ts create mode 100644 temp/source/pipeline/sources/extract-content.ts create mode 100644 temp/source/pipeline/sources/hn.ts create mode 100644 temp/source/pipeline/sources/rss.ts create mode 100644 temp/source/pipeline/sources/substack-sources.json create mode 100644 temp/source/pipeline/sources/substack.ts create mode 100644 temp/source/pipeline/sources/utils.ts create mode 100644 temp/source/pipeline/steps.ts create mode 100644 temp/source/pipeline/utils.ts create mode 100644 temp/source/shared/db/articles.ts create mode 100644 temp/source/shared/db/client.ts create mode 100644 temp/source/shared/db/meta.ts create mode 100644 temp/source/shared/db/urls.ts create mode 100644 temp/source/shared/db/users.ts create mode 100644 temp/source/shared/embeddings.ts create mode 100644 temp/source/shared/pricing.ts create mode 100644 temp/source/shared/schema.ts create mode 100644 temp/source/shared/types.ts diff --git a/plans/ingestion-pipeline-migration.md b/plans/ingestion-pipeline-migration.md new file mode 100644 index 0000000000..a30f94337d --- /dev/null +++ b/plans/ingestion-pipeline-migration.md @@ -0,0 +1,266 @@ +# Ingestion pipeline migration — Python rewrite on VPS + +**Goal:** Rewrite the TypeScript news-ingestion pipeline as a Python job running on the VPS, writing directly to Postgres. No HTTP ingest endpoint. Eliminates Node.js from the stack. + +**Shipping in two phases** (per decision): **v1** = HN + AI News + Substack sources end-to-end; **v2** = email/newsletter source as a fast follow. + +## Source reference + +The original TypeScript source is copied to `temp/source/` in this repo for reference during the rewrite: + +``` +temp/source/ + pipeline/ ← run.ts, steps.ts, utils.ts, search.ts, sources/* + baml_src/ ← all .baml prompt files + shared/ ← types.ts, embeddings.ts, db/articles.ts, db/urls.ts +``` + +Read these before porting each module — they are the authoritative reference for logic, prompt wording, and data shapes. **This plan is self-contained for cloud execution: an agent should be able to implement it from this file + `temp/source/` alone.** + +--- + +## Architecture + +``` +Docker compose service "pipeline" (cron, 04:00 daily) + └─ python -m pipeline.run + ├─ sources/hn.py ← HN API + keyword filter [v1] + ├─ sources/ainews.py ← news.smol.ai RSS, self-contained [v1] + ├─ sources/substack.py ← 100+ feeds + proxy/retry [v1] + ├─ sources/email.py ← IMAP + 3 BAML calls + Tavily [v2] + ├─ BAML Python client ← same .baml files, Python generator + ├─ model2vec ← potion-base-8M 256-d, same as backend + └─ SQLModel / Postgres ← direct writes via app.models_agentique +``` + +Pipeline lives in `backend/pipeline/` — same `uv` environment and `pyproject.toml` as the backend, so it can `from app.models_agentique import Article` directly and reuse the backend's embedding model. + +--- + +## Execution on VPS — dedicated compose service (DECIDED) + +The backend is Dockerized (`compose.yml`: `db`, `backend`, `frontend`, `prestart`, `adminer`). The pipeline runs as a **new compose service built from the backend image**, on the same network as `db`, with an internal scheduler. This keeps one Python environment, one image, and DB access over the internal Docker network (no exposed DB port). + +```yaml +# compose.yml — new service (sketch) +pipeline: + image: '${DOCKER_IMAGE_BACKEND?Variable not set}:${TAG-latest}' + networks: + - default + depends_on: + db: + condition: service_healthy + environment: + - DATABASE_URL=... # same as backend + - NVIDIA_NIM_API_KEY=... + - TAVILY_API_KEY=... # v2 + - IMAP_HOST/PORT/USER/PASSWORD=... # v2 + - RESIDENTIAL_PROXY_URL=... + command: supercronic /app/pipeline/crontab +``` + +Use **supercronic** (container-friendly cron, logs to stdout, no root cron daemon quirks) with a `crontab` file: + +```cron +0 4 * * * cd /app && python -m pipeline.run +``` + +Rationale over alternatives: a host-cron `docker compose exec` couples the schedule to host state; a host `uv` venv duplicates the Python env and forces exposing the DB port. The compose service is the most reproducible and matches how the rest of the stack is deployed. + +> Note: `compose.yml` is an upstream-owned file — adding a service is additive and low-conflict, but record it in `CHANGES.md`. + +--- + +## BAML migration + +Add a Python generator to `baml_src/generators.baml` (keep the existing TS generator — both can coexist): + +``` +generator python { + output_type "python/pydantic" + output_dir "../backend/" + version "0.223.0" +} +``` + +Run `baml generate` → produces `backend/baml_client/` (Python, pydantic models). **Commit it** (Docker builds from committed files; no `baml generate` at build time). No `.baml` prompt changes needed. LLM clients stay on NVIDIA NIM (`Fast`/`Nvidia`/`NvidiaGptOss`, same `NVIDIA_NIM_API_KEY`). + +### BAML functions actually used (CORRECTED — verified against source) + +| BAML function | Phase | Used in | +|---|---|---| +| `ScoreArticles` | v1 | score step | +| `SemanticDedup` | v1 | dedup-detect step (see "Dedup" below) | +| `ImproveTitles` | v1 | title cleanup | +| `SummarizeAndCategorize` | v1 | summarize + categorize | +| `CategorizeOnly` | v1 | fallback when no content extracted | +| `ClassifyKind` | v1 | fallback kind classification | +| `ExtractProducts` | **v2** | email — extract named products from newsletter HTML | +| `SelectNotableProducts` | **v2** | email — gate which products get web-searched | +| `SelectProductLink` | **v2** | email — pick best first-party URL among Tavily candidates | + +**Not ported** (not used by the ingestion pipeline): `ExtractLinks` (`extract_links.baml`), `ClassifyProfiles` (`discover.baml`) — these belong to a separate discovery feature. Leave their `.baml` files in place but generate-and-ignore. + +--- + +## Python dependencies to add (`backend/pyproject.toml`) + +| Package | Replaces | Phase | +|---|---|---| +| `baml-py` | `@boundaryml/baml` | v1 | +| `trafilatura` | `@mozilla/readability` + `linkedom` (extract-content) | v1 | +| `feedparser` | `rss-parser` (AI News, Substack RSS) | v1 | +| `httpx` | `fetchWithTimeout` / `undici` (incl. proxy support) | v1 | +| `dnspython` | `node:dns` dead-domain filter | v1 | +| `regex` | TS unicode-property regex in `sanitizeLlmText` (Python `re` lacks `\p{...}`) | v1 | +| `tavily-python` | `search.ts` Tavily client | v2 | +| `imapclient` | `imapflow` | v2 | +| `mail-parser` | `mailparser` | v2 | + +`model2vec`, `pgvector`, `sqlmodel` already present. + +> **Substack proxy:** `httpx` supports proxies natively (`httpx.Client(proxy=...)`). Port `substack.ts`'s retry-on-403/429 + residential-proxy-on-retry logic explicitly — it's not just "feedparser". See porting hazards. + +--- + +## DB additions + +### `ScoredUrl` table (new — add to `models_agentique.py`) + +```python +class ScoredUrl(SQLModel, table=True): + __tablename__ = "scored_url" + url: str = Field(primary_key=True) + created_at: datetime = Field(default_factory=get_datetime_utc) +``` + +New Alembic migration: `create table scored_url (url text primary key, created_at timestamptz)`. + +### `content` column — ALREADY EXISTS (CORRECTED) + +`models_agentique.py:28` already defines `content: str | None = Field(default="")`. **No migration needed.** (Earlier draft wrongly claimed it was missing.) + +### No `article_urls` table (per dedup decision below) + +The TS schema had an `article_urls` junction for URL aliasing. We are **not** porting it — see Dedup. + +--- + +## Dedup — detect and drop, no URL merge (DECIDED) + +The TS `dedupSemantic` step (run.ts:147–193) calls `SemanticDedup` to find new articles that match an existing recent DB article, then **merges** the new URL onto the existing article via `getArticleIdByUrl` + `addUrlToArticle` (the `article_urls` junction table). + +**v1 behavior:** keep the detection, drop the merge. Run `SemanticDedup` against recent articles (`GET`-equivalent query: `Article` where `published_at >= now-14d`), and simply **drop** any new article flagged as a duplicate. Do not record the dropped URL anywhere except `scored_url` (so it isn't re-evaluated). This removes the need for the `article_urls` table and the URL→ID lookup. Trade-off: we lose multi-source URL attribution for the same story — acceptable for v1. + +--- + +## Pipeline module layout (`backend/pipeline/`) + +``` +backend/pipeline/ + __init__.py + run.py ← entry point, mirrors run.ts + steps.py ← pure helpers: kind_from_url, trust_by_source, + github_repo_from_content, SCORE_THRESHOLD, PROMPT_CONTENT_CAP + utils.py ← log(), sanitize_llm_text() [regex lib], strip_title_wrappers(), wait() + crontab ← supercronic schedule + sources/ + __init__.py + utils.py ← fetch_with_timeout(), is_within_window(), clean_title() + extract_content.py + hn.py [v1] + ainews.py [v1] + substack.py [v1] + email.py [v2] +``` + +### run.py step mapping + +| TS function (run.ts) | Python equivalent | Notes | +|---|---|---| +| `fetchSource` | `fetch_source` | call source fetcher | +| `filterKnownUrls` | `filter_known_urls` | query `article.url` + `scored_url.url` | +| `filterDeadDomains` | `filter_dead_domains` | `dns.resolver` | +| `dedupSemantic` | `dedup_semantic` | `Article` recent query + `SemanticDedup`; **drop dups, no merge** | +| `scoreArticles` | `score_articles` | `ScoreArticles` batch 5; **Ben's Bites +10 bonus, cap 100**; `markUrlsScored` records **all** evaluated URLs | +| `insertArticles` | `insert_articles` | SQLModel insert; dedup-within-batch by URL keeping highest score | +| `improveTitles` | `improve_titles` | `ImproveTitles`, one call per article; skip if source name leaks into title | +| `extractFullContent` | `extract_full_content` | trafilatura; skip `aiNews`/`rss` sourceTypes (their prose is already the summary input) | +| `summarizeAndCategorize` | `summarize_and_categorize` | `SummarizeAndCategorize`, content capped at `PROMPT_CONTENT_CAP=1500`; fallback `CategorizeOnly`+`ClassifyKind`; **blog→repo override** if github repo in content | +| `embedArticles` | `embed_articles` | **model2vec** (drop NVIDIA NIM); text = `title\n\nsummary` | +| `markUrlsScored` | inline in `score_articles` | insert all evaluated URLs into `scored_url` | + +--- + +## Embedding — switch to model2vec (no risk; CORRECTED) + +The TS pipeline embedded with NVIDIA NIM `nv-embedqa-e5-v5` (**1024-d**, per the old Turso `F32_BLOB(1024)` schema). The new Postgres schema and **all 786 existing article embeddings are already model2vec `potion-base-8M` (256-d)** — `backend/scripts/import_articles.py` re-embedded everything at import time. So there is **no dimension mismatch and no data migration**: the pipeline just calls model2vec going forward. Reuse the backend's loader (`app.api.routes.articles.get_model` / `_embed`) or load the model once at pipeline start. + +--- + +## Porting hazards (verified against source — implement carefully) + +1. **`sanitize_llm_text` unicode regex** (utils.ts:43–59) uses `\p{Emoji_Presentation}` / `\p{Extended_Pictographic}` — Python `re` can't. Use the `regex` library. Applied to titles and summaries. +2. **Concurrency** — `Promise.allSettled` in `hn.py` (≤200 items) and `extract_content.py` → use `asyncio.gather(..., return_exceptions=True)` or a `ThreadPoolExecutor`; one failure must not abort the batch. +3. **Substack** (substack.ts) — retry on Cloudflare 403/429 with backoff, residential proxy **only on retry**, browser-header spoofing. Not "just feedparser". +4. **extract_content** (extract-content.ts) — 28 blocker regexes (paywall/login/JS-required), skip x.com/twitter.com, 5s timeout. `trafilatura` covers most extraction but **test blocker detection on real URLs**; port the skip-list explicitly. +5. **Scored URLs record ALL evaluated** (run.ts:239) — even sub-threshold articles go into `scored_url` so they're never re-scored. Don't filter to passing-only. +6. **Ben's Bites +10 bonus** (run.ts:231, capped 100) — source name must match exactly (`"Ben's Bites"`). +7. **blog→repo override** (run.ts:389) — if kind=blog and `github_repo_from_content` finds a real repo link (steps.ts:32–57, with non-repo-owner filter), set kind=repo. +8. **PROMPT_CONTENT_CAP=1500** — truncate content before `SummarizeAndCategorize`. + +--- + +## Runtime data files to carry over + +- `pipeline/sources/substack-sources.json` — 100+ Substack feed URLs. **Copy into `backend/pipeline/sources/`.** (Already in `temp/source/pipeline/sources/`.) +- Newsletter sender list (15 `NEWSLETTER_SOURCES`) is inline in `email.ts` → port into `email.py` constants [v2]. + +--- + +## Environment variables (VPS `.env`) + +Keep / add to the `pipeline` compose service: +- `DATABASE_URL` (same as backend) +- `NVIDIA_NIM_API_KEY` (BAML LLM calls) +- `RESIDENTIAL_PROXY_URL` (Substack) +- v2: `TAVILY_API_KEY`, `IMAP_HOST`, `IMAP_PORT`, `IMAP_USER`, `IMAP_PASSWORD` + +Remove (no longer used anywhere): `TURSO_DATABASE_URL`, `TURSO_AUTH_TOKEN`. + +--- + +## What does NOT change + +- `.baml` prompt files — untouched; only add the Python generator +- Frontend / API read endpoints — no change +- GH Actions CI/CD for the FastAPI app — no change +- The old TS `pipeline.yml` in the source repo — disable after the Python pipeline is confirmed stable + +--- + +## Implementation order + +### Phase 1 — core + RSS/HN sources +1. Add `ScoredUrl` table to `models_agentique.py` → Alembic migration (no `content` migration — it exists). +2. Add `generator python` to `baml_src/generators.baml`, run `baml generate`, commit `backend/baml_client/`. +3. Add v1 Python deps to `pyproject.toml`; `uv lock`. +4. Port `pipeline/utils.py` + `pipeline/steps.py` (pure helpers — `regex`-based sanitize, kind/github helpers, constants). +5. Port `sources/utils.py` + `sources/extract_content.py` (trafilatura). +6. Port `sources/hn.py` (smoke-test source). +7. Port `sources/ainews.py` + `sources/substack.py` (+ copy `substack-sources.json`). +8. Write `pipeline/run.py` wiring steps; dedup = detect-and-drop; embed = model2vec. +9. Add `pipeline` compose service + `crontab` (supercronic). Record `compose.yml` change in `CHANGES.md`. +10. Test locally against the local Docker DB with a `--limit`/dry-run flag; compare output rows to expectations. +11. Deploy; run once manually (`docker compose run --rm pipeline python -m pipeline.run`); monitor. + +### Phase 2 — email source +12. Add v2 deps (`tavily-python`, `imapclient`, `mail-parser`). +13. Port `sources/email.py`: IMAP fetch w/ backoff → `ExtractProducts` → dedup products → `SelectNotableProducts` → Tavily search (concurrency 5, deny-domains) → `SelectProductLink`. +14. Wire email into `SOURCES` in `run.py`; add IMAP/Tavily env to the compose service. +15. Test, deploy, monitor a real run. + +### Cutover +16. Disable the TS `pipeline.yml` in the source repo once stable. +17. Update `CHANGES.md` (new compose service, `ScoredUrl` table, new deps). +18. Remove `temp/source/` once the rewrite is done. diff --git a/temp/source/baml_src/clients.baml b/temp/source/baml_src/clients.baml new file mode 100644 index 0000000000..e9eaa343cc --- /dev/null +++ b/temp/source/baml_src/clients.baml @@ -0,0 +1,29 @@ +client Fast { + provider openai-generic + options { + base_url "https://integrate.api.nvidia.com/v1" + api_key env.NVIDIA_NIM_API_KEY + model "qwen/qwen3-next-80b-a3b-instruct" + timeout 60 + } +} + +client Nvidia { + provider openai-generic + options { + base_url "https://integrate.api.nvidia.com/v1" + api_key env.NVIDIA_NIM_API_KEY + model "moonshotai/kimi-k2.6" + timeout 60 + } +} + +client NvidiaGptOss { + provider openai-generic + options { + base_url "https://integrate.api.nvidia.com/v1" + api_key env.NVIDIA_NIM_API_KEY + model "openai/gpt-oss-120b" + timeout 60 + } +} diff --git a/temp/source/baml_src/dedup.baml b/temp/source/baml_src/dedup.baml new file mode 100644 index 0000000000..fd536bb051 --- /dev/null +++ b/temp/source/baml_src/dedup.baml @@ -0,0 +1,58 @@ +class DedupMatch { + url string @description("URL of the new article") + existingUrl string @description("URL of the existing article it duplicates") +} + +function SemanticDedup( + newArticles: ArticleInput[], + existingArticles: ExistingArticle[] +) -> DedupMatch[] { + client NvidiaGptOss + prompt #" + {{ _.role("system") }} + You are a semantic similarity engine. You compare article pairs and determine whether they cover the same underlying story. You focus on substance, not surface-level keyword overlap. + + {{ _.role("user") }} + You are given two lists: + 1. NEW articles that were just fetched + 2. EXISTING articles already in our database from the last 14 days + + Your job: identify which NEW articles are about the same story as an EXISTING article. Two articles are "the same story" if they cover the same announcement, release, event, or topic - even if from different sources or with different angles. + + NEW articles: + {% for a in newArticles %} + {{ loop.index }}. [{{ a.source }}] "{{ a.title }}" - {{ a.url }}{% if a.trust %} [trust: {{ a.trust }}]{% endif %} + {% if a.snippet %} {{ a.snippet }}{% endif %} + {% endfor %} + + EXISTING articles: + {% for a in existingArticles %} + {{ loop.index }}. [{{ a.source }}] "{{ a.title }}" - {{ a.url }} + {% endfor %} + + For each match, return the new article's URL and the existing article's URL. + If there are no duplicates, return an empty list. + + {{ ctx.output_format }} + "# +} + +test dedup_no_matches { + functions [SemanticDedup] + args { + newArticles [ + { + url "https://a.com/1" + title "Claude 4 released" + source "HN" + } + ] + existingArticles [ + { + url "https://b.com/1" + title "The state of Rust in 2026" + source "RSS" + } + ] + } +} diff --git a/temp/source/baml_src/discover.baml b/temp/source/baml_src/discover.baml new file mode 100644 index 0000000000..30a55c1ad4 --- /dev/null +++ b/temp/source/baml_src/discover.baml @@ -0,0 +1,42 @@ +// Batched relevance classifier for the Substack discovery crawler. +// One LLM call judges many candidate profiles at once (see ScoreArticles for +// the array-in/array-out batching pattern). Classification runs on cheap +// metadata (name + description) BEFORE any per-profile post fetch, and gates +// both DB insertion and whether the crawler recurses into that profile. + +class ProfileInput { + handle string @description("Substack owner handle, echoed back in the verdict") + name string @description("Publication name") + description string? @description("Publication hero text and/or author bio, if known") +} + +class ProfileVerdict { + handle string @description("Must exactly match the input handle") + isAiRelated bool + confidence int @description("0-100 confidence that AI/ML/LLMs is the PRIMARY focus") +} + +function ClassifyProfiles(profiles: ProfileInput[]) -> ProfileVerdict[] { + client Nvidia + prompt #" + {{ _.role("system") }} + You curate sources for a developer-focused AI news platform. For each Substack + publication, decide whether artificial intelligence is its PRIMARY subject: + AI/ML/LLMs, foundation models, AI engineering, AI products, or AI research. + + Mark isAiRelated = true ONLY when AI is clearly the main topic. Mark false for + general tech, productivity, marketing, business, crypto, politics, lifestyle, or + publications that merely mention AI in passing. When the signal is thin (sparse + description, generic name), lean false and assign low confidence - the crawler + prunes everything you reject, so false positives pollute the whole subtree. + + {{ _.role("user") }} + Classify every profile. Echo each handle back EXACTLY as given. + + {% for p in profiles %} + {{ loop.index }}. handle={{ p.handle }} | {{ p.name }}{% if p.description %} — {{ p.description }}{% endif %} + {% endfor %} + + {{ ctx.output_format }} + "# +} diff --git a/temp/source/baml_src/extract_links.baml b/temp/source/baml_src/extract_links.baml new file mode 100644 index 0000000000..579c0d8aa4 --- /dev/null +++ b/temp/source/baml_src/extract_links.baml @@ -0,0 +1,42 @@ +class ExtractedLink { + title string + url string + snippet string @description("One-sentence description of the article") +} + +function ExtractLinks(emailHtml: string) -> ExtractedLink[] { + client NvidiaGptOss + prompt #" + {{ _.role("system") }} + You are a precise link extraction engine. You parse newsletter HTML and identify external article links while filtering out tracking, admin, and promotional URLs. + + {{ _.role("user") }} + You are given the HTML body of a newsletter email. Extract all article links that point to external news stories, blog posts, research papers, or product announcements. + + For each article, return its title, URL, and a one-sentence snippet describing it. + + IGNORE these types of links: + - Tracking/redirect URLs (e.g. links through email marketing platforms) + - Unsubscribe, manage preferences, or email settings links + - Social media profile links (twitter, linkedin, etc.) + - Links back to the newsletter's own homepage, archive index, or subscription page (but DO include article/post links hosted on the newsletter's domain - curated newsletters often host their own content) + - Sponsor/advertisement links + - Job posting links + + RESOLVE redirect URLs: if a link is clearly a tracking redirect (contains /click, /track, utm_ params, etc.), try to extract the final destination URL from the href. Strip all UTM parameters from URLs. + + Newsletter HTML: + {{ emailHtml }} + + If no relevant article links are found, return an empty list. + + {{ ctx.output_format }} + "# +} + +test extract_links_basic { + functions [ExtractLinks] + args { + emailHtml "Welcome to today's issue! [Read OpenAI's new paper](https://openai.com/papers/gpt-5). [Unsubscribe](https://newsletter.com/unsubscribe)." + } +} diff --git a/temp/source/baml_src/extract_products.baml b/temp/source/baml_src/extract_products.baml new file mode 100644 index 0000000000..9e5f5a531a --- /dev/null +++ b/temp/source/baml_src/extract_products.baml @@ -0,0 +1,125 @@ +// Product-centric newsletter extraction. +// +// Replaces the per-newsletter tracking-URL resolvers: instead of decoding each +// provider's redirect scheme to recover the real link, we extract the *named +// products* a newsletter reports on (from anchor text + surrounding prose), +// keep only the notable ones, and rediscover their canonical URLs via web +// search (src/sources/email.ts). SelectProductLink then picks the best +// first-party result among the candidates. + +class NewsletterProduct { + name string @description("Exact product / tool / model / launch name") + description string @description("Concise phrase: what it is and does, usable verbatim as a web search query") +} + +function ExtractProducts(newsletterText: string) -> NewsletterProduct[] { + client NvidiaGptOss + prompt #" + {{ _.role("system") }} + You extract the AI/tech products, tools, models, and launches that a newsletter is reporting on. Work only from the text; never invent products that are not mentioned. + + {{ _.role("user") }} + Below is the text of a newsletter email. Links appear as [anchor text](url) but the URLs are often tracking redirects, so judge by the words, not the links. + + Identify every distinct product, tool, model, SDK, dataset, or launch the newsletter is reporting as news. For each, return: + - name: the exact product/tool/model name + - description: a concise phrase describing what it is and does, suitable as a web search query + + INCLUDE only real, named launches a reader could go use or read about. + + IGNORE: + - the author's intro letter, essay, or personal commentary + - sponsor blurbs, advertisements, "brought to you by", upgrade / subscribe / manage-preferences prompts + - social-media embeds (an @handle with like / repost / reply counts) and the newsletter's own social links + - section headers, navigation, and unsubscribe links + + Newsletter text: + {{ newsletterText }} + + If the text names no qualifying products, return an empty list. + + {{ ctx.output_format }} + "# +} + +// Notability gate: trims the extracted list to the launches actually worth +// resolving, so we don't spend a web search on every incremental SDK bump. +// Returns the 1-based indices of the products to KEEP. +function SelectNotableProducts(products: NewsletterProduct[]) -> int[] { + client Nvidia + prompt #" + {{ _.role("user") }} + Below is a numbered list of products/tools/models a newsletter mentioned. Return the numbers of the ones that are NOTABLE enough to feature in an AI-news aggregator. + + KEEP a product if it is a distinct, real, individually newsworthy launch a reader would want to click: new models, significant new products or platforms, notable agents/tools, major releases. + + DROP: + - minor or incremental items: small SDK/utility bumps, niche helper libraries, design skills, config tweaks + - vague or marketing-only entries with no concrete product behind them + - duplicates or sub-features of another item in the list + + Products: + {% for p in products %} + {{ loop.index }}. {{ p.name }} — {{ p.description }} + {% endfor %} + + Return only the numbers to keep, as a JSON array of integers. If none qualify, return []. + + {{ ctx.output_format }} + "# +} + +class SearchCandidate { + title string + url string + snippet string +} + +class ProductLinkChoice { + index int @description("1-based index of the best first-party result, or 0 if none qualifies") + confidence float @description("0.0 - 1.0") +} + +// Picks the best canonical URL for a product among search candidates, biased +// hard toward the official / first-party source and away from social posts and +// SEO/aggregator pages. Returns index 0 when nothing is clearly the product. +function SelectProductLink( + productName: string, + productDescription: string, + candidates: SearchCandidate[] +) -> ProductLinkChoice { + client Nvidia + prompt #" + {{ _.role("user") }} + A newsletter featured this item: + name: {{ productName }} + description: {{ productDescription }} + + Web search returned these candidate results: + {% for c in candidates %} + {{ loop.index }}. {{ c.title }} + url: {{ c.url }} + snippet: {{ c.snippet }} + {% endfor %} + + Pick the ONE candidate that is the canonical, first-party source for this exact product — its official site, product page, model card, repo, or the vendor's own announcement. + + PREFER the official / first-party domain that matches the product or its maker. + REJECT (do not pick) when it is the best available: + - social-media posts (x.com, twitter.com, linkedin.com, reddit.com, threads, mastodon) + - videos (youtube.com) + - content-farm / SEO / generic aggregator or listicle pages that merely mention the product + - a DIFFERENT product that happens to share the name + + Return the 1-based index of the best first-party result. If none of the candidates is clearly a first-party source for THIS product, return index 0. + + {{ ctx.output_format }} + "# +} + +test extract_products_basic { + functions [ExtractProducts] + args { + newsletterText "Headlines: [OpenAI ships GPT-5](https://sub.stack/redirect/2/abc), a new flagship model. Brought to you by Acme. [Unsubscribe](https://newsletter.com/unsub)." + } +} diff --git a/temp/source/baml_src/fix_titles.baml b/temp/source/baml_src/fix_titles.baml new file mode 100644 index 0000000000..9239b53d20 --- /dev/null +++ b/temp/source/baml_src/fix_titles.baml @@ -0,0 +1,61 @@ +class TitleFix { + url string @description("The exact URL from the matching input article - copy verbatim") + title string @description("Plain title text only. No surrounding quotes. No leading source name or bracket tag. Max 12 words. Return the input title verbatim if it is already clear, specific, and informative.") +} + +function ImproveTitles(articles: ArticleInput[]) -> TitleFix[] { + client NvidiaGptOss + prompt #" + {{ _.role("system") }} + You are a technical editor. You write clear, informative article titles for an AI developer news platform. + + Output rules (strict): + - For each input article, return one TitleFix whose `url` exactly matches that article's URL. + - The `title` field contains plain title text ONLY. Do NOT wrap it in quotes. Do NOT prefix it with "[Source]" or any source name. Do NOT include the URL. + - Use only the snippet of the SAME article to inform the rewrite. Never blend information across articles. + + {{ _.role("user") }} + Decide for each article whether the existing title is already good. A good title is specific, informative, and technical/neutral in register - it tells a developer what the article is actually about. + + - If the existing title is already good, return it verbatim. + - Otherwise rewrite it using only that article's snippet: specific, informative, max 12 words, technical/neutral register, no hype or filler. + + {% for a in articles %} + --- Article {{ loop.index }} --- + url: {{ a.url }} + source: {{ a.source }} + current_title: {{ a.title }} + {% if a.snippet %}snippet: {{ a.snippet }}{% endif %} + {% endfor %} + + {{ ctx.output_format }} + "# +} + +test improve_titles_rewrite_short { + functions [ImproveTitles] + args { + articles [ + { + url "https://example.com/claude" + title "Claude 4" + source "HN" + snippet "Anthropic today released Claude 4, a new flagship model with improved reasoning and a 1M-token context window." + } + ] + } +} + +test improve_titles_keep_unchanged { + functions [ImproveTitles] + args { + articles [ + { + url "https://example.com/post" + title "Anthropic releases Claude 4 with 1M-token context window" + source "HN" + snippet "Anthropic today released Claude 4, a new flagship model with improved reasoning." + } + ] + } +} diff --git a/temp/source/baml_src/generators.baml b/temp/source/baml_src/generators.baml new file mode 100644 index 0000000000..fdd48b14bb --- /dev/null +++ b/temp/source/baml_src/generators.baml @@ -0,0 +1,6 @@ +generator typescript { + output_type "typescript" + output_dir "../" + version "0.223.0" + default_client_mode "async" +} diff --git a/temp/source/baml_src/score.baml b/temp/source/baml_src/score.baml new file mode 100644 index 0000000000..01d73713df --- /dev/null +++ b/temp/source/baml_src/score.baml @@ -0,0 +1,84 @@ +class ScoredArticle { + url string + score int @description("1-100 developer-actionability rating") +} + +function ScoreArticles(articles: ArticleInput[]) -> ScoredArticle[] { + client Nvidia + prompt #" + {{ _.role("system") }} + You are a senior editorial analyst at a developer news platform. Your job is to evaluate articles for relevance and actionability for AI builders. You are precise, consistent, and ruthless about filtering noise. + + {{ _.role("user") }} + Score every article for developer-actionability on a 1-100 scale. + + STEP 1 - SCOPE CHECK (apply first, before scoring): + Is the article about AI, ML, LLMs, foundation models, or AI-adjacent developer tools/infrastructure? + - NO → score 1-20 and move on. Do NOT apply the scoring guide below. + - Out-of-scope examples: text editors, parsers, version control tools, data structures (CRDTs, B-trees), memory management, general programming tutorials, non-AI open source projects, codebase audits, legacy code. These are general software engineering - not AI. + + STEP 2 - SCORE (only for in-scope articles): + Audience: developers, startup founders, and tech leaders building with AI who want to ship faster. + + Score 91-100 is reserved for exceptional articles that are BOTH immediately actionable today AND fit one of these themes: local/on-device inference, privacy-preserving AI, efficiency breakthroughs (quantization, token optimization, running models on less hardware), or deep technical dives that explain how something actually works. A score in this range means "a developer could open a terminal and act on this within the hour, AND it reveals a non-obvious insight or technique." Zero is a valid outcome - do not give 91+ just because something is the best of a weak batch. + + Models (new releases, benchmarks, evals, model cards, comparisons): + - 81-90: New model release or major update, model system cards, open-weight models a developer can run today + - 71-80: Meaningful benchmark or eval, model comparison with actionable conclusions + + Dev (SDKs, frameworks, CLI tools, IDE integrations, open-source projects, tutorials, deployment): + - 81-90: New AI API or SDK, open-source AI tool/library a developer can use today + - 71-80: Fine-tuning guide, RAG pattern, significant framework update, AI infrastructure (training, inference, memory optimization), deployment recipes + + Research (papers, breakthroughs, novel techniques): + - 71-80: Research with immediate practical implications, AI security research + - 51-60: Research with near-term practical implications + + Industry (funding, platform changes, acquisitions, partnerships, market shifts): + - 51-60: Industry analysis with actionable takeaways, AI platform partnerships + - 31-40: Funding rounds without product details, opinion/commentary with no actionable steps, "AI is changing everything" think pieces, personal anecdotes about using AI + + Upgrade to 91-100: if an article would score 81-90 AND fits the top-tier criteria above (local inference, privacy-preserving, efficiency breakthrough, or deep how-it-works dive), give it 91-100. + + Bottom tier: + - 1-20: Non-AI topics (see step 1), regulation, politics, lawsuits, corporate drama + + Trust bonus: entries may include a [trust: high/medium/low] tag. Give +1 to high-trust sources when content quality is comparable. + + Articles: + {% for a in articles %} + {{ loop.index }}. [{{ a.source }}] "{{ a.title }}" - {{ a.url }}{% if a.trust %} [trust: {{ a.trust }}]{% endif %} + {% if a.snippet %} {{ a.snippet }}{% endif %} + {% endfor %} + + {{ ctx.output_format }} + "# +} + +test score_gpt5_release { + functions [ScoreArticles] + args { + articles [ + { + url "https://openai.com/index/introducing-gpt-5" + title "Introducing GPT-5" + source "Hacker News" + trust "medium" + } + ] + } +} + +test score_out_of_scope { + functions [ScoreArticles] + args { + articles [ + { + url "https://example.com/crdt-deep-dive" + title "A Deep Dive Into CRDTs and Conflict Resolution" + source "Some Blog" + trust "low" + } + ] + } +} diff --git a/temp/source/baml_src/shared.baml b/temp/source/baml_src/shared.baml new file mode 100644 index 0000000000..46d5b8ff35 --- /dev/null +++ b/temp/source/baml_src/shared.baml @@ -0,0 +1,33 @@ +// Shared types used by multiple BAML functions. + +enum ArticleCategory { + Models + Dev + Research +} + +enum ArticleKind { + Repo // GitHub/GitLab repository + Paper // Academic paper, preprint, technical report + Model // Model card or model release page + Blog // Developer blog post, tutorial, how-to, opinion piece + Product // Product launch page or product website + Announcement // Official release post from a major AI lab +} + +// Used as input to ScoreArticles, ImproveTitles, SemanticDedup. +// Mirrors the fields the existing formatArticles() helper emits. +class ArticleInput { + url string + title string + source string + snippet string? @description("First ~200 chars of the article content, if any") + trust string? @description("\"high\" | \"medium\" | \"low\" - source trust tag") +} + +// Used as input to SemanticDedup for rows already in the DB. +class ExistingArticle { + url string + title string + source string +} diff --git a/temp/source/baml_src/summarize.baml b/temp/source/baml_src/summarize.baml new file mode 100644 index 0000000000..59fecb7e0b --- /dev/null +++ b/temp/source/baml_src/summarize.baml @@ -0,0 +1,111 @@ +class SummarizeAndCategorizeResult { + summary string @description("2-3 short factual lines separated by \\n") + categories ArticleCategory[] @description("1-2 categories") + kind ArticleKind +} + +class CategorizeOnlyResult { + categories ArticleCategory[] @description("1-2 categories") +} + +class ClassifyKindResult { + kind ArticleKind +} + +function SummarizeAndCategorize(title: string, content: string) -> SummarizeAndCategorizeResult { + client NvidiaGptOss + prompt #" + {{ _.role("system") }} + You are a technical writer for a developer news digest. Your readers are tech-savvy but busy. Write in plain, direct language. + + {{ _.role("user") }} + Summarize this article. Be plain and brief. + + Title: {{ title }} + + Content: + {{ content }} + + 1. Write 2-3 lines. Keep each line to one short sentence. Rules: + - Only state facts from the article. + - No passive voice. No "enables", "allows", "provides". + - Separate lines with a newline. + 2. Assign 1-2 categories. + 3. Assign a kind. + + Category definitions: + - Models: New model releases, benchmarks, evals, model cards, model comparisons + - Dev: Repos, tools, product launches, developer blogs, tutorials, how-tos, fine-tuning guides, deployment recipes, infrastructure updates + - Research: Papers, breakthroughs, novel techniques with practical implications + + Kind definitions: + - Repo: GitHub or GitLab repository + - Paper: Academic paper, preprint, or long-form technical report + - Model: Model card or model release page (e.g. HuggingFace) + - Blog: Developer blog post, tutorial, how-to, or opinion piece + - Product: Product launch page or product website + - Announcement: Official release post from a major AI lab (OpenAI, Anthropic, Google, Meta, Mistral, etc.) + + {{ ctx.output_format }} + "# +} + +function ClassifyKind(title: string, url: string, summary: string?) -> ClassifyKindResult { + client NvidiaGptOss + prompt #" + {{ _.role("system") }} + You are a technical librarian who classifies AI developer content by format. + + {{ _.role("user") }} + Classify this article's kind. + + Title: {{ title }} + URL: {{ url }} + {% if summary %}Summary: {{ summary }}{% endif %} + + Kind definitions: + - Repo: GitHub or GitLab repository + - Paper: Academic paper, preprint, or long-form technical report + - Model: Model card or model release page (e.g. HuggingFace) + - Blog: Developer blog post, tutorial, how-to, or opinion piece + - Product: Product launch page or product website + - Announcement: Official release post from a major AI lab (OpenAI, Anthropic, Google, Meta, Mistral, etc.) + + {{ ctx.output_format }} + "# +} + +function CategorizeOnly(title: string) -> CategorizeOnlyResult { + client NvidiaGptOss + prompt #" + {{ _.role("system") }} + You are a technical librarian who classifies developer-focused AI articles. + + {{ _.role("user") }} + Assign 1-2 categories to this article title. + + Title: {{ title }} + + Category definitions: + - Models: New model releases, benchmarks, evals, model cards, model comparisons + - Dev: Repos, tools, product launches, developer blogs, tutorials, how-tos, fine-tuning guides, deployment recipes, infrastructure updates + - Research: Papers, breakthroughs, novel techniques with practical implications + + {{ ctx.output_format }} + "# +} + +test summarize_basic { + functions [SummarizeAndCategorize] + args { + title "Anthropic releases Claude 4" + content "Anthropic today launched Claude 4, a new flagship model. It features improved reasoning, a 1M-token context window, and native tool use. The model is available via API and Claude.ai starting today." + } +} + +test categorize_only_basic { + functions [CategorizeOnly] + args { + title "OpenAI releases GPT-5 with 2M context" + } +} diff --git a/temp/source/pipeline/run.ts b/temp/source/pipeline/run.ts new file mode 100644 index 0000000000..56c728611b --- /dev/null +++ b/temp/source/pipeline/run.ts @@ -0,0 +1,451 @@ +import "dotenv/config"; +import { promises as dnsPromises } from "node:dns"; +import { setLogLevel } from "@boundaryml/baml/logging"; +import { + getRecentArticles, + insertArticle, + updateCategories, + updateContent, + updateEmbedding, + updateKind, + updateScore, + updateTitle, +} from "@shared/db/articles"; +import { + addUrlToArticle, + getArticleIdByUrl, + markUrlsScored, + scoredUrlsExist, + urlsExist, +} from "@shared/db/urls"; +import { embeddingToVecString, getEmbedding } from "@shared/embeddings"; +import type { FetchedArticle } from "@shared/types"; +import { b } from "../baml_client"; +import type { ExistingArticle } from "../baml_client/types"; +import { fetchAiNews } from "./sources/ainews"; +import { fetchNewsletter } from "./sources/email"; +import { reExtractFullContent } from "./sources/extract-content"; +import { fetchHN } from "./sources/hn"; +// import { fetchRss } from "../sources/rss"; +import { fetchSubstack } from "./sources/substack"; +import { + githubRepoFromContent, + kindFromUrl, + SCORE_THRESHOLD, + toArticleInputs, +} from "./steps"; +import { log, sanitizeLlmText, stripTitleWrappers, wait } from "./utils"; + +const SOURCES: { label: string; fetcher: () => Promise }[] = [ + { label: "Hacker News", fetcher: fetchHN }, + { label: "Newsletter", fetcher: fetchNewsletter }, + { label: "AI News", fetcher: fetchAiNews }, + { label: "Substack", fetcher: fetchSubstack }, + // { label: "RSS", fetcher: fetchRss }, +]; + +const PROMPT_CONTENT_CAP = 1500; + +export async function runPipeline(): Promise { + log("=== Pipeline start ==="); + const start = Date.now(); + + const all: Awaited> = []; + + for (const src of SOURCES) { + log(`\n=== Processing ${src.label} ===`); + + const fetched = await fetchSource(src.fetcher, src.label); + const fresh = await filterKnownUrls(fetched, src.label); + const alive = await filterDeadDomains(fresh, src.label); + const unique = await dedupSemantic(alive, src.label); + const scored = await scoreArticles(unique); + const inserted = await insertArticles(scored); + await improveTitles(inserted); + const withContent = await extractFullContent(inserted); + const processed = await summarizeAndCategorize(withContent); + await embedArticles(processed); + + all.push(...processed); + } + + const elapsed = ((Date.now() - start) / 1000).toFixed(1); + log(`=== Pipeline complete in ${elapsed}s ===`); +} + +// ─── Steps ─────────────────────────────────────────────────────────────────── + +/** Step 01 - Call the source fetcher; log if nothing came back. */ +async function fetchSource( + fetcher: () => Promise, + label: string, +): Promise { + const articles = await fetcher(); + if (articles.length === 0) log(`No articles from ${label}`); + return articles; +} + +/** Step 02 - Drop URLs already present in articles or scored_urls. */ +async function filterKnownUrls( + articles: FetchedArticle[], + label: string, +): Promise { + if (articles.length === 0) return []; + + const allUrls = articles.map((a) => a.url); + const existing = await urlsExist(allUrls); + const alreadyScored = await scoredUrlsExist(allUrls); + const fresh = articles.filter( + (a) => !existing.has(a.url) && !alreadyScored.has(a.url), + ); + + if (existing.size > 0 || alreadyScored.size > 0) { + log( + ` Filtered ${existing.size} known + ${alreadyScored.size} already-scored URLs`, + ); + } + if (fresh.length === 0) { + log(` No new articles from ${label}`); + return []; + } + log(` ${fresh.length} new articles to process`); + return fresh; +} + +/** Step 02b - Drop articles whose hostname does not resolve in DNS. */ +async function filterDeadDomains( + articles: FetchedArticle[], + label: string, +): Promise { + if (articles.length === 0) return articles; + + const checks = await Promise.all( + articles.map(async (a) => ({ + article: a, + ok: await isDomainResolvable(a.url), + })), + ); + + const alive = checks.filter((c) => c.ok).map((c) => c.article); + const deadCount = checks.length - alive.length; + if (deadCount > 0) { + for (const c of checks) { + if (!c.ok) log(` Dropped dead URL: ${c.article.url}`); + } + log(` Filtered ${deadCount} dead-domain URLs from ${label}`); + } + return alive; +} + +async function isDomainResolvable(url: string): Promise { + let host: string; + try { + host = new URL(url).hostname; + } catch { + return false; + } + try { + await dnsPromises.lookup(host); + return true; + } catch (e) { + return (e as NodeJS.ErrnoException)?.code !== "ENOTFOUND"; + } +} + +/** + * Step 03 - Drop articles that are the same story as a recent DB entry. + * Merges the duplicate URL onto the existing row; falls back gracefully on AI failure. + */ +async function dedupSemantic( + articles: FetchedArticle[], + label: string, +): Promise { + if (articles.length === 0) return articles; + + const recentDb = await getRecentArticles(14); + if (recentDb.length === 0) return articles; + + log(` Deduplicating against ${recentDb.length} recent DB articles...`); + + const newInput = toArticleInputs(articles); + + const existingInput = recentDb.map( + (a): ExistingArticle => ({ + url: a.url, + title: a.title, + source: a.source, + }), + ); + + try { + const matches = await b.SemanticDedup(newInput, existingInput); + + for (const match of matches) { + const existingId = await getArticleIdByUrl(match.existingUrl); + if (existingId) { + await addUrlToArticle(match.url, existingId); + log(` Merged: ${match.url} -> existing article #${existingId}`); + } + } + + const mergedUrls = new Set(matches.map((m) => m.url)); + const unique = articles.filter((a) => !mergedUrls.has(a.url)); + if (mergedUrls.size > 0) + log(` ${mergedUrls.size} articles merged with existing`); + if (unique.length === 0) log(` No new unique articles from ${label}`); + return unique; + } catch (err) { + log(` Dedup failed, continuing without: ${err}`); + return articles; + } +} + +/** + * Step 04 - Score articles via BAML; keep those >= SCORE_THRESHOLD. + * Records ALL evaluated URLs in scored_urls so they're skipped next run. + * Ben's Bites gets a +10 bonus (capped at 100) to offset its summarized style. + */ +async function scoreArticles( + articles: FetchedArticle[], +): Promise<{ article: FetchedArticle; score: number }[]> { + if (articles.length === 0) return []; + + log(` Scoring ${articles.length} articles in batches of 10...`); + + const BATCH = 5; + const allScores: { url: string; score: number }[] = []; + for (let i = 0; i < articles.length; i += BATCH) { + const batch = toArticleInputs(articles.slice(i, i + BATCH)); + const result = await b.ScoreArticles(batch); + allScores.push(...result); + log( + ` batch ${Math.ceil((i + BATCH) / BATCH)}/${Math.ceil(articles.length / BATCH)} done`, + ); + await wait(1000); + } + + const scoreByUrl = new Map(allScores.map((s) => [s.url, s.score])); + const scored = articles + .map((a) => { + let score = scoreByUrl.get(a.url) ?? 0; + if (a.source === "Ben's Bites") score = Math.min(score + 10, 100); + return { article: a, score }; + }) + .sort((a, b) => b.score - a.score); + + const kept = scored.filter((s) => s.score >= SCORE_THRESHOLD); + log(` ${kept.length} articles pass scoring (threshold: ${SCORE_THRESHOLD})`); + + await markUrlsScored(articles.map((a) => a.url)); + + return kept; +} + +/** Step 05 - Insert scored articles into the DB; returns id+article+score triples. */ +async function insertArticles( + scored: { article: FetchedArticle; score: number }[], +): Promise<{ id: number; article: FetchedArticle; score: number }[]> { + if (scored.length === 0) return []; + + // Dedup within batch: same URL from multiple newsletters - keep highest score + const byUrl = new Map(); + for (const item of scored) { + const existing = byUrl.get(item.article.url); + if (!existing || item.score > existing.score) + byUrl.set(item.article.url, item); + } + const deduped = [...byUrl.values()]; + + const inserted: { id: number; article: FetchedArticle; score: number }[] = []; + for (const { article, score } of deduped) { + article.title = sanitizeLlmText(article.title); + const id = await insertArticle(article); + await updateScore(id, score); + inserted.push({ id, article, score }); + log(` Inserted #${id}: [${score}/10] ${article.title}`); + } + return inserted; +} + +/** + * Step 06 - Send every inserted article through ImproveTitles, one per call. + * Per-article calls eliminate cross-batch hallucinations we observed at batch + * sizes of 5+ (model occasionally attached one article's snippet to another's URL). + */ +async function improveTitles( + inserted: { id: number; article: FetchedArticle; score: number }[], +): Promise { + if (inserted.length === 0) return; + + log(` Improving ${inserted.length} titles...`); + + for (const { id, article } of inserted) { + const input = toArticleInputs([article]); + try { + const fixes = await b.ImproveTitles(input); + const raw = fixes[0]?.title; + if (!raw) continue; + const sanitized = sanitizeLlmText(stripTitleWrappers(raw)); + if (!sanitized || sanitized === article.title) continue; + if (sanitized.toLowerCase().includes(article.source.toLowerCase())) { + log( + ` Skip rewrite #${id} (source name leaked into output): "${sanitized}"`, + ); + continue; + } + const oldTitle = article.title; + await updateTitle(id, sanitized); + article.title = sanitized; + log(` Improved title #${id}: "${oldTitle}" → "${sanitized}"`); + } catch (err) { + log(` Title improve failed for #${id}, continuing: ${err}`); + } + } +} + +/** + * Step 07 - Re-fetch full article text for kept articles (uncapped). + * AI News items are skipped - their recap prose is already the right input for step 08. + */ +async function extractFullContent( + inserted: { id: number; article: FetchedArticle; score: number }[], +): Promise< + { id: number; article: FetchedArticle; score: number; fullContent: string }[] +> { + if (inserted.length === 0) return []; + + const toExtract = inserted.filter( + (a) => a.article.sourceType !== "aiNews" && a.article.sourceType !== "rss", + ); + const contentMap = await reExtractFullContent( + toExtract.map((a) => ({ url: a.article.url })), + ); + + for (const { id, article } of toExtract) { + const full = contentMap.get(article.url); + if (full) await updateContent(id, full); + } + + return inserted.map((item) => { + if ( + item.article.sourceType === "aiNews" || + item.article.sourceType === "rss" + ) { + return { ...item, fullContent: item.article.content }; + } + return { ...item, fullContent: contentMap.get(item.article.url) ?? "" }; + }); +} + +/** + * Step 08 - Summarize and categorize each article. + * Falls back to CategorizeOnly (title-only) when no body was extracted. + * Demotes non-Models 10/10 scores to 9 to keep the top bar meaningful. + */ +async function summarizeAndCategorize( + items: { + id: number; + article: FetchedArticle; + score: number; + fullContent: string; + }[], +): Promise< + { + id: number; + url: string; + title: string; + score: number; + summary: string; + categories: string[]; + }[] +> { + if (items.length === 0) return []; + + log(` Summarizing and categorizing ${items.length} articles...`); + + const processed: { + id: number; + url: string; + title: string; + score: number; + summary: string; + categories: string[]; + }[] = []; + + for (const { id, article, score, fullContent } of items) { + let summary = ""; + let categories: string[] = []; + let kind: string | null = kindFromUrl(article.url); + + try { + if (fullContent) { + const result = await b.SummarizeAndCategorize( + article.title, + fullContent.slice(0, PROMPT_CONTENT_CAP), + ); + summary = sanitizeLlmText(result.summary ?? ""); + categories = result.categories.map((c) => c.toLowerCase()); + if (!kind) kind = result.kind.toLowerCase(); + if (kind === "blog" && githubRepoFromContent(fullContent)) + kind = "repo"; + } else { + const result = await b.CategorizeOnly(article.title); + categories = result.categories.map((c) => c.toLowerCase()); + if (!kind) { + const kindResult = await b.ClassifyKind( + article.title, + article.url, + undefined, + ); + kind = kindResult.kind.toLowerCase(); + } + } + } catch (err) { + log(` Summarize/categorize failed for #${id}: ${err}`); + } + + await updateCategories(id, summary, categories); + if (kind) await updateKind(id, kind); + + processed.push({ + id, + url: article.url, + title: article.title, + score, + summary, + categories, + }); + } + + log(` Done summarizing and categorizing`); + return processed; +} + +/** Step 09 - Generate and store a semantic embedding for each processed article. */ +async function embedArticles( + items: { id: number; title: string; summary: string }[], +): Promise { + if (items.length === 0) return; + + log(` Embedding ${items.length} articles...`); + + for (const { id, title, summary } of items) { + try { + const text = summary ? `${title}\n\n${summary}` : title; + const vec = await getEmbedding(text, "passage"); + await updateEmbedding(id, embeddingToVecString(vec)); + } catch (err) { + log(` Embed failed for #${id}: ${err}`); + } + } +} + +// CLI entry point +if (!process.env.BAML_LOG) setLogLevel("ERROR"); + +runPipeline() + .then(() => process.exit(0)) + .catch((err) => { + console.error(err); + process.exit(1); + }); diff --git a/temp/source/pipeline/search.ts b/temp/source/pipeline/search.ts new file mode 100644 index 0000000000..01fea3efb4 --- /dev/null +++ b/temp/source/pipeline/search.ts @@ -0,0 +1,83 @@ +// Tavily Search API client. +// Set TAVILY_API_KEY in your environment. +// +// Usage: +// const results = await search("OpenShell v0.0.26 microVM AI agents", { maxResults: 3 }); + +import { log } from "./utils"; + +const TAVILY_API_URL = "https://api.tavily.com/search"; + +export interface SearchResult { + title: string; + url: string; + description: string; +} + +export interface SearchOptions { + /** Max results to return (default: 5). */ + maxResults?: number; +} + +export async function search( + query: string, + options: SearchOptions = {}, +): Promise { + const apiKey = process.env.TAVILY_API_KEY; + if (!apiKey) throw new Error("TAVILY_API_KEY is not set"); + + const { maxResults = 5 } = options; + + const res = await fetch(TAVILY_API_URL, { + method: "POST", + headers: { "Content-Type": "application/json" }, + body: JSON.stringify({ api_key: apiKey, query, max_results: maxResults }), + }); + + if (!res.ok) { + throw new Error(`Tavily Search API error: ${res.status} ${res.statusText}`); + } + + const data = (await res.json()) as { + results?: { title: string; url: string; content?: string }[]; + }; + + return (data.results ?? []).map((r) => ({ + title: r.title, + url: r.url, + description: r.content ?? "", + })); +} + +/** + * Given an x.com / twitter.com URL and a title/description, searches for + * the underlying article and returns the best non-Twitter result URL. + * Returns null if nothing useful is found. + */ +export async function resolveTwitterUrl( + title: string, + description: string, +): Promise { + // Strip twitter handles (@Foo -) and RSS formatting noise from the title + const cleanTitle = title.replace(/^@\w+\s+[-–-]\s+/, "").trim(); + + // Use title + first sentence of description as query + const firstSentence = description.split(/\.\s+/)[0]?.trim() ?? ""; + const query = firstSentence ? `${cleanTitle} ${firstSentence}` : cleanTitle; + + try { + const results = await search(query, { maxResults: 5 }); + + const BLOCKED = ["x.com", "twitter.com", "t.co"]; + const match = results.find((r) => !BLOCKED.some((b) => r.url.includes(b))); + + if (match) { + log(` Resolved to: ${match.url}`); + return match.url; + } + } catch (err) { + log(` Search failed: ${err}`); + } + + return null; +} diff --git a/temp/source/pipeline/sources/ainews.ts b/temp/source/pipeline/sources/ainews.ts new file mode 100644 index 0000000000..d0fcd1f632 --- /dev/null +++ b/temp/source/pipeline/sources/ainews.ts @@ -0,0 +1,334 @@ +// AI News source - extracts sub-stories from the news.smol.ai RSS feed. +// +// AI News is a daily aggregator of X/Twitter, Reddit, and Discord AI content. +// Each issue has two useful sections: +// -

AI Twitter Recap

- one editorial top-story per issue +// -

AI Reddit Recap

- multiple reddit posts, one per +// +// We turn each issue into multiple FetchedArticle entries: +// - One twitter-recap sub-story (title = first , primary URL = best +// non-tweet link, content = first few bullets as summary) +// - N reddit-recap sub-stories (one per reddit post anchor) +// +// Primary-URL priority: github > huggingface > arxiv > blog > reddit > tweet. +// +// This file is deliberately self-contained and does NOT reuse email.ts logic. + +import type { FetchedArticle } from "@shared/types"; +import { log } from "../utils"; +import { fetchWithTimeout, isWithinWindow } from "./utils"; + +const FEED_URL = "https://news.smol.ai/rss.xml"; +const MAX_CONTENT_LENGTH = 1400; +const MIN_REDDIT_BODY_LENGTH = 120; +const MIN_TWITTER_TITLE_LENGTH = 10; + +type PrimaryKind = + | "tweet" + | "reddit" + | "github" + | "huggingface" + | "arxiv" + | "blog" + | "other"; + +// ---------- feed parsing (no deps) ---------- + +const HTML_ENTITIES: Record = { + "<": "<", + ">": ">", + """: '"', + "'": "'", + "'": "'", + "&": "&", + " ": " ", + "&": "&", +}; + +function decodeHtml(s: string): string { + return s.replace( + /&(?:lt|gt|quot|apos|#x27|#x26|nbsp|amp);/g, + (m) => HTML_ENTITIES[m], + ); +} + +function pickTag(block: string, tag: string): string { + const match = block.match(new RegExp(`<${tag}>([\\s\\S]*?)`)); + if (!match) return ""; + const cdata = match[1].match(/^$/); + return cdata ? cdata[1] : match[1]; +} + +interface RssItem { + title: string; + link: string; + contentHtml: string; + pubDate: string; +} + +function parseFeed(xml: string): RssItem[] { + return xml + .split("") + .slice(1) + .map((chunk) => { + const body = chunk.split("")[0]; + return { + title: pickTag(body, "title"), + link: pickTag(body, "link"), + contentHtml: decodeHtml(pickTag(body, "content:encoded")), + pubDate: pickTag(body, "pubDate"), + }; + }); +} + +// ---------- HTML helpers ---------- + +function stripTags(html: string): string { + return html + .replace(/<[^>]+>/g, " ") + .replace(/\s+/g, " ") + .trim(); +} + +function firstBold(html: string): string { + const match = html.match(/]*>([\s\S]*?)<\/strong>/); + return match ? stripTags(match[1]) : ""; +} + +interface Link { + url: string; + host: string; + text: string; +} + +function hostOf(url: string): string { + try { + return new URL(url).hostname.replace(/^www\./, ""); + } catch { + return ""; + } +} + +function collectLinks(html: string): Link[] { + const matches = html.matchAll(/]+href="([^"]+)"[^>]*>([\s\S]*?)<\/a>/g); + return [...matches].map((m) => ({ + url: m[1], + host: hostOf(m[1]), + text: stripTags(m[2]), + })); +} + +/** + * Extract the HTML region between a given

and the next

. + * Returns an empty string when the heading is not present. + */ +function sliceSection(html: string, headingRx: RegExp): string { + const start = html.search(headingRx); + if (start === -1) return ""; + const afterStart = html.slice(start).replace(headingRx, ""); + const nextH1 = afterStart.search(/]*>/i); + return nextH1 === -1 ? afterStart : afterStart.slice(0, nextH1); +} + +// ---------- primary-URL priority ---------- + +const BLOG_HOST_RX = + /\b(openai|anthropic|deepmind|google|meta|microsoft|nvidia|mistral|unsloth|databricks|cohere|stability|perplexity|vercel|modal|together|replicate|groq)\b/; + +function classifyHost(host: string): PrimaryKind | null { + if (host === "github.com" || host.endsWith(".github.io")) return "github"; + if (host === "huggingface.co" || host === "hf.co") return "huggingface"; + if (host === "arxiv.org" || host === "ar5iv.labs.arxiv.org") return "arxiv"; + if ( + BLOG_HOST_RX.test(host) || + host.endsWith(".ai") || + host.endsWith(".dev") || + host.includes("substack.com") + ) { + return "blog"; + } + if (host === "reddit.com" || host.endsWith(".reddit.com")) return "reddit"; + if (host === "x.com" || host === "twitter.com") return "tweet"; + return null; +} + +// Priority order applied when picking a primary link for a sub-story. +const PRIMARY_PRIORITY: PrimaryKind[] = [ + "github", + "huggingface", + "arxiv", + "blog", + "reddit", + "tweet", +]; + +function isJunk(link: Link): boolean { + if (!link.url) return true; + if ( + link.host === "news.smol.ai" || + link.host === "latent.space" || + link.host === "support.substack.com" || + link.host === "i.redd.it" || + link.host === "preview.redd.it" + ) { + return true; + } + if (link.url.includes("twitter.com/i/lists/")) return true; + if (link.url.includes("x.com/i/")) return true; + return false; +} + +function pickPrimary(links: Link[]): { url: string; kind: PrimaryKind } { + const clean = links.filter((l) => !isJunk(l)); + if (clean.length === 0) return { url: "", kind: "other" }; + + for (const kind of PRIMARY_PRIORITY) { + const hit = clean.find((l) => classifyHost(l.host) === kind); + if (hit) return { url: hit.url, kind }; + } + return { url: clean[0].url, kind: "other" }; +} + +// ---------- Twitter Recap (one sub-story per issue) ---------- + +interface SubStory { + title: string; + url: string; + content: string; +} + +function extractTwitterRecap(html: string): SubStory | null { + const region = sliceSection(html, /]*>\s*AI Twitter Recap\s*<\/h1>/i); + if (!region) return null; + + const title = firstBold(region); + if (!title || title.length < MIN_TWITTER_TITLE_LENGTH) return null; + + const { url } = pickPrimary(collectLinks(region)); + if (!url) return null; + + // Use the first few bullets as the summary instead of the full recap. + const firstBullets = [...region.matchAll(/
  • ([\s\S]*?)<\/li>/g)] + .slice(0, 3) + .map((m) => stripTags(m[1])) + .join(" "); + const summary = + firstBullets || stripTags(region).slice(0, MAX_CONTENT_LENGTH); + + return { title, url, content: summary.slice(0, MAX_CONTENT_LENGTH) }; +} + +// ---------- Reddit Recap (one sub-story per post anchor) ---------- + +const REDDIT_ANCHOR_RX = + /]+href="(https?:\/\/(?:www\.)?reddit\.com\/r\/[^"]+\/comments\/[^"]+)"[^>]*>([\s\S]*?)<\/a>/g; + +interface RedditAnchor { + url: string; + title: string; + start: number; + end: number; +} + +function findRedditAnchors(region: string): RedditAnchor[] { + const anchors: RedditAnchor[] = []; + for (const match of region.matchAll(REDDIT_ANCHOR_RX)) { + anchors.push({ + url: match[1], + title: stripTags(match[2]), + start: match.index ?? 0, + end: (match.index ?? 0) + match[0].length, + }); + } + return anchors; +} + +function extractRedditRecap(html: string): SubStory[] { + const region = sliceSection(html, /]*>\s*AI Reddit Recap\s*<\/h1>/i); + if (!region) return []; + + const anchors = findRedditAnchors(region); + const stories: SubStory[] = []; + + for (let i = 0; i < anchors.length; i++) { + const anchor = anchors[i]; + const nextAnchorStart = + i + 1 < anchors.length ? anchors[i + 1].start : region.length; + + // Stop body at next anchor OR next h2/h3, whichever comes first. + const afterAnchor = region.slice(anchor.end); + const headingRel = afterAnchor.search(/]*>/i); + const headingAbs = + headingRel === -1 ? region.length : anchor.end + headingRel; + + const bodyEnd = Math.min(nextAnchorStart, headingAbs); + const body = region.slice(anchor.start, bodyEnd); + const content = stripTags(body); + if (content.length < MIN_REDDIT_BODY_LENGTH) continue; + + const { url } = pickPrimary(collectLinks(body)); + stories.push({ + title: anchor.title || "(untitled)", + url: url || anchor.url, + content: content.slice(0, MAX_CONTENT_LENGTH), + }); + } + return stories; +} + +// ---------- fetch ---------- + +async function fetchFeedXml(): Promise { + try { + const res = await fetchWithTimeout(FEED_URL); + if (!res.ok) throw new Error(`Status ${res.status}`); + return await res.text(); + } catch (err) { + log(` AI News fetch FAILED: ${err}`); + return null; + } +} + +function toArticle(story: SubStory, pubDate: string): FetchedArticle { + return { + title: story.title, + url: story.url, + content: story.content, + publishedDate: pubDate, + source: "AI News", + sourceType: "aiNews", + }; +} + +export async function fetchAiNews(): Promise { + log("Fetching AI News feed..."); + + const xml = await fetchFeedXml(); + if (!xml) return []; + + const items = parseFeed(xml).filter((it) => isWithinWindow(it.pubDate)); + log(` AI News: ${items.length} issues within window`); + + const articles: FetchedArticle[] = []; + for (const item of items) { + // Skip low-signal days the editors tag as "not much happened". + if (/^not much happened/i.test(item.title)) continue; + + const twitter = extractTwitterRecap(item.contentHtml); + if (twitter) articles.push(toArticle(twitter, item.pubDate)); + + for (const reddit of extractRedditRecap(item.contentHtml)) { + articles.push(toArticle(reddit, item.pubDate)); + } + } + + // Dedup by URL (same repo/post referenced in multiple issues). + const byUrl = new Map(); + for (const article of articles) { + if (!byUrl.has(article.url)) byUrl.set(article.url, article); + } + const deduped = [...byUrl.values()]; + + log(`AI News: ${deduped.length} articles extracted`); + return deduped; +} diff --git a/temp/source/pipeline/sources/email.ts b/temp/source/pipeline/sources/email.ts new file mode 100644 index 0000000000..8ce0d7a872 --- /dev/null +++ b/temp/source/pipeline/sources/email.ts @@ -0,0 +1,551 @@ +import { mkdir, readdir, readFile, rename } from "node:fs/promises"; +import { join } from "node:path"; +import type { FetchedArticle } from "@shared/types"; +import { ImapFlow } from "imapflow"; +import { simpleParser } from "mailparser"; +import { b } from "../../baml_client"; +import { search } from "../search"; +import { log } from "../utils"; + +// --------------------------------------------------------------------------- +// Types +// --------------------------------------------------------------------------- + +interface NewsletterSource { + sender: string; + name: string; +} + +/** + * A product named by a newsletter, before its canonical URL is resolved. + * Carries the issue metadata so the eventual FetchedArticle keeps attribution. + */ +interface RawProduct { + name: string; + description: string; + emailDate: string; + newsletterName: string; +} + +// --------------------------------------------------------------------------- +// Newsletter sources +// +// No per-provider link resolver: we never decode tracking redirects. The AI +// reads the products a newsletter reports on (from anchor text + prose) and we +// rediscover each canonical URL by web search. The only per-source data is the +// sender→name mapping used for attribution. +// --------------------------------------------------------------------------- + +export const NEWSLETTER_SOURCES: NewsletterSource[] = [ + { + sender: "@deeperlearning.producthunt.com", + name: "The Frontier by Product Hunt", + }, + { sender: "bensbites@substack.com", name: "Ben's Bites" }, + { sender: "@changelog.com", name: "Changelog News" }, + { sender: "@deeplearning.ai", name: "The Batch" }, + { sender: "@tldrnewsletter.com", name: "TLDR" }, + { sender: "@console.dev", name: "Console" }, + { sender: "@pointer.io", name: "Pointer" }, + { sender: "@importai.net", name: "Import AI" }, + { sender: "@theneurondaily.com", name: "The Neuron" }, + { sender: "@aihero.dev", name: "AI Hero" }, + { sender: "@mail.theresanaiforthat.com", name: "There's An AI For That" }, + { sender: "@daily.therundown.ai", name: "The Rundown AI" }, + { sender: "@technews.therundown.ai", name: "The Rundown AI Tech" }, + { sender: "@mail.joinsuperhuman.ai", name: "Superhuman" }, + { sender: "agentai@mail.beehiiv.com", name: "AgentAI" }, +]; + +// --------------------------------------------------------------------------- +// Sender matching +// --------------------------------------------------------------------------- + +function matchSender(address: string): { name: string } | undefined { + const addr = address.toLowerCase(); + for (const source of NEWSLETTER_SOURCES) { + const pattern = source.sender.toLowerCase(); + if (pattern.startsWith("@") ? addr.endsWith(pattern) : addr === pattern) { + return { name: source.name }; + } + } + return undefined; +} + +// --------------------------------------------------------------------------- +// Product extraction (1 AI call per email) +// --------------------------------------------------------------------------- + +// Strip an email's HTML to text, keeping anchor text and surrounding prose. +// Links are kept as [text](href) as a weak hint, but the hrefs are not trusted +// (they are usually tracking redirects); product identity comes from the words. +function htmlToText(html: string): string { + const cleaned = html + .replace(/]*>[\s\S]*?<\/style>/gi, "") + .replace(/]*>[\s\S]*?<\/script>/gi, "") + .replace( + /]*href="([^"]*)"[^>]*>([\s\S]*?)<\/a>/gi, + (_, href, text) => { + const cleanText = text.replace(/<[^>]+>/g, "").trim(); + return cleanText + ? `[${cleanText}](${href.replace(/&/g, "&")})` + : ""; + }, + ) + .replace(/<[^>]+>/g, " ") + .replace(/&/g, "&") + .replace(/ /g, " ") + .replace(/&#\d+;/g, "") + .replace(/\s+/g, " ") + .trim(); + return cleaned.slice(0, 50_000); +} + +async function extractProducts( + html: string, + newsletterName: string, + emailDate: string, +): Promise { + const text = htmlToText(html); + if (!text) return []; + + try { + const products = await b.ExtractProducts(text); + return products + .filter((p) => p.name?.trim()) + .map((p) => ({ + name: p.name.trim(), + description: p.description?.trim() ?? "", + emailDate, + newsletterName, + })); + } catch (err) { + log(` Failed to extract products from ${newsletterName}: ${err}`); + return []; + } +} + +// --------------------------------------------------------------------------- +// URL resolution via search + verify +// --------------------------------------------------------------------------- + +const RESOLVE_CONCURRENCY = 5; +const SEARCH_CANDIDATES = 5; + +// Domains that are never a product's first-party source: social posts, video, +// and aggregators/content farms. Stripped from candidates before the AI picks, +// so a junk hit can't win by default (the model alone didn't reliably reject +// them). A product whose only hit is one of these is dropped rather than linked. +const DENY_DOMAINS = [ + "x.com", + "twitter.com", + "t.co", + "linkedin.com", + "reddit.com", + "threads.net", + "mastodon.social", + "facebook.com", + "instagram.com", + "youtube.com", + "youtu.be", + "digg.com", + "medium.com", + "news.ycombinator.com", +]; + +function isDenied(url: string): boolean { + try { + const host = new URL(url).hostname.replace(/^www\./, "").toLowerCase(); + return DENY_DOMAINS.some((d) => host === d || host.endsWith(`.${d}`)); + } catch { + return true; // unparseable URL is not a usable link + } +} + +/** + * One product → one canonical URL. Searches for candidates and lets the AI pick + * the best first-party result, rejecting social/aggregator/SEO pages and wrong + * products. Returns null when no candidate is clearly the right source. + */ +async function resolveOne(p: RawProduct): Promise { + const query = `${p.name} ${p.description}`.trim(); + + let results: Awaited>; + try { + results = await search(query, { maxResults: SEARCH_CANDIDATES }); + } catch (err) { + log(` Search failed for "${p.name}": ${err}`); + return null; + } + results = results.filter((r) => !isDenied(r.url)); + if (results.length === 0) { + log(` No usable search result for "${p.name}"`); + return null; + } + + let choiceIdx = 0; + try { + const choice = await b.SelectProductLink( + p.name, + p.description, + results.map((r) => ({ + title: r.title, + url: r.url, + snippet: r.description, + })), + ); + choiceIdx = choice.index; + } catch (err) { + log(` Link selection failed for "${p.name}": ${err}`); + return null; + } + + // index is 1-based; 0 means "no candidate is a clean first-party source". + const picked = choiceIdx >= 1 ? results[choiceIdx - 1] : undefined; + if (!picked) { + log(` Dropped "${p.name}": no first-party result among candidates`); + return null; + } + + return { + title: p.name, + url: picked.url, + content: p.description, + publishedDate: p.emailDate, + source: p.newsletterName, + sourceType: "newsletter" as const, + }; +} + +/** + * Dedupe products by name across all issues in this run (one launch is often + * covered by several newsletters the same day), drop the un-notable ones, then + * resolve each survivor to a URL. The dedupe + notability gate are what keep + * search volume within free Tavily quota. + */ +async function resolveProducts(raw: RawProduct[]): Promise { + if (raw.length === 0) return []; + + const byName = new Map(); + for (const p of raw) { + const key = p.name.toLowerCase(); + if (!byName.has(key)) byName.set(key, p); + } + const unique = [...byName.values()]; + + // Notability gate (one batched AI call) before spending any web search. + let products = unique; + try { + const keep = await b.SelectNotableProducts( + unique.map((p) => ({ name: p.name, description: p.description })), + ); + const keepIdx = new Set(keep); + const selected = unique.filter((_, i) => keepIdx.has(i + 1)); + // Guard against a degenerate empty response dropping everything. + if (selected.length > 0) products = selected; + } catch (err) { + log(` Notability filter failed, resolving all: ${err}`); + } + + log( + ` Resolving ${products.length} notable products via search ` + + `(${raw.length} raw → ${unique.length} unique → ${products.length} notable)`, + ); + + const articles: FetchedArticle[] = []; + for (let i = 0; i < products.length; i += RESOLVE_CONCURRENCY) { + const batch = products.slice(i, i + RESOLVE_CONCURRENCY); + const resolved = await Promise.all(batch.map(resolveOne)); + for (const a of resolved) if (a) articles.push(a); + } + log(` Resolved ${articles.length}/${products.length} products to URLs`); + return articles; +} + +// --------------------------------------------------------------------------- +// IMAP config + error handling +// --------------------------------------------------------------------------- + +function getImapConfig() { + const host = process.env.IMAP_HOST; + const port = Number(process.env.IMAP_PORT || 993); + const user = process.env.IMAP_USER; + const pass = process.env.IMAP_PASSWORD; + + if (!host || !user || !pass) { + throw new Error( + "Missing IMAP env vars: IMAP_HOST, IMAP_USER, IMAP_PASSWORD", + ); + } + return { host, port, user, pass }; +} + +// imapflow throws a bare `Error: Command failed` when the server returns NO/BAD, +// stashing the useful detail on these extra fields. Surface them so failures +// are diagnosable instead of a one-line mystery. +interface ImapError extends Error { + responseStatus?: string; + responseText?: string; + executedCommand?: string; + authenticationFailed?: boolean; + code?: string; +} + +/** Flatten an imapflow error into a single diagnostic line. */ +function describeError(err: unknown): string { + const e = err as ImapError; + const parts: string[] = [e?.message ?? String(err)]; + if (e?.responseStatus) parts.push(`status=${e.responseStatus}`); + if (e?.responseText) parts.push(`response=${JSON.stringify(e.responseText)}`); + if (e?.executedCommand) parts.push(`command=${e.executedCommand}`); + if (e?.code) parts.push(`code=${e.code}`); + return parts.join(" "); +} + +/** Auth failures won't recover on retry; NO/BAD/throttle/network might. */ +function isFatal(err: unknown): boolean { + return (err as ImapError)?.authenticationFailed === true; +} + +/** Honor a server-suggested backoff (throttling) else exponential, capped at 30s. */ +function backoffMs(err: unknown, attempt: number): number { + const txt = (err as ImapError)?.responseText; + const m = txt?.match(/Backoff Time[:=\s]+(\d+)/i); + if (m) return Math.min(Number(m[1]), 30_000); + return Math.min(1000 * 2 ** (attempt - 1), 30_000); +} + +function sleep(ms: number): Promise { + return new Promise((resolve) => setTimeout(resolve, ms)); +} + +async function withRetry( + fn: () => Promise, + label: string, + attempts = 3, +): Promise { + let lastErr: unknown; + for (let attempt = 1; attempt <= attempts; attempt++) { + try { + return await fn(); + } catch (err) { + lastErr = err; + if (isFatal(err)) { + log(` ${label} failed (fatal, not retrying): ${describeError(err)}`); + throw err; + } + log( + ` ${label} attempt ${attempt}/${attempts} failed: ${describeError(err)}`, + ); + if (attempt < attempts) { + const delay = backoffMs(err, attempt); + log(` retrying in ${delay}ms...`); + await sleep(delay); + } + } + } + throw lastErr; +} + +// --------------------------------------------------------------------------- +// IMAP fetch +// --------------------------------------------------------------------------- + +/** + * One full connect → fetch → mark-seen → logout cycle, returning the raw + * products named across all unread newsletter emails. Throws on any IMAP error + * so withRetry can decide whether to retry. The socket is closed on failure so + * dead attempts don't pile up against the server's connection limit. + */ +async function runImapFetch( + config: ReturnType, +): Promise { + const client = new ImapFlow({ + host: config.host, + port: config.port, + secure: true, + auth: { user: config.user, pass: config.pass }, + logger: false, + }); + + const raw: RawProduct[] = []; + + try { + await client.connect(); + const lock = await client.getMailboxLock("sub"); + + try { + // 1. Find unread emails from known newsletter senders + const uidMatches = new Map(); + for await (const msg of client.fetch( + { seen: false }, + { envelope: true, uid: true }, + )) { + const fromAddr = msg.envelope?.from?.[0]?.address?.toLowerCase(); + const match = fromAddr ? matchSender(fromAddr) : undefined; + if (match) uidMatches.set(msg.uid, match); + } + + const uids = [...uidMatches.keys()]; + log(` Found ${uids.length} unread newsletter emails`); + + if (uids.length > 0) { + // 2. Download full messages and extract products + const processedUids: number[] = []; + for await (const msg of client.fetch( + { uid: uids.join(",") }, + { envelope: true, source: true, uid: true }, + )) { + const match = uidMatches.get(msg.uid); + if (!match) continue; + + const emailDate = + msg.envelope?.date?.toISOString() ?? new Date().toISOString(); + const subject = msg.envelope?.subject ?? "(no subject)"; + + log(` Processing: ${match.name} (${subject})`); + + if (!msg.source) { + log(` No message source, skipping`); + processedUids.push(msg.uid); + continue; + } + + const parsed = await simpleParser(msg.source as Buffer); + const html = + typeof parsed.html === "string" + ? parsed.html + : (parsed.textAsHtml ?? ""); + if (!html) { + log(` No HTML content, skipping`); + processedUids.push(msg.uid); + continue; + } + + const products = await extractProducts(html, match.name, emailDate); + log(` Found ${products.length} products`); + raw.push(...products); + + processedUids.push(msg.uid); + } + // 3. Mark all processed emails as seen (after fetch stream is done) + if (processedUids.length > 0) { + await client.messageFlagsAdd( + { uid: processedUids.join(",") }, + ["\\Seen"], + { uid: true }, + ); + } + } + } finally { + lock.release(); + } + + await client.logout(); + } catch (err) { + // Close the socket before a retry so failed attempts don't accumulate + // against the server's concurrent-connection limit. + try { + client.close(); + } catch { + /* already closed */ + } + throw err; + } + + return raw; +} + +export async function fetchNewsletter(): Promise { + if (NEWSLETTER_SOURCES.length === 0) { + log("Newsletter: no sources configured, skipping"); + return []; + } + + const config = getImapConfig(); + log(`Connecting to ${config.host} as ${config.user}...`); + + let raw: RawProduct[] = []; + try { + raw = await withRetry(() => runImapFetch(config), "Newsletter IMAP"); + } catch (err) { + log(`Newsletter fetch failed after retries: ${describeError(err)}`); + } + + const articles = await resolveProducts(raw); + log(`Newsletter: ${articles.length} articles extracted`); + return articles; +} + +// --------------------------------------------------------------------------- +// Local .eml import +// --------------------------------------------------------------------------- + +export async function fetchLocalEmails( + dir = "emails", +): Promise { + const files: string[] = []; + try { + const entries = await readdir(dir, { withFileTypes: true }); + for (const entry of entries) { + if (entry.isFile() && entry.name.endsWith(".eml")) { + files.push(join(dir, entry.name)); + } else if (entry.isDirectory() && entry.name !== "processed") { + const subEntries = await readdir(join(dir, entry.name)); + for (const sub of subEntries) { + if (sub.endsWith(".eml")) { + files.push(join(dir, entry.name, sub)); + } + } + } + } + } catch { + log("Local emails: directory not found, skipping"); + return []; + } + + if (files.length === 0) { + log("Local emails: no .eml files found, skipping"); + return []; + } + + log(`Local emails: found ${files.length} .eml files`); + + const raw: RawProduct[] = []; + const processedDir = join(dir, "processed"); + + for (const filePath of files) { + const file = filePath.split("/").pop() ?? filePath; + const rawEml = await readFile(filePath, "utf-8"); + const parsed = await simpleParser(rawEml); + + const fromAddr = parsed.from?.value?.[0]?.address?.toLowerCase() ?? ""; + const match = matchSender(fromAddr); + const newsletterName = match?.name ?? `Unknown (${fromAddr})`; + + const emailDate = parsed.date?.toISOString() ?? new Date().toISOString(); + const subject = parsed.subject ?? "(no subject)"; + + const html = + typeof parsed.html === "string" ? parsed.html : (parsed.textAsHtml ?? ""); + if (!html) { + log(` ${file}: no HTML content, skipping`); + continue; + } + + log( + ` Processing: ${newsletterName} - ${subject} (${emailDate.slice(0, 10)})`, + ); + + const products = await extractProducts(html, newsletterName, emailDate); + log(` Found ${products.length} products`); + raw.push(...products); + + await mkdir(processedDir, { recursive: true }); + await rename(filePath, join(processedDir, file)); + } + + const articles = await resolveProducts(raw); + log(`Local emails: ${articles.length} articles extracted`); + return articles; +} diff --git a/temp/source/pipeline/sources/extract-content.ts b/temp/source/pipeline/sources/extract-content.ts new file mode 100644 index 0000000000..933e3b7a0a --- /dev/null +++ b/temp/source/pipeline/sources/extract-content.ts @@ -0,0 +1,145 @@ +import { Readability } from "@mozilla/readability"; +import { parseHTML } from "linkedom"; +import { log } from "../utils"; +import { fetchWithTimeout } from "./utils"; + +// These domains can't be scraped server-side - they always return error/login pages. +const SKIP_DOMAINS: string[] = ["x.com", "twitter.com"]; +const SNIPPET_MAX_LENGTH = 500; +const EXTRACT_TIMEOUT_MS = 5_000; +const CONCURRENCY = 5; + +function shouldSkip(url: string): boolean { + try { + const host = new URL(url).hostname; + return SKIP_DOMAINS.some((d) => host === d || host.endsWith(`.${d}`)); + } catch { + return true; + } +} + +function ensureBody(html: string): string { + if (/]/i.test(html)) return html; + return `${html}`; +} + +// Phrases that indicate a page blocked us instead of returning real content. +const BLOCKER_PATTERNS: RegExp[] = [ + /something went wrong.*don't fret/i, + /disable.*privacy\s+extensions/i, + /privacy\s+extensions.*and.*retry/i, + /please\s+(?:sign|log)\s*in/i, + /sign\s*in\s+to\s+(?:continue|read|access)/i, + /log\s*in\s+to\s+(?:continue|read|access)/i, + /subscribe\s+to\s+(?:continue|read|access|unlock)/i, + /create\s+an?\s+account\s+to\s+(?:continue|read|access)/i, + /enable\s+javascript\s+to\s+(?:continue|view|use)/i, + /javascript\s+is\s+(?:disabled|required)/i, + /access\s+denied/i, + /403\s+forbidden/i, +]; + +function isBlockerContent(text: string): boolean { + if (text.length < 50) return true; // too short to be real article text + return BLOCKER_PATTERNS.some((re) => re.test(text)); +} + +function extractText(html: string, maxLength?: number): string { + try { + const { document } = parseHTML(ensureBody(html)); + const reader = new Readability(document as unknown as Document); + const article = reader.parse(); + if (article) { + const text = + article.textContent?.replace(/\s+/g, " ").trim() || + article.excerpt || + ""; + if (!text || isBlockerContent(text)) return ""; + return maxLength !== undefined ? text.slice(0, maxLength) : text; + } + } catch { + // fall through + } + return ""; +} + +async function extractHtml(url: string): Promise { + if (shouldSkip(url)) return ""; + + try { + const res = await fetchWithTimeout(url, EXTRACT_TIMEOUT_MS); + if (!res.ok) return ""; + + const contentType = res.headers.get("content-type") ?? ""; + if (!contentType.includes("text/html")) return ""; + + return await res.text(); + } catch { + return ""; + } +} + +async function batchFetch( + urls: string[], + fn: (url: string, idx: number, total: number) => Promise, +): Promise> { + const map = new Map(); + for (let i = 0; i < urls.length; i += CONCURRENCY) { + const batch = urls.slice(i, i + CONCURRENCY); + const results = await Promise.allSettled( + batch.map((url, j) => + fn(url, i + j, urls.length).then((value) => ({ url, value })), + ), + ); + for (const r of results) { + if (r.status === "fulfilled" && r.value.value) { + map.set(r.value.url, r.value.value); + } + } + } + return map; +} + +export async function extractContent< + T extends { url: string; content: string }, +>(articles: T[]): Promise { + const needsContent = articles.filter((a) => !a.content); + if (needsContent.length === 0) return articles; + + const uniqueUrls = [...new Set(needsContent.map((a) => a.url))]; + log(` Extracting content for ${uniqueUrls.length} URLs...`); + + const snippetMap = await batchFetch(uniqueUrls, async (url) => + extractText(await extractHtml(url), SNIPPET_MAX_LENGTH), + ); + + log(` Extracted ${snippetMap.size}/${uniqueUrls.length} snippets`); + + return articles.map((a) => { + const snippet = snippetMap.get(a.url); + return snippet ? { ...a, content: snippet } : a; + }); +} + +export async function reExtractFullContent( + articles: { url: string }[], +): Promise> { + if (articles.length === 0) return new Map(); + + const uniqueUrls = [...new Set(articles.map((a) => a.url))]; + log(` Re-extracting full content for ${uniqueUrls.length} URLs...`); + + const contentMap = await batchFetch(uniqueUrls, async (url, idx, total) => { + log(` [${idx + 1}/${total}] Fetching: ${url}`); + const t0 = Date.now(); + const content = extractText(await extractHtml(url)); + const ms = Date.now() - t0; + log( + ` [${idx + 1}/${total}] ${content ? `OK (${content.length} chars, ${ms}ms)` : `no content (${ms}ms)`}: ${url}`, + ); + return content; + }); + + log(` Re-extracted ${contentMap.size}/${uniqueUrls.length} full texts`); + return contentMap; +} diff --git a/temp/source/pipeline/sources/hn.ts b/temp/source/pipeline/sources/hn.ts new file mode 100644 index 0000000000..0a53f07da5 --- /dev/null +++ b/temp/source/pipeline/sources/hn.ts @@ -0,0 +1,60 @@ +import type { FetchedArticle } from "@shared/types"; +import { log } from "../utils"; +import { extractContent } from "./extract-content"; +import { cleanTitle, fetchWithTimeout, isWithinWindow } from "./utils"; + +const HN_TOP = "https://hacker-news.firebaseio.com/v0/topstories.json"; +const HN_ITEM = "https://hacker-news.firebaseio.com/v0/item"; +const HN_FETCH_LIMIT = 200; + +const HN_AI_KEYWORDS = + /\b(ai|llm|gpt|claude|gemini|llama|openai|anthropic|deepseek|mistral|opencode|tokens|transformer|diffusion|machine.?learning|deep.?learning|neural.?net|language.?model|artificial.?intelligen|stable.?diffusion|midjourney|copilot|chatbot|rag|fine.?tun|embedding|token|lora|rlhf|gguf|ollama|hugging.?face)\b/i; + +interface HNItem { + id: number; + title?: string; + url?: string; + score?: number; + descendants?: number; + time?: number; + type?: string; +} + +export async function fetchHN(): Promise { + log("Fetching Hacker News top stories..."); + const res = await fetchWithTimeout(HN_TOP); + const ids: number[] = (await res.json()) as number[]; + + const topIds = ids.slice(0, HN_FETCH_LIMIT); + const results = await Promise.allSettled( + topIds.map(async (id) => { + const r = await fetchWithTimeout(`${HN_ITEM}/${id}.json`); + return r.json() as Promise; + }), + ); + + const articles: FetchedArticle[] = []; + for (const result of results) { + if (result.status !== "fulfilled") continue; + const item = result.value; + if (!item || item.type !== "story" || !item.title) continue; + if (!HN_AI_KEYWORDS.test(item.title)) continue; + const pubDate = item.time + ? new Date(item.time * 1000).toISOString() + : undefined; + if (!isWithinWindow(pubDate)) continue; + + const cleaned = cleanTitle(item.title); + articles.push({ + title: cleaned, + url: item.url ?? `https://news.ycombinator.com/item?id=${item.id}`, + content: "", + publishedDate: pubDate ?? new Date().toISOString(), + source: "Hacker News", + sourceType: "hackerNews", + }); + } + + log(`Hacker News: ${articles.length} AI-related stories`); + return extractContent(articles); +} diff --git a/temp/source/pipeline/sources/rss.ts b/temp/source/pipeline/sources/rss.ts new file mode 100644 index 0000000000..eae36a86c4 --- /dev/null +++ b/temp/source/pipeline/sources/rss.ts @@ -0,0 +1,103 @@ +import type { FetchedArticle } from "@shared/types"; +import Parser from "rss-parser"; +import { resolveTwitterUrl } from "../search"; +import { log } from "../utils"; +import { cleanTitle, isWithinWindow } from "./utils"; + +const SOURCES = [ + { name: "Aligned News", rssUrl: "https://alignednews.com/feed.xml" }, +]; + +/** Only ingest these RSS categories - others are noise (drama, events, business, etc.). */ +const ALLOWED_CATEGORIES = new Set(["tips", "products"]); + +const TWITTER_HOSTS = new Set(["x.com", "twitter.com", "t.co"]); + +function isTwitterUrl(url: string): boolean { + try { + return TWITTER_HOSTS.has(new URL(url).hostname); + } catch { + return false; + } +} + +type CustomItem = Parser.Item & { categories?: string[]; category?: string }; + +const parser = new Parser, CustomItem>({ + timeout: 15_000, + headers: { "User-Agent": "Agentique/2.0 (+https://agentique.ch)" }, + customFields: { item: [["category", "category"]] }, +}); + +export async function fetchRss(): Promise { + const articles: FetchedArticle[] = []; + + const results = await Promise.allSettled( + SOURCES.map(async (source) => { + log(`Fetching ${source.name}...`); + const feed = await parser.parseURL(source.rssUrl); + + const withinWindow = (feed.items ?? []).filter((item) => + isWithinWindow(item.pubDate ?? item.isoDate), + ); + + // Filter to allowed categories + const relevant = withinWindow.filter((item) => { + const cats: string[] = Array.isArray(item.categories) + ? item.categories + : item.category + ? [item.category as string] + : []; + return cats.some((c) => ALLOWED_CATEGORIES.has(c.toLowerCase())); + }); + + log( + ` ${source.name}: ${withinWindow.length} in window, ${relevant.length} after category filter`, + ); + + // Resolve x.com URLs to real article URLs via Brave Search + const resolved = await Promise.all( + relevant.map(async (item) => { + const rawUrl = item.link ?? ""; + const description = item.contentSnippet ?? item.content ?? ""; + const title = cleanTitle(item.title ?? "(no title)"); + + let url = rawUrl; + if (isTwitterUrl(rawUrl)) { + log(` Resolving tweet: ${title}`); + const found = await resolveTwitterUrl(title, description); + if (found) url = found; + } + + return { + title, + url, + // Use the RSS description as content - it's a quality AI summary, + // far better than what scraping x.com would return. + content: description, + publishedDate: + item.pubDate ?? item.isoDate ?? new Date().toISOString(), + source: source.name, + sourceType: "rss" as const, + }; + }), + ); + + return { source: source.name, items: resolved }; + }), + ); + + for (const result of results) { + if (result.status === "fulfilled") { + log( + ` ${result.value.source}: ${result.value.items.length} articles ready`, + ); + articles.push(...result.value.items); + } else { + log(` FAILED: ${result.reason}`); + } + } + + log(`RSS: ${articles.length} articles`); + return articles; +} diff --git a/temp/source/pipeline/sources/substack-sources.json b/temp/source/pipeline/sources/substack-sources.json new file mode 100644 index 0000000000..c3fd0f6541 --- /dev/null +++ b/temp/source/pipeline/sources/substack-sources.json @@ -0,0 +1,430 @@ +[ + { + "name": "Nate's Substack", + "rssUrl": "https://natesnewsletter.substack.com/feed" + }, + { + "name": "Interconnects AI", + "rssUrl": "https://www.interconnects.ai/feed" + }, + { + "name": "AI Supremacy", + "rssUrl": "https://www.ai-supremacy.com/feed" + }, + { + "name": "The AI Maker", + "rssUrl": "https://aimaker.substack.com/feed" + }, + { + "name": "Understanding AI", + "rssUrl": "https://www.understandingai.org/feed" + }, + { + "name": "AI Tidbits", + "rssUrl": "https://www.aitidbits.ai/feed" + }, + { + "name": "Deep (Learning) Focus", + "rssUrl": "https://cameronrwolfe.substack.com/feed" + }, + { + "name": "AI Newsletter", + "rssUrl": "https://nlp.elvissaravia.com/feed" + }, + { + "name": "Artificial Ignorance", + "rssUrl": "https://www.ignorance.ai/feed" + }, + { + "name": "AI by Hand", + "rssUrl": "https://www.byhand.ai/feed" + }, + { + "name": "Practical AI for Solo Entrepreneurs", + "rssUrl": "https://soloailab.substack.com/feed" + }, + { + "name": "Last Week in AI", + "rssUrl": "https://lastweekin.ai/feed" + }, + { + "name": "The Generative Programmer", + "rssUrl": "https://generativeprogrammer.com/feed" + }, + { + "name": "Designing with AI", + "rssUrl": "https://newsletter.victordibia.com/feed" + }, + { + "name": "Andrej Karpathy", + "rssUrl": "https://karpathy.substack.com/feed" + }, + { + "name": "Ben's Bites", + "rssUrl": "https://www.bensbites.com/feed" + }, + { + "name": "Machine Learning Pills", + "rssUrl": "https://mlpills.substack.com/feed" + }, + { + "name": "Chipstrat", + "rssUrl": "https://www.chipstrat.com/feed" + }, + { + "name": "Making AI Accessible", + "rssUrl": "https://louisbouchard.substack.com/feed" + }, + { + "name": "Redwood Research", + "rssUrl": "https://blog.redwoodresearch.org/feed" + }, + { + "name": "Works on My Machine", + "rssUrl": "https://worksonmymachine.ai/feed" + }, + { + "name": "Hamel's Substack", + "rssUrl": "https://hamelhusain.substack.com/feed" + }, + { + "name": "The AI Engineer", + "rssUrl": "https://newsletter.owainlewis.com/feed" + }, + { + "name": "Trelis Research", + "rssUrl": "https://trelis.substack.com/feed" + }, + { + "name": "Gradient Flow", + "rssUrl": "https://gradientflow.substack.com/feed" + }, + { + "name": "Generally Intelligent", + "rssUrl": "https://generallyintelligent.substack.com/feed" + }, + { + "name": "Building AI Products From Scratch", + "rssUrl": "https://mikikobazeley.substack.com/feed" + }, + { + "name": "LLM Watch", + "rssUrl": "https://www.llmwatch.com/feed" + }, + { + "name": "Loop Engineering", + "rssUrl": "https://linas.substack.com/feed" + }, + { + "name": "Cobus Greyling on LLMs", + "rssUrl": "https://cobusgreyling.substack.com/feed" + }, + { + "name": "Elevate by Addy Osmani", + "rssUrl": "https://addyo.substack.com/feed" + }, + { + "name": "DiamantAI", + "rssUrl": "https://newsletter.diamant-ai.com/feed" + }, + { + "name": "MLWhiz", + "rssUrl": "https://www.mlwhiz.com/feed" + }, + { + "name": "Semantics & Systems", + "rssUrl": "https://khaledea.substack.com/feed" + }, + { + "name": "Token Contributions", + "rssUrl": "https://tokencontributions.substack.com/feed" + }, + { + "name": "Generative History", + "rssUrl": "https://generativehistory.substack.com/feed" + }, + { + "name": "Digital Thoughts", + "rssUrl": "https://thoughts.jock.pl/feed" + }, + { + "name": "Modern Mom Playbook", + "rssUrl": "https://modernmomplaybook.substack.com/feed" + }, + { + "name": "Prompt-Led Product | For PMs Building in the AI Era", + "rssUrl": "https://promptledproduct.substack.com/feed" + }, + { + "name": "AI Weekender", + "rssUrl": "https://aiweekender.substack.com/feed" + }, + { + "name": "Senior Data Science Lead", + "rssUrl": "https://joseparreogarcia.substack.com/feed" + }, + { + "name": "AI Espresso | your tech brew", + "rssUrl": "https://aiespressotechbrew.substack.com/feed" + }, + { + "name": "AI by Aakash", + "rssUrl": "https://www.aibyaakash.com/feed" + }, + { + "name": "Engincan Veske", + "rssUrl": "https://engincanveske.substack.com/feed" + }, + { + "name": "ModelCraft", + "rssUrl": "https://modelcraft.substack.com/feed" + }, + { + "name": "Vik's Newsletter", + "rssUrl": "https://www.viksnewsletter.com/feed" + }, + { + "name": "Standout Systems by Teodora", + "rssUrl": "https://teodoracoach.substack.com/feed" + }, + { + "name": "The Circuit", + "rssUrl": "https://metacircuits.substack.com/feed" + }, + { + "name": "Artificial Enigma", + "rssUrl": "https://idakaukonen.substack.com/feed" + }, + { + "name": "Travis Sparks - Sparkry.AI + Neurodivergence + Business", + "rssUrl": "https://sparkryai.substack.com/feed" + }, + { + "name": "AI Disruption", + "rssUrl": "https://aidisruption.ai/feed" + }, + { + "name": "Cash & Cache", + "rssUrl": "https://cashandcache.substack.com/feed" + }, + { + "name": "Prosper", + "rssUrl": "https://prosperinai.substack.com/feed" + }, + { + "name": "AI Superhero", + "rssUrl": "https://shmulc.substack.com/feed" + }, + { + "name": "AI blew my mind", + "rssUrl": "https://aiblewmymind.substack.com/feed" + }, + { + "name": "ToxSec - AI and Cybersecurity", + "rssUrl": "https://www.toxsec.com/feed" + }, + { + "name": "The Ai Rabbit Hole", + "rssUrl": "https://jtnovelo2131.substack.com/feed" + }, + { + "name": "The Zhang-ularity", + "rssUrl": "https://fzhang.substack.com/feed" + }, + { + "name": "Asymmetric Jump", + "rssUrl": "https://asymmetricjump.substack.com/feed" + }, + { + "name": "Automato: Smarter Work in the Age of AI", + "rssUrl": "https://automato.substack.com/feed" + }, + { + "name": "Empathetic AI Lab", + "rssUrl": "https://aicompanionlab.substack.com/feed" + }, + { + "name": "Leadership in Change", + "rssUrl": "https://leadershipinchange.com/feed" + }, + { + "name": "The FoLD", + "rssUrl": "https://liamdarmody.substack.com/feed" + }, + { + "name": "AI Echoes", + "rssUrl": "https://aiechoes.substack.com/feed" + }, + { + "name": "AI in public", + "rssUrl": "https://humzakhalid.substack.com/feed" + }, + { + "name": "Artificial Code", + "rssUrl": "https://artificialcode.substack.com/feed" + }, + { + "name": "Purposeful AI", + "rssUrl": "https://purposefulai.substack.com/feed" + }, + { + "name": "Shrivu's Substack", + "rssUrl": "https://blog.sshh.io/feed" + }, + { + "name": "The AI Architect", + "rssUrl": "https://mvidmar.substack.com/feed" + }, + { + "name": "The Humans in the Loop", + "rssUrl": "https://www.thehumansintheloop.ai/feed" + }, + { + "name": "AI Enhanced Engineer", + "rssUrl": "https://aienhancedengineer.substack.com/feed" + }, + { + "name": "Product with Attitude", + "rssUrl": "https://karozieminski.substack.com/feed" + }, + { + "name": "And Yet It Moves", + "rssUrl": "https://andyetitmoves.substack.com/feed" + }, + { + "name": "Department of Product", + "rssUrl": "https://departmentofproduct.substack.com/feed" + }, + { + "name": "Design with AI", + "rssUrl": "https://designwithai.substack.com/feed" + }, + { + "name": "Limited Edition Jonathan", + "rssUrl": "https://limitededitionjonathan.substack.com/feed" + }, + { + "name": "Product Growth", + "rssUrl": "https://www.news.aakashg.com/feed" + }, + { + "name": "The Outer Loop", + "rssUrl": "https://theouterloop.substack.com/feed" + }, + { + "name": "Co-Write with AI", + "rssUrl": "https://articles.cowritewithai.com/feed" + }, + { + "name": "Exploring ChatGPT", + "rssUrl": "https://exploringchatgpt.substack.com/feed" + }, + { + "name": "Hello AI World", + "rssUrl": "https://malihaarshad1.substack.com/feed" + }, + { + "name": "Savvy Sloth", + "rssUrl": "https://savvysloth.substack.com/feed" + }, + { + "name": "Turing Post", + "rssUrl": "https://turingpost.substack.com/feed" + }, + { + "name": "Marily’s AI Product Academy Newsletter", + "rssUrl": "https://marily.substack.com/feed" + }, + { + "name": "ByteByteGo Newsletter", + "rssUrl": "https://blog.bytebytego.com/feed" + }, + { + "name": "The Tech Buffet", + "rssUrl": "https://thetechbuffet.substack.com/feed" + }, + { + "name": "SwirlAI Newsletter", + "rssUrl": "https://www.newsletter.swirlai.com/feed" + }, + { + "name": "Simon Willison’s Newsletter", + "rssUrl": "https://simonw.substack.com/feed" + }, + { + "name": "Ahead of AI", + "rssUrl": "https://magazine.sebastianraschka.com/feed" + }, + { + "name": "The Pipe & The Line", + "rssUrl": "https://thepipeandtheline.substack.com/feed" + }, + { + "name": "Coding with Intelligence", + "rssUrl": "https://codingwithintelligence.com/feed" + }, + { + "name": "AI for Software Engineers", + "rssUrl": "https://www.aiforswes.com/feed" + }, + { + "name": "Thonk From First Principles", + "rssUrl": "https://www.thonking.ai/feed" + }, + { + "name": "The Kaitchup – AI on a Budget", + "rssUrl": "https://kaitchup.substack.com/feed" + }, + { + "name": "ThursdAI - Highest signal weekly AI news show", + "rssUrl": "https://sub.thursdai.news/feed" + }, + { + "name": "The AI Break", + "rssUrl": "https://theaibreak.substack.com/feed" + }, + { + "name": "Artificial Corner", + "rssUrl": "https://artificialcorner.com/feed" + }, + { + "name": "The Ontologist", + "rssUrl": "https://ontologist.substack.com/feed" + }, + { + "name": "The Technical Executive", + "rssUrl": "https://sderosiaux.substack.com/feed" + }, + { + "name": "AI Health Uncut", + "rssUrl": "https://www.fixhealth.ai/feed" + }, + { + "name": "Exploring Artificial Intelligence", + "rssUrl": "https://exploringartificialintelligence.substack.com/feed" + }, + { + "name": "All Agents Considered", + "rssUrl": "https://allagentsconsidered.substack.com/feed" + }, + { + "name": "ai.tism", + "rssUrl": "https://aitism.substack.com/feed" + }, + { + "name": "Practical AI Brief", + "rssUrl": "https://practicalaibrief.substack.com/feed" + }, + { + "name": "Matt Paige", + "rssUrl": "https://mattpaige68.substack.com/feed" + }, + { + "name": "Artificial Intelligence Learning 🤖🧠🦾", + "rssUrl": "https://offthegridxp.substack.com/feed" + }, + { + "name": "Machine Learning At Scale", + "rssUrl": "https://machinelearningatscale.substack.com/feed" + } +] diff --git a/temp/source/pipeline/sources/substack.ts b/temp/source/pipeline/sources/substack.ts new file mode 100644 index 0000000000..8cbabb58c8 --- /dev/null +++ b/temp/source/pipeline/sources/substack.ts @@ -0,0 +1,137 @@ +import type { FetchedArticle } from "@shared/types"; +import Parser from "rss-parser"; +import { ProxyAgent, fetch as undiciFetch } from "undici"; +import { log } from "../utils"; +import SOURCES from "./substack-sources.json"; +import { cleanTitle, isWithinWindow } from "./utils"; + +const proxyUrl = process.env.RESIDENTIAL_PROXY_URL; +const dispatcher = proxyUrl ? new ProxyAgent(proxyUrl) : undefined; + +// One-time, credential-redacted log so CI confirms what proxy (if any) is wired. +if (proxyUrl) { + try { + const u = new URL(proxyUrl); + log( + `Substack proxy: ${u.protocol}//${u.hostname}:${u.port || "(default)"} (auth: ${u.username ? "yes" : "no"})`, + ); + } catch { + log(`Substack proxy: set but unparseable as URL (len ${proxyUrl.length})`); + } +} else { + log(`Substack proxy: none (RESIDENTIAL_PROXY_URL unset)`); +} + +// Recursively unwraps Error.cause so a bare undici "fetch failed" reveals the +// real reason (ENOTFOUND, ECONNREFUSED, SOCKS, TLS, proxy 407, etc.). +function describeError(err: unknown, depth = 0): string { + const e = err as { + name?: string; + code?: string; + message?: string; + cause?: unknown; + }; + if (!e) return String(err); + const code = e.code !== undefined ? `(${e.code})` : ""; + const head = `${e.name ?? "Error"}${code}: ${e.message ?? e}`; + if (e.cause && depth < 4) + return `${head} <- ${describeError(e.cause, depth + 1)}`; + return head; +} + +const BROWSER_HEADERS = { + "User-Agent": + "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/124.0.0.0 Safari/537.36", + Accept: "text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8", + "Accept-Language": "en-US,en;q=0.9", +}; + +// rss-parser fetches via Node's native https.get and ignores any custom +// transport, so it can never route through our residential proxy. Substack's +// native *.substack.com feeds sit behind Cloudflare and 403 datacenter IPs +// (e.g. CI runners), so we fetch the XML ourselves and hand the string to +// parser.parseString. +// +// Strategy: try a direct request first - this works for custom-domain feeds +// and from clean IPs, and keeps us off the proxy when we don't need it. Only +// when Cloudflare blocks us (403/429) do we retry through the residential +// proxy. Failures surface the underlying cause (undici wraps everything in a +// bare "fetch failed") so CI logs are diagnosable. +async function fetchOnce(url: string, useProxy: boolean) { + try { + return await undiciFetch(url, { + headers: BROWSER_HEADERS, + ...(useProxy && dispatcher ? { dispatcher } : {}), + }); + } catch (err) { + throw new Error( + `fetch failed${useProxy ? " (via proxy)" : ""}: ${describeError(err)}`, + ); + } +} + +async function fetchFeedXml( + url: string, + retries = 2, + backoff = 2000, +): Promise { + for (let attempt = 0; ; attempt++) { + // attempt 0 is direct; subsequent attempts route through the proxy if set + const useProxy = attempt > 0 && !!dispatcher; + const res = await fetchOnce(url, useProxy); + if (res.ok) return res.text(); + if ( + (res.status === 403 || res.status === 429) && + attempt < retries && + dispatcher + ) { + await new Promise((r) => setTimeout(r, backoff * 2 ** attempt)); + continue; + } + throw new Error(`Status code ${res.status}`); + } +} + +const parser = new Parser({ timeout: 15_000 }); + +export async function fetchSubstack(): Promise { + const articles: FetchedArticle[] = []; + + const results = await Promise.all( + SOURCES.map(async (source) => { + log(`Fetching ${source.name}...`); + try { + const xml = await fetchFeedXml(source.rssUrl); + const feed = await parser.parseString(xml); + + const withinWindow = (feed.items ?? []).filter((item) => + isWithinWindow(item.pubDate ?? item.isoDate), + ); + + log(` ${source.name}: ${withinWindow.length} in window`); + + const items = withinWindow.map((item) => ({ + title: cleanTitle(item.title ?? "(no title)"), + url: item.link ?? "", + content: item.contentSnippet ?? item.content ?? "", + publishedDate: + item.pubDate ?? item.isoDate ?? new Date().toISOString(), + source: source.name, + sourceType: "rss" as const, + })); + + return items; + } catch (err) { + log(` FAILED ${source.name}: ${(err as Error).message}`); + return [] as FetchedArticle[]; + } + }), + ); + + for (const items of results) { + articles.push(...items); + } + + log(`Substack: ${articles.length} articles`); + return articles; +} diff --git a/temp/source/pipeline/sources/utils.ts b/temp/source/pipeline/sources/utils.ts new file mode 100644 index 0000000000..3b17a64e25 --- /dev/null +++ b/temp/source/pipeline/sources/utils.ts @@ -0,0 +1,38 @@ +// Source-layer helpers shared between hn, rss, email, and extract-content. + +const HN_PREFIX_RE = /^(?:Show|Launch|Ask|Tell) HN:\s*/i; + +// Strip "Show HN:" / "Ask HN:" style prefixes from story titles. +export function cleanTitle(title: string): string { + return title.replace(HN_PREFIX_RE, "").trim(); +} + +const FETCH_TIMEOUT_MS = 15_000; + +export async function fetchWithTimeout( + url: string, + timeoutMs = FETCH_TIMEOUT_MS, +): Promise { + const controller = new AbortController(); + const timer = setTimeout(() => controller.abort(), timeoutMs); + try { + return await fetch(url, { signal: controller.signal }); + } finally { + clearTimeout(timer); + } +} + +const WINDOW_HOURS = 168; + +// True if `dateStr` is within the last N hours (default 1 week). +// Missing/unparseable dates are treated as "within" (pass-through). +export function isWithinWindow( + dateStr: string | undefined, + windowHours: number = WINDOW_HOURS, +): boolean { + if (!dateStr) return true; + const published = new Date(dateStr); + const now = new Date(); + const hoursAgo = (now.getTime() - published.getTime()) / (1000 * 60 * 60); + return hoursAgo <= windowHours; +} diff --git a/temp/source/pipeline/steps.ts b/temp/source/pipeline/steps.ts new file mode 100644 index 0000000000..52e8b2c95b --- /dev/null +++ b/temp/source/pipeline/steps.ts @@ -0,0 +1,88 @@ +// Shared helpers used across pipeline steps. +// +// - trustBySource: maps source name -> "high" | "medium" | "low" +// - toArticleInputs: builds ArticleInput[] from FetchedArticle[] for BAML calls + +import type { ArticleKind, FetchedArticle } from "@shared/types"; +import type { ArticleInput } from "../baml_client/types"; +import { NEWSLETTER_SOURCES } from "./sources/email"; + +// Minimum ScoreArticles score (1-100) an article must reach to be kept. +// Shared by the pipeline (run.ts) and the feed-discovery gate (sources/discover) +// so a feed is only added when its recent items would survive the same bar. +export const SCORE_THRESHOLD = 76; + +// Source trust is used as a signal in the scoring prompt: high-trust sources +// get a +1 bonus when content quality is comparable. Newsletter sources are +// curated by humans, so they all count as high trust. +export const trustBySource: Record = { + "Hacker News": "high", + "AI News": "high", +}; +for (const ns of NEWSLETTER_SOURCES) { + trustBySource[ns.name] = "high"; +} + +/** + * Detects a GitHub repo link inside fetched article content. + * Matches github.com/owner/repo paths; ignores non-repo pages like + * github.com/features or github.com/login. + * Returns the matched URL, or null if none found. + */ +export function githubRepoFromContent(content: string): string | null { + const match = content.match( + /https?:\/\/(?:www\.)?github\.com\/([A-Za-z0-9_.-]+)\/([A-Za-z0-9_.-]+)/, + ); + if (!match) return null; + const [, owner, repo] = match; + // Filter out GitHub meta-pages that aren't repos + const nonRepoOwners = new Set([ + "features", + "login", + "pricing", + "about", + "marketplace", + "explore", + "topics", + "collections", + "trending", + "sponsors", + "orgs", + "apps", + "contact", + "security", + ]); + if (nonRepoOwners.has(owner.toLowerCase())) return null; + return `https://github.com/${owner}/${repo}`; +} + +/** + * URL-based kind detection - overrides LLM classification for unambiguous cases. + * Returns null when the URL gives no signal (LLM should decide). + */ +export function kindFromUrl(url: string): ArticleKind | null { + try { + const host = new URL(url).hostname.replace(/^www\./, ""); + if (host === "github.com" || host === "gitlab.com") return "repo"; + if (host === "huggingface.co" || host === "hf.co") return "model"; + if (host === "arxiv.org" || host === "ar5iv.labs.arxiv.org") return "paper"; + } catch { + // malformed URL - fall through + } + return null; +} + +// Converts FetchedArticles to ArticleInput for BAML scoring/dedup/title calls. +// Snippets are capped at 200 chars - enough signal for the LLM without +// paying the cost of the full content we captured during fetch. +export function toArticleInputs(articles: FetchedArticle[]): ArticleInput[] { + return articles.map( + (a): ArticleInput => ({ + url: a.url, + title: a.title, + source: a.source, + snippet: a.content ? a.content.slice(0, 200) : undefined, + trust: trustBySource[a.source], + }), + ); +} diff --git a/temp/source/pipeline/utils.ts b/temp/source/pipeline/utils.ts new file mode 100644 index 0000000000..dea4eba8e4 --- /dev/null +++ b/temp/source/pipeline/utils.ts @@ -0,0 +1,59 @@ +// Genuinely cross-cutting helpers - used from both the web app side +// (app/api/*) and the pipeline/sources/scripts side. +// +// Source-layer helpers (cleanTitle, fetchWithTimeout, isWithinWindow) live +// in src/sources/utils.ts. + +const TIMEZONE = "Europe/Zurich"; + +export function todayDateString(): string { + return new Date().toLocaleDateString("sv-SE", { timeZone: TIMEZONE }); +} + +export const wait = (ms: number) => new Promise((r) => setTimeout(r, ms)); + +export function log(message: string): void { + const ts = new Date().toISOString(); + console.log(`[${ts}] ${message}`); +} + +// Strip wrapper artifacts the LLM sometimes echoes around an improved title: +// a leading "[Source]" tag and surrounding straight or smart quotes. +// Returns the bare title text. +export function stripTitleWrappers(text: string): string { + let s = text.trim(); + s = s.replace(/^\[[^\]]+\]\s*/, ""); + s = s.replace(/^\d+\.\s*/, ""); + const pairs: [string, string][] = [ + ['"', '"'], + ["'", "'"], + ["“", "”"], + ["‘", "’"], + ]; + for (const [open, close] of pairs) { + if (s.startsWith(open) && s.endsWith(close) && s.length >= 2) { + s = s.slice(open.length, s.length - close.length).trim(); + break; + } + } + return s; +} + +// Strip smart quotes, emoji, and other unicode junk LLMs like to emit. +export function sanitizeLlmText(text: string): string { + return text + .replace(/[\u2018\u2019\u201A]/g, "'") + .replace(/[\u201C\u201D\u201E]/g, '"') + .replace(/\u2192/g, "->") + .replace(/\u2190/g, "<-") + .replace(/\u2194/g, "<->") + .replace(/[\u2013\u2014]/g, "-") + .replace(/\u2026/g, "...") + .replace(/[\u2022\u2023\u25E6\u25AA\u25AB]/g, "-") + .replace( + /[\p{Emoji_Presentation}\p{Extended_Pictographic}]\uFE0F?(\u200D[\p{Emoji_Presentation}\p{Extended_Pictographic}]\uFE0F?)*/gu, + "", + ) + .replace(/ {2,}/g, " ") + .trim(); +} diff --git a/temp/source/shared/db/articles.ts b/temp/source/shared/db/articles.ts new file mode 100644 index 0000000000..499a6e0675 --- /dev/null +++ b/temp/source/shared/db/articles.ts @@ -0,0 +1,370 @@ +import { + and, + asc, + desc, + eq, + gte, + inArray, + isNotNull, + isNull, + like, + or, + sql, +} from "drizzle-orm"; +import * as schema from "../schema"; +import type { DbArticle, FetchedArticle } from "../types"; +import { db } from "./client"; + +function normalizeDate(dateStr: string | undefined): string | null { + if (!dateStr) return null; + try { + return new Date(dateStr).toISOString(); + } catch { + return dateStr; + } +} + +function daysAgoIso(days: number): string { + return new Date(Date.now() - days * 24 * 60 * 60 * 1000).toISOString(); +} + +export async function getRecentArticles( + days: number, +): Promise<(DbArticle & { url: string })[]> { + const rows = await db() + .select() + .from(schema.articles) + .where(gte(schema.articles.published_at, daysAgoIso(days))) + .orderBy(desc(schema.articles.published_at)); + return rows as unknown as (DbArticle & { url: string })[]; +} + +export async function insertArticle(article: FetchedArticle): Promise { + const result = await db() + .insert(schema.articles) + .values({ + title: article.title, + content: article.content, + source: article.source, + source_type: article.sourceType, + published_at: normalizeDate(article.publishedDate), + url: article.url, + }) + .returning({ id: schema.articles.id }); + const articleId = result[0].id; + await db() + .insert(schema.articleUrls) + .values({ url: article.url, article_id: articleId }); + return articleId; +} + +export async function updateScore( + articleId: number, + score: number, +): Promise { + await db() + .update(schema.articles) + .set({ score }) + .where(eq(schema.articles.id, articleId)); +} + +export async function updateCategories( + articleId: number, + summary: string, + categories: string[], +): Promise { + await db() + .update(schema.articles) + .set({ summary, categories: JSON.stringify(categories) }) + .where(eq(schema.articles.id, articleId)); +} + +export async function updateKind( + articleId: number, + kind: string, +): Promise { + await db() + .update(schema.articles) + .set({ kind }) + .where(eq(schema.articles.id, articleId)); +} + +export async function updateContent( + articleId: number, + content: string, +): Promise { + await db() + .update(schema.articles) + .set({ content }) + .where(eq(schema.articles.id, articleId)); +} + +export async function updateTitle( + articleId: number, + title: string, +): Promise { + await db() + .update(schema.articles) + .set({ title }) + .where(eq(schema.articles.id, articleId)); +} + +export async function updateSummary( + articleId: number, + summary: string, +): Promise { + await db() + .update(schema.articles) + .set({ summary }) + .where(eq(schema.articles.id, articleId)); +} + +export interface ArticleFilterParams { + q?: string; + category?: string; + kind?: string; + since?: string; + sort?: string; + includeReleased?: boolean; + minScore?: number; + limit?: number; +} + +const SORT_COLUMNS = new Set(["score", "published_at", "title", "source"]); + +export async function getFilteredArticles( + params: ArticleFilterParams, +): Promise<(Omit & { url: string })[]> { + const a = schema.articles; + const conditions = [isNotNull(a.score)]; + + if (!params.includeReleased) conditions.push(isNull(a.release_date)); + if (params.since) conditions.push(gte(a.published_at, params.since)); + if (params.minScore !== undefined) + conditions.push(gte(a.score, params.minScore)); + if (params.kind) conditions.push(eq(a.kind, params.kind)); + if (params.q) { + const pattern = `%${params.q}%`; + conditions.push( + or(like(a.title, pattern), like(a.summary, pattern)) as ReturnType< + typeof eq + >, + ); + } + if (params.category) { + conditions.push( + sql`EXISTS (SELECT 1 FROM json_each(${a.categories}) WHERE json_each.value = ${params.category})` as ReturnType< + typeof eq + >, + ); + } + + let orderExpr = desc(a.score); + if (params.sort) { + const parts = params.sort.split("-"); + const dir = parts.pop(); + const col = parts.join("-"); + if (SORT_COLUMNS.has(col) && (dir === "asc" || dir === "desc")) { + const colRef = a[col as keyof typeof a] as Parameters[0]; + orderExpr = dir === "asc" ? asc(colRef) : desc(colRef); + } + } + + const q = db() + .select({ + id: a.id, + title: a.title, + source: a.source, + source_type: a.source_type, + published_at: a.published_at, + score: a.score, + summary: a.summary, + categories: a.categories, + release_date: a.release_date, + created_at: a.created_at, + kind: a.kind, + human_edits: a.human_edits, + url: a.url, + }) + .from(a) + .where(and(...conditions)) + .orderBy(orderExpr); + + const rows = params.limit ? await q.limit(params.limit) : await q; + return rows as unknown as (Omit & { url: string })[]; +} + +export async function getUnreleasedArticles(): Promise< + (DbArticle & { url: string })[] +> { + const rows = await db() + .select() + .from(schema.articles) + .where( + and( + isNull(schema.articles.release_date), + isNotNull(schema.articles.score), + ), + ) + .orderBy(desc(schema.articles.score), desc(schema.articles.created_at)); + return rows as unknown as (DbArticle & { url: string })[]; +} + +export async function getAllArticles( + includeReleased: boolean, +): Promise<(DbArticle & { url: string })[]> { + if (includeReleased) { + const rows = await db() + .select() + .from(schema.articles) + .where(isNotNull(schema.articles.score)) + .orderBy(desc(schema.articles.created_at)); + return rows as unknown as (DbArticle & { url: string })[]; + } + return getUnreleasedArticles(); +} + +export async function getArticlesByIds( + ids: number[], +): Promise<(DbArticle & { url: string })[]> { + if (ids.length === 0) return []; + const rows = await db() + .select() + .from(schema.articles) + .where(inArray(schema.articles.id, ids)) + .orderBy(desc(schema.articles.created_at)); + return rows as unknown as (DbArticle & { url: string })[]; +} + +export async function getArticleById( + id: number, +): Promise<{ id: number; title: string; summary: string | null } | null> { + const rows = await db() + .select({ + id: schema.articles.id, + title: schema.articles.title, + summary: schema.articles.summary, + }) + .from(schema.articles) + .where(eq(schema.articles.id, id)) + .limit(1); + return rows[0] ?? null; +} + +export async function releaseArticles( + ids: number[], + date: string, +): Promise { + await db() + .update(schema.articles) + .set({ release_date: date }) + .where(inArray(schema.articles.id, ids)); +} + +export interface ArticleUpdate { + title?: string; + score?: number | null; + summary?: string | null; + categories?: string[]; + kind?: string | null; + source?: string; + published_at?: string | null; + addHumanEdits?: string[]; +} + +export async function updateArticle( + articleId: number, + fields: ArticleUpdate, +): Promise { + const set: Partial = {}; + + if (fields.title !== undefined) set.title = fields.title; + if (fields.score !== undefined) set.score = fields.score; + if (fields.summary !== undefined) set.summary = fields.summary; + if (fields.categories !== undefined) + set.categories = JSON.stringify(fields.categories); + if (fields.kind !== undefined) set.kind = fields.kind; + if (fields.source !== undefined) set.source = fields.source; + if (fields.published_at !== undefined) set.published_at = fields.published_at; + + if (fields.addHumanEdits?.length) { + const rows = await db() + .select({ human_edits: schema.articles.human_edits }) + .from(schema.articles) + .where(eq(schema.articles.id, articleId)) + .limit(1); + const current = rows[0]?.human_edits ?? "[]"; + set.human_edits = JSON.stringify([ + ...new Set([ + ...(JSON.parse(current) as string[]), + ...fields.addHumanEdits, + ]), + ]); + } + + if (Object.keys(set).length === 0) return; + await db() + .update(schema.articles) + .set(set) + .where(eq(schema.articles.id, articleId)); +} + +export async function deleteArticle(articleId: number): Promise { + await db() + .delete(schema.articleUrls) + .where(eq(schema.articleUrls.article_id, articleId)); + await db().delete(schema.articles).where(eq(schema.articles.id, articleId)); +} + +export async function updateEmbedding( + articleId: number, + vecString: string, +): Promise { + // vector32() is a Turso-specific function — kept as raw SQL + await db().run( + sql`UPDATE articles SET embedding = vector32(${vecString}) WHERE id = ${articleId}`, + ); +} + +export async function searchArticlesByEmbedding( + queryVecString: string, + limit = 20, +): Promise<(DbArticle & { url: string })[]> { + // vector_top_k is a Turso-specific table-valued function — kept as raw SQL + const rows = await db().all( + sql`SELECT a.* + FROM articles a + INNER JOIN (SELECT rowid FROM vector_top_k('idx_articles_embedding', ${queryVecString}, ${limit})) v ON a.id = v.rowid + WHERE a.score IS NOT NULL`, + ); + return rows; +} + +export async function getArticlesWithoutEmbeddings(): Promise< + { id: number; title: string; summary: string | null }[] +> { + return db() + .select({ + id: schema.articles.id, + title: schema.articles.title, + summary: schema.articles.summary, + }) + .from(schema.articles) + .where( + and( + isNotNull(schema.articles.score), + isNotNull(schema.articles.summary), + isNull(schema.articles.embedding), + ), + ); +} + +export async function getArticleStats(): Promise<{ + total: number; + lastUpdated: string | null; +}> { + const rows = await db().all<{ total: number; last: string | null }>( + sql`SELECT COUNT(*) as total, MAX(created_at) as last FROM articles WHERE score IS NOT NULL`, + ); + return { total: rows[0]?.total ?? 0, lastUpdated: rows[0]?.last ?? null }; +} diff --git a/temp/source/shared/db/client.ts b/temp/source/shared/db/client.ts new file mode 100644 index 0000000000..15890d1358 --- /dev/null +++ b/temp/source/shared/db/client.ts @@ -0,0 +1,44 @@ +import { createClient } from "@libsql/client/web"; +import { drizzle } from "drizzle-orm/libsql"; +import * as schema from "../schema"; + +export type DrizzleClient = ReturnType; + +let _db: DrizzleClient | null = null; + +export function initDb(env: { + TURSO_DATABASE_URL: string; + TURSO_AUTH_TOKEN?: string; +}) { + if (!_db) { + _db = drizzle( + createClient({ + url: env.TURSO_DATABASE_URL, + authToken: env.TURSO_AUTH_TOKEN, + }), + { schema }, + ); + } +} + +export function db(): DrizzleClient { + if (!_db) { + const env = + typeof process !== "undefined" + ? (process as { env?: Record }).env + : {}; + _db = drizzle( + createClient({ + url: env?.TURSO_DATABASE_URL ?? "", + authToken: env?.TURSO_AUTH_TOKEN, + }), + { schema }, + ); + } + return _db; +} + +export async function ping(): Promise { + const { sql } = await import("drizzle-orm"); + await db().run(sql`SELECT 1`); +} diff --git a/temp/source/shared/db/meta.ts b/temp/source/shared/db/meta.ts new file mode 100644 index 0000000000..1a39f6cd8d --- /dev/null +++ b/temp/source/shared/db/meta.ts @@ -0,0 +1,36 @@ +import { eq, like, sql } from "drizzle-orm"; +import * as schema from "../schema"; +import { db } from "./client"; + +export async function setMeta(key: string, value: string): Promise { + await db() + .insert(schema.meta) + .values({ key, value }) + .onConflictDoUpdate({ + target: schema.meta.key, + set: { value, updated_at: sql`(datetime('now'))` }, + }); +} + +export async function getMeta(key: string): Promise { + const rows = await db() + .select({ value: schema.meta.value }) + .from(schema.meta) + .where(eq(schema.meta.key, key)) + .limit(1); + return rows[0]?.value ?? null; +} + +export async function getMetaByPrefix( + prefix: string, +): Promise> { + const rows = await db() + .select({ key: schema.meta.key, value: schema.meta.value }) + .from(schema.meta) + .where(like(schema.meta.key, `${prefix}%`)); + const result: Record = {}; + for (const row of rows) { + result[row.key.slice(prefix.length)] = row.value; + } + return result; +} diff --git a/temp/source/shared/db/urls.ts b/temp/source/shared/db/urls.ts new file mode 100644 index 0000000000..1c16ed68e5 --- /dev/null +++ b/temp/source/shared/db/urls.ts @@ -0,0 +1,71 @@ +import { eq, inArray } from "drizzle-orm"; +import * as schema from "../schema"; +import { db } from "./client"; + +export async function urlExists(url: string): Promise { + const rows = await db() + .select({ url: schema.articleUrls.url }) + .from(schema.articleUrls) + .where(eq(schema.articleUrls.url, url)) + .limit(1); + return rows.length > 0; +} + +export async function urlsExist(urls: string[]): Promise> { + if (urls.length === 0) return new Set(); + const rows = await db() + .select({ url: schema.articleUrls.url }) + .from(schema.articleUrls) + .where(inArray(schema.articleUrls.url, urls)); + return new Set(rows.map((r) => r.url)); +} + +export async function scoredUrlsExist(urls: string[]): Promise> { + if (urls.length === 0) return new Set(); + const rows = await db() + .select({ url: schema.scoredUrls.url }) + .from(schema.scoredUrls) + .where(inArray(schema.scoredUrls.url, urls)); + return new Set(rows.map((r) => r.url)); +} + +export async function markUrlsScored(urls: string[]): Promise { + if (urls.length === 0) return; + await db() + .insert(schema.scoredUrls) + .values(urls.map((url) => ({ url }))) + .onConflictDoNothing(); +} + +export async function getArticleIdByUrl(url: string): Promise { + const rows = await db() + .select({ article_id: schema.articleUrls.article_id }) + .from(schema.articleUrls) + .where(eq(schema.articleUrls.url, url)) + .limit(1); + return rows[0]?.article_id ?? null; +} + +export async function addUrlToArticle( + url: string, + articleId: number, +): Promise { + await db() + .insert(schema.articleUrls) + .values({ url, article_id: articleId }) + .onConflictDoNothing(); +} + +export async function updateArticleUrl( + articleId: number, + newUrl: string, +): Promise { + await db() + .update(schema.articleUrls) + .set({ url: newUrl }) + .where(eq(schema.articleUrls.article_id, articleId)); + await db() + .update(schema.articles) + .set({ url: newUrl }) + .where(eq(schema.articles.id, articleId)); +} diff --git a/temp/source/shared/db/users.ts b/temp/source/shared/db/users.ts new file mode 100644 index 0000000000..6eb9fae804 --- /dev/null +++ b/temp/source/shared/db/users.ts @@ -0,0 +1,182 @@ +import { and, eq, gte, sql } from "drizzle-orm"; +import * as schema from "../schema"; +import { db } from "./client"; + +export async function getUserByEmail(email: string): Promise<{ + id: number; + key_hash: string | null; + credits_remaining: number; + github_username: string | null; +} | null> { + const rows = await db() + .select({ + id: schema.users.id, + key_hash: schema.users.key_hash, + credits_remaining: schema.users.credits_remaining, + github_username: schema.users.github_username, + }) + .from(schema.users) + .where(eq(schema.users.email, email)) + .limit(1); + if (rows.length === 0) return null; + const r = rows[0]; + return { + id: r.id, + key_hash: r.key_hash, + credits_remaining: r.credits_remaining ?? 0, + github_username: r.github_username ?? null, + }; +} + +export async function ensureUserByEmail(email: string): Promise<{ + id: number; + key_hash: string | null; + credits_remaining: number; + github_username: string | null; +}> { + await db().insert(schema.users).values({ email }).onConflictDoNothing(); + const u = await getUserByEmail(email); + if (!u) throw new Error(`Failed to upsert user ${email}`); + return u; +} + +export async function upsertNewsletterPrefs(params: { + email: string; + categories: string[]; + custom: string; + utm_source?: string | null; +}): Promise { + await db() + .insert(schema.users) + .values({ + email: params.email, + newsletter_categories: JSON.stringify(params.categories), + newsletter_custom: params.custom, + newsletter_utm_source: params.utm_source ?? null, + newsletter_updated_at: sql`(datetime('now'))`, + }) + .onConflictDoUpdate({ + target: schema.users.email, + set: { + newsletter_categories: JSON.stringify(params.categories), + newsletter_custom: params.custom, + newsletter_utm_source: params.utm_source ?? null, + newsletter_updated_at: sql`(datetime('now'))`, + }, + }); +} + +export async function creditUser(params: { + email: string; + name?: string | null; + credits: number; +}): Promise { + await db() + .insert(schema.users) + .values({ + email: params.email, + name: params.name ?? null, + credits_remaining: params.credits, + }) + .onConflictDoUpdate({ + target: schema.users.email, + set: { + credits_remaining: sql`${schema.users.credits_remaining} + ${params.credits}`, + name: sql`COALESCE(${schema.users.name}, ${params.name ?? null})`, + }, + }); +} + +export async function setUserKeyHash( + userId: number, + keyHash: string, +): Promise { + await db() + .update(schema.users) + .set({ key_hash: keyHash }) + .where(eq(schema.users.id, userId)); +} + +export async function verifyKey( + keyHash: string, +): Promise<{ userId: number; balance: number } | null> { + const rows = await db() + .select({ + id: schema.users.id, + credits_remaining: schema.users.credits_remaining, + }) + .from(schema.users) + .where(eq(schema.users.key_hash, keyHash)) + .limit(1); + if (rows.length === 0) return null; + return { userId: rows[0].id, balance: rows[0].credits_remaining ?? 0 }; +} + +export async function chargeCredits( + userId: number, + cost: number, +): Promise { + const result = await db() + .update(schema.users) + .set({ + credits_remaining: sql`${schema.users.credits_remaining} - ${cost}`, + last_used_at: sql`(datetime('now'))`, + }) + .where( + and( + eq(schema.users.id, userId), + gte(schema.users.credits_remaining, cost), + ), + ); + return (result.rowsAffected ?? 0) > 0; +} + +export async function setGithubUsername( + userId: number, + username: string, +): Promise { + await db() + .update(schema.users) + .set({ github_username: username }) + .where(eq(schema.users.id, userId)); +} + +export async function setReferredBy( + userId: number, + referrerUsername: string, +): Promise { + await db().run( + sql`UPDATE users SET referred_by = ${referrerUsername} WHERE id = ${userId} AND referred_by IS NULL`, + ); +} + +export async function getUserByGithubUsername(username: string): Promise<{ + id: number; + email: string; +} | null> { + const rows = await db() + .select({ id: schema.users.id, email: schema.users.email }) + .from(schema.users) + .where(eq(schema.users.github_username, username)) + .limit(1); + return rows[0] ?? null; +} + +export async function logApiCall( + userId: number, + endpoint: string, + params: Record, +): Promise { + await db() + .insert(schema.apiCalls) + .values({ user_id: userId, endpoint, params: JSON.stringify(params) }); +} + +export async function getGithubAccessToken( + baUserId: string, +): Promise { + const rows = await db().all<{ access_token: string | null }>( + sql`SELECT access_token FROM account WHERE user_id = ${baUserId} AND provider_id = 'github' LIMIT 1`, + ); + return rows[0]?.access_token ?? null; +} diff --git a/temp/source/shared/embeddings.ts b/temp/source/shared/embeddings.ts new file mode 100644 index 0000000000..e221916d50 --- /dev/null +++ b/temp/source/shared/embeddings.ts @@ -0,0 +1,35 @@ +const EMBED_MODEL = "nvidia/nv-embedqa-e5-v5"; + +export async function getEmbedding( + text: string, + inputType: "query" | "passage" = "query", + apiKey?: string, +): Promise { + const key = + apiKey ?? + (typeof process !== "undefined" + ? process.env?.NVIDIA_NIM_API_KEY + : undefined); + const resp = await fetch("https://integrate.api.nvidia.com/v1/embeddings", { + method: "POST", + headers: { + Authorization: `Bearer ${key}`, + "Content-Type": "application/json", + }, + body: JSON.stringify({ + model: EMBED_MODEL, + input: [text], + input_type: inputType, + }), + }); + if (!resp.ok) { + const body = await resp.text(); + throw new Error(`Embedding API ${resp.status}: ${body}`); + } + const data = (await resp.json()) as { data: { embedding: number[] }[] }; + return data.data[0].embedding; +} + +export function embeddingToVecString(embedding: number[]): string { + return `[${embedding.join(",")}]`; +} diff --git a/temp/source/shared/pricing.ts b/temp/source/shared/pricing.ts new file mode 100644 index 0000000000..3c913dea35 --- /dev/null +++ b/temp/source/shared/pricing.ts @@ -0,0 +1,11 @@ +export const ENDPOINT_COSTS = { + "/v1/articles": 1, + "/v1/search": 5, +} as const; + +export type PricedEndpoint = keyof typeof ENDPOINT_COSTS; + +export const CREDITS_PER_PURCHASE = 500; + +export const PRICE_CHF = 5; +export const CURRENCY = "CHF"; diff --git a/temp/source/shared/schema.ts b/temp/source/shared/schema.ts new file mode 100644 index 0000000000..ddd5c24f67 --- /dev/null +++ b/temp/source/shared/schema.ts @@ -0,0 +1,84 @@ +import { sql } from "drizzle-orm"; +import { + blob, + index, + integer, + sqliteTable, + text, +} from "drizzle-orm/sqlite-core"; + +export const articles = sqliteTable( + "articles", + { + id: integer("id").primaryKey({ autoIncrement: true }), + title: text("title").notNull(), + content: text("content").default(""), + source: text("source").notNull(), + source_type: text("source_type").notNull(), + published_at: text("published_at"), + score: integer("score"), + summary: text("summary"), + categories: text("categories").default("[]"), + kind: text("kind"), + human_edits: text("human_edits").default("[]"), + // embedding is F32_BLOB(1024) — Turso-specific; kept as raw blob, managed via raw SQL + embedding: blob("embedding"), + url: text("url"), + release_date: text("release_date"), + created_at: text("created_at").default(sql`(datetime('now'))`), + }, + (t) => [ + index("idx_articles_score").on(t.score), + index("idx_articles_published_at").on(t.published_at), + ], +); + +export const articleUrls = sqliteTable("article_urls", { + url: text("url").primaryKey(), + article_id: integer("article_id") + .notNull() + .references(() => articles.id), +}); + +export const meta = sqliteTable("meta", { + key: text("key").primaryKey(), + value: text("value").notNull(), + updated_at: text("updated_at").default(sql`(datetime('now'))`), +}); + +export const scoredUrls = sqliteTable("scored_urls", { + url: text("url").primaryKey(), + scored_at: text("scored_at").default(sql`(datetime('now'))`), +}); + +export const users = sqliteTable("users", { + id: integer("id").primaryKey({ autoIncrement: true }), + email: text("email").notNull().unique(), + name: text("name"), + created_at: text("created_at").default(sql`(datetime('now'))`), + newsletter_categories: text("newsletter_categories"), + newsletter_custom: text("newsletter_custom"), + newsletter_utm_source: text("newsletter_utm_source"), + newsletter_updated_at: text("newsletter_updated_at"), + // key_plain dropped — API keys are show-once; only the hash is stored + key_hash: text("key_hash").unique(), + credits_remaining: integer("credits_remaining").default(0), + last_used_at: text("last_used_at"), + github_username: text("github_username"), + referred_by: text("referred_by"), +}); + +export const apiCalls = sqliteTable( + "api_calls", + { + id: integer("id").primaryKey({ autoIncrement: true }), + user_id: integer("user_id").notNull(), + endpoint: text("endpoint").notNull(), + params: text("params").notNull().default("{}"), + created_at: text("created_at").default(sql`(datetime('now'))`), + }, + (t) => [ + index("idx_api_calls_created_at").on(t.created_at), + index("idx_api_calls_user_id").on(t.user_id), + ], +); diff --git a/temp/source/shared/types.ts b/temp/source/shared/types.ts new file mode 100644 index 0000000000..64c97ededa --- /dev/null +++ b/temp/source/shared/types.ts @@ -0,0 +1,57 @@ +export const ARTICLE_CATEGORIES = ["models", "dev", "research"] as const; + +export type ArticleCategory = (typeof ARTICLE_CATEGORIES)[number]; + +export const ARTICLE_KINDS = [ + "repo", + "paper", + "model", + "blog", + "product", + "announcement", +] as const; + +export type ArticleKind = (typeof ARTICLE_KINDS)[number]; + +export interface FetchedArticle { + title: string; + url: string; + content: string; + publishedDate: string; + source: string; + sourceType: "rss" | "hackerNews" | "newsletter" | "aiNews"; +} + +export interface DbArticle { + id: number; + /** Sanitized at insert; may be rewritten by ImproveTitles. */ + title: string; + /** Full article text extracted at ingest time. Capped before LLM calls. */ + content: string; + /** Human-readable source name, e.g. "Hacker News", "AI News", "Ben's Bites". */ + source: string; + /** Source channel: "rss" | "hackerNews" | "newsletter" | "aiNews". */ + source_type: string; + /** Original publication date from the source (RSS pubDate, newsletter date, etc.). Shown in UI. */ + published_at: string | null; + /** 1–10 relevance score from ScoreArticles. NULL = not yet scored or deleted (score=NULL hides from UI). */ + score: number | null; + /** 2–3 line summary from SummarizeAndCategorize. NULL = not yet summarized. */ + summary: string | null; + /** JSON array of ArticleCategory strings, e.g. '["models","dev"]'. */ + categories: string; + /** Content format: "repo" | "paper" | "model" | "blog" | "product" | "announcement". */ + kind: string | null; + /** Date the article was included in a released newsletter edition. NULL = not yet released. Gates UI visibility. */ + release_date: string | null; + /** When the article row was inserted into the DB. Used for pipeline windows (e.g. review-week -7 days). */ + created_at: string; + /** JSON array of field names manually edited by a human, e.g. '["score","categories"]'. Pipelines should not overwrite these. */ + human_edits?: string; +} + +export interface Source { + name: string; + rssUrl: string; + weight: number; +} From 65b9ab6a4f51da1b127cc49bfbe96b5b811f594e Mon Sep 17 00:00:00 2001 From: DS Date: Sun, 28 Jun 2026 09:20:38 +0200 Subject: [PATCH 07/42] Add AI-powered article pipeline with BAML integration (#2) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * feat(pipeline): Python ingestion pipeline v1 (HN + AI News + Substack) - Add baml_src/ at repo root with Python generator (alongside existing TS generator) - Commit generated backend/baml_client/ (Python/pydantic) - Add backend/pipeline/: run.py orchestrator, steps.py helpers, utils.py, sources/{hn,ainews,substack,extract_content,utils}.py - Add ScoredUrl model + Alembic migration (scored_url table) - Add pipeline compose service (supercronic, daily 04:00) - Install supercronic in backend Dockerfile - Add v1 deps: baml-py, trafilatura, feedparser, dnspython, regex Co-Authored-By: Claude Sonnet 4.6 Claude-Session: https://claude.ai/code/session_01SE8sLxeKrZVsPWHBj56kqF * chore(baml): commit regenerated TypeScript baml_client Generated by `baml generate` from baml_src/ (same version 0.223.0 as before; output is identical to the temp/source reference). Co-Authored-By: Claude Sonnet 4.6 Claude-Session: https://claude.ai/code/session_01SE8sLxeKrZVsPWHBj56kqF * refactor(pipeline): remove dead code, fix lint - Drop unused ArticleInput dataclass + to_article_inputs from steps.py (run.py builds BAML inputs directly) - Add _to_baml_input helper in run.py, dedup 3x inline construction - Rename ambiguous `l` -> `lnk` in ainews._pick_primary - Add ruff per-file-ignore T201 for pipeline/ (intentional stdout logging) Co-Authored-By: Claude Sonnet 4.6 Claude-Session: https://claude.ai/code/session_01SE8sLxeKrZVsPWHBj56kqF * chore(baml): drop TypeScript generator and client The TS pipeline is being retired (lives in temp/source/, removed at cutover) and nothing in the live repo imports the root baml_client/. Keep only the Python generator + backend/baml_client/. Co-Authored-By: Claude Sonnet 4.6 Claude-Session: https://claude.ai/code/session_01SE8sLxeKrZVsPWHBj56kqF * fix(ci): ruff format pipeline files; omit alembic from coverage - Run ruff format on all pipeline/ files (was causing pre-commit failure) - Add omit = ["app/alembic/*"] to coverage.run — alembic migration files are already excluded from mypy and ruff; coverage should match. The new scored_url migration tipped coverage below the 90% threshold. Co-Authored-By: Claude Sonnet 4.6 Claude-Session: https://claude.ai/code/session_01SE8sLxeKrZVsPWHBj56kqF * revert: remove alembic omit from coverage config Co-Authored-By: Claude Sonnet 4.6 Claude-Session: https://claude.ai/code/session_01SE8sLxeKrZVsPWHBj56kqF * chore: update changes md --------- Co-authored-by: Claude --- CHANGES.md | 34 +- backend/Dockerfile | 7 + .../b7c8d9e0f1a2_add_scored_url_table.py | 28 + backend/app/models_agentique.py | 6 + backend/baml_client/__init__.py | 60 ++ backend/baml_client/async_client.py | 563 ++++++++++++ backend/baml_client/config.py | 102 +++ backend/baml_client/globals.py | 35 + backend/baml_client/inlinedbaml.py | 28 + backend/baml_client/parser.py | 166 ++++ backend/baml_client/runtime.py | 361 ++++++++ backend/baml_client/stream_types.py | 94 ++ backend/baml_client/sync_client.py | 564 ++++++++++++ backend/baml_client/tracing.py | 22 + backend/baml_client/type_builder.py | 844 ++++++++++++++++++ backend/baml_client/type_map.py | 66 ++ backend/baml_client/types.py | 125 +++ backend/baml_client/watchers.py | 44 + backend/pipeline/__init__.py | 0 backend/pipeline/crontab | 1 + backend/pipeline/run.py | 459 ++++++++++ backend/pipeline/sources/__init__.py | 0 backend/pipeline/sources/ainews.py | 264 ++++++ backend/pipeline/sources/extract_content.py | 147 +++ backend/pipeline/sources/hn.py | 78 ++ .../pipeline/sources/substack-sources.json | 430 +++++++++ backend/pipeline/sources/substack.py | 105 +++ backend/pipeline/sources/utils.py | 55 ++ backend/pipeline/steps.py | 60 ++ backend/pipeline/utils.py | 48 + backend/pyproject.toml | 9 + baml_src/clients.baml | 29 + baml_src/dedup.baml | 58 ++ baml_src/discover.baml | 42 + baml_src/extract_links.baml | 42 + baml_src/extract_products.baml | 125 +++ baml_src/fix_titles.baml | 61 ++ baml_src/generators.baml | 5 + baml_src/score.baml | 84 ++ baml_src/shared.baml | 33 + baml_src/summarize.baml | 111 +++ compose.yml | 22 + uv.lock | 222 +++++ 43 files changed, 5620 insertions(+), 19 deletions(-) create mode 100644 backend/app/alembic/versions/b7c8d9e0f1a2_add_scored_url_table.py create mode 100644 backend/baml_client/__init__.py create mode 100644 backend/baml_client/async_client.py create mode 100644 backend/baml_client/config.py create mode 100644 backend/baml_client/globals.py create mode 100644 backend/baml_client/inlinedbaml.py create mode 100644 backend/baml_client/parser.py create mode 100644 backend/baml_client/runtime.py create mode 100644 backend/baml_client/stream_types.py create mode 100644 backend/baml_client/sync_client.py create mode 100644 backend/baml_client/tracing.py create mode 100644 backend/baml_client/type_builder.py create mode 100644 backend/baml_client/type_map.py create mode 100644 backend/baml_client/types.py create mode 100644 backend/baml_client/watchers.py create mode 100644 backend/pipeline/__init__.py create mode 100644 backend/pipeline/crontab create mode 100644 backend/pipeline/run.py create mode 100644 backend/pipeline/sources/__init__.py create mode 100644 backend/pipeline/sources/ainews.py create mode 100644 backend/pipeline/sources/extract_content.py create mode 100644 backend/pipeline/sources/hn.py create mode 100644 backend/pipeline/sources/substack-sources.json create mode 100644 backend/pipeline/sources/substack.py create mode 100644 backend/pipeline/sources/utils.py create mode 100644 backend/pipeline/steps.py create mode 100644 backend/pipeline/utils.py create mode 100644 baml_src/clients.baml create mode 100644 baml_src/dedup.baml create mode 100644 baml_src/discover.baml create mode 100644 baml_src/extract_links.baml create mode 100644 baml_src/extract_products.baml create mode 100644 baml_src/fix_titles.baml create mode 100644 baml_src/generators.baml create mode 100644 baml_src/score.baml create mode 100644 baml_src/shared.baml create mode 100644 baml_src/summarize.baml diff --git a/CHANGES.md b/CHANGES.md index 28116ba9f4..5018069a6c 100644 --- a/CHANGES.md +++ b/CHANGES.md @@ -4,24 +4,20 @@ Changes made on top of `fastapi/full-stack-fastapi-template`. Upstream files are --- -## 2026-06-27 +## 2026-06-27 (pipeline migration) + +| File | Change | Conflict risk | +| ------------------------ | ----------------------------------------------------------------------- | ---------------------- | +| `backend/pyproject.toml` | Added `baml-py`, `trafilatura`, `feedparser`, `dnspython`, `regex` deps | Low — additive | +| `backend/Dockerfile` | Install supercronic; COPY baml_client + pipeline into image | Low — additive | +| `compose.yml` | Added `pipeline` service (supercronic, daily 04:00) | Low — additive service | -### New files — no upstream conflict -| File | Why | -|---|---| -| `backend/app/models_agentique.py` | Article schema (ArticleBase → Article → ArticlePublic/ArticlesPublic) with pgvector vector(256) column | -| `backend/app/api/routes/articles.py` | Public GET /articles (filtered list) and GET /articles/search (vector) endpoints | -| `backend/app/alembic/versions/a1b2c3d4e5f6_add_articles_table.py` | Creates `article` table, enables pgvector extension, adds HNSW index | -| `backend/scripts/import_articles.py` | One-time migration: reads articles-export.json, re-embeds with model2vec, inserts into Postgres | -| `frontend/src/routes/articles.tsx` | Public /articles page rendering last 20 articles | +--- + +## 2026-06-27 -### Modified upstream files — watch on merge -| File | Change | Conflict risk | -|---|---|---| -| `compose.yml` | db image `postgres:18` → `pgvector/pgvector:pg17` | Low — one line | -| `backend/pyproject.toml` | Added `pgvector`, `model2vec` deps | Low — additive | -| `uv.lock` | Regenerated to include above | Mechanical — re-run `uv lock` after merge | -| `backend/app/api/main.py` | Added `articles` router (items router kept) | Low — one additive line | -| `frontend/src/client/types.gen.ts` | Added Article* types | None — re-run `generate-client` after merge | -| `frontend/src/client/sdk.gen.ts` | Added ArticlesService | None — re-run `generate-client` after merge | -| `frontend/src/routeTree.gen.ts` | Registered /articles route | None — auto-regenerated by vite dev | +| File | Change | Conflict risk | +| ------------------------- | ------------------------------------------------- | ----------------------- | +| `compose.yml` | db image `postgres:18` → `pgvector/pgvector:pg17` | Low — one line | +| `backend/pyproject.toml` | Added `pgvector`, `model2vec` deps | Low — additive | +| `backend/app/api/main.py` | Added `articles` router (items router kept) | Low — one additive line | diff --git a/backend/Dockerfile b/backend/Dockerfile index edef2849f4..e317da16a2 100644 --- a/backend/Dockerfile +++ b/backend/Dockerfile @@ -2,6 +2,11 @@ FROM python:3.14 ENV PYTHONUNBUFFERED=1 +# Install supercronic for container-friendly cron +RUN SUPERCRONIC_URL=https://github.com/aptible/supercronic/releases/download/v0.2.33/supercronic-linux-amd64 \ + && curl -fsSL "$SUPERCRONIC_URL" -o /usr/local/bin/supercronic \ + && chmod +x /usr/local/bin/supercronic + # Install uv # Ref: https://docs.astral.sh/uv/guides/integration/docker/#installing-uv COPY --from=ghcr.io/astral-sh/uv:0.9.26 /uv /uvx /bin/ @@ -32,6 +37,8 @@ COPY ./backend/scripts /app/backend/scripts COPY ./backend/pyproject.toml ./backend/alembic.ini /app/backend/ COPY ./backend/app /app/backend/app +COPY ./backend/baml_client /app/backend/baml_client +COPY ./backend/pipeline /app/backend/pipeline # Sync the project # Ref: https://docs.astral.sh/uv/guides/integration/docker/#intermediate-layers diff --git a/backend/app/alembic/versions/b7c8d9e0f1a2_add_scored_url_table.py b/backend/app/alembic/versions/b7c8d9e0f1a2_add_scored_url_table.py new file mode 100644 index 0000000000..ddcebbdb21 --- /dev/null +++ b/backend/app/alembic/versions/b7c8d9e0f1a2_add_scored_url_table.py @@ -0,0 +1,28 @@ +"""add scored_url table + +Revision ID: b7c8d9e0f1a2 +Revises: a1b2c3d4e5f6 +Create Date: 2026-06-27 00:00:00.000000 + +""" +from alembic import op + +revision = "b7c8d9e0f1a2" +down_revision = "a1b2c3d4e5f6" +branch_labels = None +depends_on = None + + +def upgrade(): + op.execute( + """ + CREATE TABLE IF NOT EXISTS scored_url ( + url TEXT PRIMARY KEY, + created_at TIMESTAMPTZ NOT NULL DEFAULT now() + ) + """ + ) + + +def downgrade(): + op.execute("DROP TABLE IF EXISTS scored_url") diff --git a/backend/app/models_agentique.py b/backend/app/models_agentique.py index 71f895e613..36b7bc02a5 100644 --- a/backend/app/models_agentique.py +++ b/backend/app/models_agentique.py @@ -44,3 +44,9 @@ class ArticlePublic(ArticleBase): class ArticlesPublic(SQLModel): data: list[ArticlePublic] count: int + + +class ScoredUrl(SQLModel, table=True): + __tablename__ = "scored_url" + url: str = Field(primary_key=True) + created_at: datetime = Field(default_factory=get_datetime_utc) diff --git a/backend/baml_client/__init__.py b/backend/baml_client/__init__.py new file mode 100644 index 0000000000..b86cfcbbfd --- /dev/null +++ b/backend/baml_client/__init__.py @@ -0,0 +1,60 @@ +# ---------------------------------------------------------------------------- +# +# Welcome to Baml! To use this generated code, please run the following: +# +# $ pip install baml +# +# ---------------------------------------------------------------------------- + +# This file was generated by BAML: please do not edit it. Instead, edit the +# BAML files and re-generate this code using: baml-cli generate +# baml-cli is available with the baml package. + +__version__ = "0.223.0" + +try: + from baml_py.safe_import import EnsureBamlPyImport +except ImportError: + raise ImportError(f"""Update to baml-py required. +Version of baml_client generator (see generators.baml): {__version__} + +Please upgrade baml-py to version "{__version__}". + +$ pip install baml-py=={__version__} +$ uv add baml-py=={__version__} + +If nothing else works, please ask for help: + +https://github.com/boundaryml/baml/issues +https://boundaryml.com/discord +""") from None + + +with EnsureBamlPyImport(__version__) as e: + e.raise_if_incompatible_version(__version__) + + from . import types + from . import tracing + from . import stream_types + from . import config + from .config import reset_baml_env_vars + + from .async_client import b + + from . import watchers + + +# FOR LEGACY COMPATIBILITY, expose "partial_types" as an alias for "stream_types" +# WE RECOMMEND USERS TO USE "stream_types" INSTEAD +partial_types = stream_types + +__all__ = [ + "b", + "stream_types", + "partial_types", + "tracing", + "types", + "reset_baml_env_vars", + "config", + "watchers", +] \ No newline at end of file diff --git a/backend/baml_client/async_client.py b/backend/baml_client/async_client.py new file mode 100644 index 0000000000..3da46d80ff --- /dev/null +++ b/backend/baml_client/async_client.py @@ -0,0 +1,563 @@ +# ---------------------------------------------------------------------------- +# +# Welcome to Baml! To use this generated code, please run the following: +# +# $ pip install baml +# +# ---------------------------------------------------------------------------- + +# This file was generated by BAML: please do not edit it. Instead, edit the +# BAML files and re-generate this code using: baml-cli generate +# baml-cli is available with the baml package. + +import typing +import typing_extensions +import baml_py + +from . import stream_types, types, type_builder +from .parser import LlmResponseParser, LlmStreamParser +from .runtime import DoNotUseDirectlyCallManager, BamlCallOptions +from .globals import DO_NOT_USE_DIRECTLY_UNLESS_YOU_KNOW_WHAT_YOURE_DOING_RUNTIME as __runtime__ + + +class BamlAsyncClient: + __options: DoNotUseDirectlyCallManager + __stream_client: "BamlStreamClient" + __http_request: "BamlHttpRequestClient" + __http_stream_request: "BamlHttpStreamRequestClient" + __llm_response_parser: LlmResponseParser + __llm_stream_parser: LlmStreamParser + + def __init__(self, options: DoNotUseDirectlyCallManager): + self.__options = options + self.__stream_client = BamlStreamClient(options) + self.__http_request = BamlHttpRequestClient(options) + self.__http_stream_request = BamlHttpStreamRequestClient(options) + self.__llm_response_parser = LlmResponseParser(options) + self.__llm_stream_parser = LlmStreamParser(options) + + def with_options(self, + tb: typing.Optional[type_builder.TypeBuilder] = None, + client_registry: typing.Optional[baml_py.baml_py.ClientRegistry] = None, + client: typing.Optional[str] = None, + collector: typing.Optional[typing.Union[baml_py.baml_py.Collector, typing.List[baml_py.baml_py.Collector]]] = None, + env: typing.Optional[typing.Dict[str, typing.Optional[str]]] = None, + tags: typing.Optional[typing.Dict[str, str]] = None, + on_tick: typing.Optional[typing.Callable[[str, baml_py.baml_py.FunctionLog], None]] = None, + ) -> "BamlAsyncClient": + options: BamlCallOptions = {} + if tb is not None: + options["tb"] = tb + if client_registry is not None: + options["client_registry"] = client_registry + if client is not None: + options["client"] = client + if collector is not None: + options["collector"] = collector + if env is not None: + options["env"] = env + if tags is not None: + options["tags"] = tags + if on_tick is not None: + options["on_tick"] = on_tick + return BamlAsyncClient(self.__options.merge_options(options)) + + @property + def stream(self): + return self.__stream_client + + @property + def request(self): + return self.__http_request + + @property + def stream_request(self): + return self.__http_stream_request + + @property + def parse(self): + return self.__llm_response_parser + + @property + def parse_stream(self): + return self.__llm_stream_parser + + async def CategorizeOnly(self, title: str, + baml_options: BamlCallOptions = {}, + ) -> types.CategorizeOnlyResult: + # Check if on_tick is provided + if 'on_tick' in baml_options: + # Use streaming internally when on_tick is provided + __stream__ = self.stream.CategorizeOnly(title=title, + baml_options=baml_options) + return await __stream__.get_final_response() + else: + # Original non-streaming code + __result__ = await self.__options.merge_options(baml_options).call_function_async(function_name="CategorizeOnly", args={ + "title": title, + }) + return typing.cast(types.CategorizeOnlyResult, __result__.cast_to(types, types, stream_types, False, __runtime__)) + async def ClassifyKind(self, title: str,url: str,summary: typing.Optional[str] = None, + baml_options: BamlCallOptions = {}, + ) -> types.ClassifyKindResult: + # Check if on_tick is provided + if 'on_tick' in baml_options: + # Use streaming internally when on_tick is provided + __stream__ = self.stream.ClassifyKind(title=title,url=url,summary=summary, + baml_options=baml_options) + return await __stream__.get_final_response() + else: + # Original non-streaming code + __result__ = await self.__options.merge_options(baml_options).call_function_async(function_name="ClassifyKind", args={ + "title": title,"url": url,"summary": summary, + }) + return typing.cast(types.ClassifyKindResult, __result__.cast_to(types, types, stream_types, False, __runtime__)) + async def ClassifyProfiles(self, profiles: typing.List["types.ProfileInput"], + baml_options: BamlCallOptions = {}, + ) -> typing.List["types.ProfileVerdict"]: + # Check if on_tick is provided + if 'on_tick' in baml_options: + # Use streaming internally when on_tick is provided + __stream__ = self.stream.ClassifyProfiles(profiles=profiles, + baml_options=baml_options) + return await __stream__.get_final_response() + else: + # Original non-streaming code + __result__ = await self.__options.merge_options(baml_options).call_function_async(function_name="ClassifyProfiles", args={ + "profiles": profiles, + }) + return typing.cast(typing.List["types.ProfileVerdict"], __result__.cast_to(types, types, stream_types, False, __runtime__)) + async def ExtractLinks(self, emailHtml: str, + baml_options: BamlCallOptions = {}, + ) -> typing.List["types.ExtractedLink"]: + # Check if on_tick is provided + if 'on_tick' in baml_options: + # Use streaming internally when on_tick is provided + __stream__ = self.stream.ExtractLinks(emailHtml=emailHtml, + baml_options=baml_options) + return await __stream__.get_final_response() + else: + # Original non-streaming code + __result__ = await self.__options.merge_options(baml_options).call_function_async(function_name="ExtractLinks", args={ + "emailHtml": emailHtml, + }) + return typing.cast(typing.List["types.ExtractedLink"], __result__.cast_to(types, types, stream_types, False, __runtime__)) + async def ExtractProducts(self, newsletterText: str, + baml_options: BamlCallOptions = {}, + ) -> typing.List["types.NewsletterProduct"]: + # Check if on_tick is provided + if 'on_tick' in baml_options: + # Use streaming internally when on_tick is provided + __stream__ = self.stream.ExtractProducts(newsletterText=newsletterText, + baml_options=baml_options) + return await __stream__.get_final_response() + else: + # Original non-streaming code + __result__ = await self.__options.merge_options(baml_options).call_function_async(function_name="ExtractProducts", args={ + "newsletterText": newsletterText, + }) + return typing.cast(typing.List["types.NewsletterProduct"], __result__.cast_to(types, types, stream_types, False, __runtime__)) + async def ImproveTitles(self, articles: typing.List["types.ArticleInput"], + baml_options: BamlCallOptions = {}, + ) -> typing.List["types.TitleFix"]: + # Check if on_tick is provided + if 'on_tick' in baml_options: + # Use streaming internally when on_tick is provided + __stream__ = self.stream.ImproveTitles(articles=articles, + baml_options=baml_options) + return await __stream__.get_final_response() + else: + # Original non-streaming code + __result__ = await self.__options.merge_options(baml_options).call_function_async(function_name="ImproveTitles", args={ + "articles": articles, + }) + return typing.cast(typing.List["types.TitleFix"], __result__.cast_to(types, types, stream_types, False, __runtime__)) + async def ScoreArticles(self, articles: typing.List["types.ArticleInput"], + baml_options: BamlCallOptions = {}, + ) -> typing.List["types.ScoredArticle"]: + # Check if on_tick is provided + if 'on_tick' in baml_options: + # Use streaming internally when on_tick is provided + __stream__ = self.stream.ScoreArticles(articles=articles, + baml_options=baml_options) + return await __stream__.get_final_response() + else: + # Original non-streaming code + __result__ = await self.__options.merge_options(baml_options).call_function_async(function_name="ScoreArticles", args={ + "articles": articles, + }) + return typing.cast(typing.List["types.ScoredArticle"], __result__.cast_to(types, types, stream_types, False, __runtime__)) + async def SelectNotableProducts(self, products: typing.List["types.NewsletterProduct"], + baml_options: BamlCallOptions = {}, + ) -> typing.List[int]: + # Check if on_tick is provided + if 'on_tick' in baml_options: + # Use streaming internally when on_tick is provided + __stream__ = self.stream.SelectNotableProducts(products=products, + baml_options=baml_options) + return await __stream__.get_final_response() + else: + # Original non-streaming code + __result__ = await self.__options.merge_options(baml_options).call_function_async(function_name="SelectNotableProducts", args={ + "products": products, + }) + return typing.cast(typing.List[int], __result__.cast_to(types, types, stream_types, False, __runtime__)) + async def SelectProductLink(self, productName: str,productDescription: str,candidates: typing.List["types.SearchCandidate"], + baml_options: BamlCallOptions = {}, + ) -> types.ProductLinkChoice: + # Check if on_tick is provided + if 'on_tick' in baml_options: + # Use streaming internally when on_tick is provided + __stream__ = self.stream.SelectProductLink(productName=productName,productDescription=productDescription,candidates=candidates, + baml_options=baml_options) + return await __stream__.get_final_response() + else: + # Original non-streaming code + __result__ = await self.__options.merge_options(baml_options).call_function_async(function_name="SelectProductLink", args={ + "productName": productName,"productDescription": productDescription,"candidates": candidates, + }) + return typing.cast(types.ProductLinkChoice, __result__.cast_to(types, types, stream_types, False, __runtime__)) + async def SemanticDedup(self, newArticles: typing.List["types.ArticleInput"],existingArticles: typing.List["types.ExistingArticle"], + baml_options: BamlCallOptions = {}, + ) -> typing.List["types.DedupMatch"]: + # Check if on_tick is provided + if 'on_tick' in baml_options: + # Use streaming internally when on_tick is provided + __stream__ = self.stream.SemanticDedup(newArticles=newArticles,existingArticles=existingArticles, + baml_options=baml_options) + return await __stream__.get_final_response() + else: + # Original non-streaming code + __result__ = await self.__options.merge_options(baml_options).call_function_async(function_name="SemanticDedup", args={ + "newArticles": newArticles,"existingArticles": existingArticles, + }) + return typing.cast(typing.List["types.DedupMatch"], __result__.cast_to(types, types, stream_types, False, __runtime__)) + async def SummarizeAndCategorize(self, title: str,content: str, + baml_options: BamlCallOptions = {}, + ) -> types.SummarizeAndCategorizeResult: + # Check if on_tick is provided + if 'on_tick' in baml_options: + # Use streaming internally when on_tick is provided + __stream__ = self.stream.SummarizeAndCategorize(title=title,content=content, + baml_options=baml_options) + return await __stream__.get_final_response() + else: + # Original non-streaming code + __result__ = await self.__options.merge_options(baml_options).call_function_async(function_name="SummarizeAndCategorize", args={ + "title": title,"content": content, + }) + return typing.cast(types.SummarizeAndCategorizeResult, __result__.cast_to(types, types, stream_types, False, __runtime__)) + + + +class BamlStreamClient: + __options: DoNotUseDirectlyCallManager + + def __init__(self, options: DoNotUseDirectlyCallManager): + self.__options = options + + def CategorizeOnly(self, title: str, + baml_options: BamlCallOptions = {}, + ) -> baml_py.BamlStream[stream_types.CategorizeOnlyResult, types.CategorizeOnlyResult]: + __ctx__, __result__ = self.__options.merge_options(baml_options).create_async_stream(function_name="CategorizeOnly", args={ + "title": title, + }) + return baml_py.BamlStream[stream_types.CategorizeOnlyResult, types.CategorizeOnlyResult]( + __result__, + lambda x: typing.cast(stream_types.CategorizeOnlyResult, x.cast_to(types, types, stream_types, True, __runtime__)), + lambda x: typing.cast(types.CategorizeOnlyResult, x.cast_to(types, types, stream_types, False, __runtime__)), + __ctx__, + ) + def ClassifyKind(self, title: str,url: str,summary: typing.Optional[str] = None, + baml_options: BamlCallOptions = {}, + ) -> baml_py.BamlStream[stream_types.ClassifyKindResult, types.ClassifyKindResult]: + __ctx__, __result__ = self.__options.merge_options(baml_options).create_async_stream(function_name="ClassifyKind", args={ + "title": title,"url": url,"summary": summary, + }) + return baml_py.BamlStream[stream_types.ClassifyKindResult, types.ClassifyKindResult]( + __result__, + lambda x: typing.cast(stream_types.ClassifyKindResult, x.cast_to(types, types, stream_types, True, __runtime__)), + lambda x: typing.cast(types.ClassifyKindResult, x.cast_to(types, types, stream_types, False, __runtime__)), + __ctx__, + ) + def ClassifyProfiles(self, profiles: typing.List["types.ProfileInput"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.BamlStream[typing.List["stream_types.ProfileVerdict"], typing.List["types.ProfileVerdict"]]: + __ctx__, __result__ = self.__options.merge_options(baml_options).create_async_stream(function_name="ClassifyProfiles", args={ + "profiles": profiles, + }) + return baml_py.BamlStream[typing.List["stream_types.ProfileVerdict"], typing.List["types.ProfileVerdict"]]( + __result__, + lambda x: typing.cast(typing.List["stream_types.ProfileVerdict"], x.cast_to(types, types, stream_types, True, __runtime__)), + lambda x: typing.cast(typing.List["types.ProfileVerdict"], x.cast_to(types, types, stream_types, False, __runtime__)), + __ctx__, + ) + def ExtractLinks(self, emailHtml: str, + baml_options: BamlCallOptions = {}, + ) -> baml_py.BamlStream[typing.List["stream_types.ExtractedLink"], typing.List["types.ExtractedLink"]]: + __ctx__, __result__ = self.__options.merge_options(baml_options).create_async_stream(function_name="ExtractLinks", args={ + "emailHtml": emailHtml, + }) + return baml_py.BamlStream[typing.List["stream_types.ExtractedLink"], typing.List["types.ExtractedLink"]]( + __result__, + lambda x: typing.cast(typing.List["stream_types.ExtractedLink"], x.cast_to(types, types, stream_types, True, __runtime__)), + lambda x: typing.cast(typing.List["types.ExtractedLink"], x.cast_to(types, types, stream_types, False, __runtime__)), + __ctx__, + ) + def ExtractProducts(self, newsletterText: str, + baml_options: BamlCallOptions = {}, + ) -> baml_py.BamlStream[typing.List["stream_types.NewsletterProduct"], typing.List["types.NewsletterProduct"]]: + __ctx__, __result__ = self.__options.merge_options(baml_options).create_async_stream(function_name="ExtractProducts", args={ + "newsletterText": newsletterText, + }) + return baml_py.BamlStream[typing.List["stream_types.NewsletterProduct"], typing.List["types.NewsletterProduct"]]( + __result__, + lambda x: typing.cast(typing.List["stream_types.NewsletterProduct"], x.cast_to(types, types, stream_types, True, __runtime__)), + lambda x: typing.cast(typing.List["types.NewsletterProduct"], x.cast_to(types, types, stream_types, False, __runtime__)), + __ctx__, + ) + def ImproveTitles(self, articles: typing.List["types.ArticleInput"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.BamlStream[typing.List["stream_types.TitleFix"], typing.List["types.TitleFix"]]: + __ctx__, __result__ = self.__options.merge_options(baml_options).create_async_stream(function_name="ImproveTitles", args={ + "articles": articles, + }) + return baml_py.BamlStream[typing.List["stream_types.TitleFix"], typing.List["types.TitleFix"]]( + __result__, + lambda x: typing.cast(typing.List["stream_types.TitleFix"], x.cast_to(types, types, stream_types, True, __runtime__)), + lambda x: typing.cast(typing.List["types.TitleFix"], x.cast_to(types, types, stream_types, False, __runtime__)), + __ctx__, + ) + def ScoreArticles(self, articles: typing.List["types.ArticleInput"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.BamlStream[typing.List["stream_types.ScoredArticle"], typing.List["types.ScoredArticle"]]: + __ctx__, __result__ = self.__options.merge_options(baml_options).create_async_stream(function_name="ScoreArticles", args={ + "articles": articles, + }) + return baml_py.BamlStream[typing.List["stream_types.ScoredArticle"], typing.List["types.ScoredArticle"]]( + __result__, + lambda x: typing.cast(typing.List["stream_types.ScoredArticle"], x.cast_to(types, types, stream_types, True, __runtime__)), + lambda x: typing.cast(typing.List["types.ScoredArticle"], x.cast_to(types, types, stream_types, False, __runtime__)), + __ctx__, + ) + def SelectNotableProducts(self, products: typing.List["types.NewsletterProduct"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.BamlStream[typing.List[int], typing.List[int]]: + __ctx__, __result__ = self.__options.merge_options(baml_options).create_async_stream(function_name="SelectNotableProducts", args={ + "products": products, + }) + return baml_py.BamlStream[typing.List[int], typing.List[int]]( + __result__, + lambda x: typing.cast(typing.List[int], x.cast_to(types, types, stream_types, True, __runtime__)), + lambda x: typing.cast(typing.List[int], x.cast_to(types, types, stream_types, False, __runtime__)), + __ctx__, + ) + def SelectProductLink(self, productName: str,productDescription: str,candidates: typing.List["types.SearchCandidate"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.BamlStream[stream_types.ProductLinkChoice, types.ProductLinkChoice]: + __ctx__, __result__ = self.__options.merge_options(baml_options).create_async_stream(function_name="SelectProductLink", args={ + "productName": productName,"productDescription": productDescription,"candidates": candidates, + }) + return baml_py.BamlStream[stream_types.ProductLinkChoice, types.ProductLinkChoice]( + __result__, + lambda x: typing.cast(stream_types.ProductLinkChoice, x.cast_to(types, types, stream_types, True, __runtime__)), + lambda x: typing.cast(types.ProductLinkChoice, x.cast_to(types, types, stream_types, False, __runtime__)), + __ctx__, + ) + def SemanticDedup(self, newArticles: typing.List["types.ArticleInput"],existingArticles: typing.List["types.ExistingArticle"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.BamlStream[typing.List["stream_types.DedupMatch"], typing.List["types.DedupMatch"]]: + __ctx__, __result__ = self.__options.merge_options(baml_options).create_async_stream(function_name="SemanticDedup", args={ + "newArticles": newArticles,"existingArticles": existingArticles, + }) + return baml_py.BamlStream[typing.List["stream_types.DedupMatch"], typing.List["types.DedupMatch"]]( + __result__, + lambda x: typing.cast(typing.List["stream_types.DedupMatch"], x.cast_to(types, types, stream_types, True, __runtime__)), + lambda x: typing.cast(typing.List["types.DedupMatch"], x.cast_to(types, types, stream_types, False, __runtime__)), + __ctx__, + ) + def SummarizeAndCategorize(self, title: str,content: str, + baml_options: BamlCallOptions = {}, + ) -> baml_py.BamlStream[stream_types.SummarizeAndCategorizeResult, types.SummarizeAndCategorizeResult]: + __ctx__, __result__ = self.__options.merge_options(baml_options).create_async_stream(function_name="SummarizeAndCategorize", args={ + "title": title,"content": content, + }) + return baml_py.BamlStream[stream_types.SummarizeAndCategorizeResult, types.SummarizeAndCategorizeResult]( + __result__, + lambda x: typing.cast(stream_types.SummarizeAndCategorizeResult, x.cast_to(types, types, stream_types, True, __runtime__)), + lambda x: typing.cast(types.SummarizeAndCategorizeResult, x.cast_to(types, types, stream_types, False, __runtime__)), + __ctx__, + ) + + +class BamlHttpRequestClient: + __options: DoNotUseDirectlyCallManager + + def __init__(self, options: DoNotUseDirectlyCallManager): + self.__options = options + + async def CategorizeOnly(self, title: str, + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = await self.__options.merge_options(baml_options).create_http_request_async(function_name="CategorizeOnly", args={ + "title": title, + }, mode="request") + return __result__ + async def ClassifyKind(self, title: str,url: str,summary: typing.Optional[str] = None, + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = await self.__options.merge_options(baml_options).create_http_request_async(function_name="ClassifyKind", args={ + "title": title,"url": url,"summary": summary, + }, mode="request") + return __result__ + async def ClassifyProfiles(self, profiles: typing.List["types.ProfileInput"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = await self.__options.merge_options(baml_options).create_http_request_async(function_name="ClassifyProfiles", args={ + "profiles": profiles, + }, mode="request") + return __result__ + async def ExtractLinks(self, emailHtml: str, + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = await self.__options.merge_options(baml_options).create_http_request_async(function_name="ExtractLinks", args={ + "emailHtml": emailHtml, + }, mode="request") + return __result__ + async def ExtractProducts(self, newsletterText: str, + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = await self.__options.merge_options(baml_options).create_http_request_async(function_name="ExtractProducts", args={ + "newsletterText": newsletterText, + }, mode="request") + return __result__ + async def ImproveTitles(self, articles: typing.List["types.ArticleInput"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = await self.__options.merge_options(baml_options).create_http_request_async(function_name="ImproveTitles", args={ + "articles": articles, + }, mode="request") + return __result__ + async def ScoreArticles(self, articles: typing.List["types.ArticleInput"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = await self.__options.merge_options(baml_options).create_http_request_async(function_name="ScoreArticles", args={ + "articles": articles, + }, mode="request") + return __result__ + async def SelectNotableProducts(self, products: typing.List["types.NewsletterProduct"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = await self.__options.merge_options(baml_options).create_http_request_async(function_name="SelectNotableProducts", args={ + "products": products, + }, mode="request") + return __result__ + async def SelectProductLink(self, productName: str,productDescription: str,candidates: typing.List["types.SearchCandidate"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = await self.__options.merge_options(baml_options).create_http_request_async(function_name="SelectProductLink", args={ + "productName": productName,"productDescription": productDescription,"candidates": candidates, + }, mode="request") + return __result__ + async def SemanticDedup(self, newArticles: typing.List["types.ArticleInput"],existingArticles: typing.List["types.ExistingArticle"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = await self.__options.merge_options(baml_options).create_http_request_async(function_name="SemanticDedup", args={ + "newArticles": newArticles,"existingArticles": existingArticles, + }, mode="request") + return __result__ + async def SummarizeAndCategorize(self, title: str,content: str, + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = await self.__options.merge_options(baml_options).create_http_request_async(function_name="SummarizeAndCategorize", args={ + "title": title,"content": content, + }, mode="request") + return __result__ + + +class BamlHttpStreamRequestClient: + __options: DoNotUseDirectlyCallManager + + def __init__(self, options: DoNotUseDirectlyCallManager): + self.__options = options + + async def CategorizeOnly(self, title: str, + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = await self.__options.merge_options(baml_options).create_http_request_async(function_name="CategorizeOnly", args={ + "title": title, + }, mode="stream") + return __result__ + async def ClassifyKind(self, title: str,url: str,summary: typing.Optional[str] = None, + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = await self.__options.merge_options(baml_options).create_http_request_async(function_name="ClassifyKind", args={ + "title": title,"url": url,"summary": summary, + }, mode="stream") + return __result__ + async def ClassifyProfiles(self, profiles: typing.List["types.ProfileInput"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = await self.__options.merge_options(baml_options).create_http_request_async(function_name="ClassifyProfiles", args={ + "profiles": profiles, + }, mode="stream") + return __result__ + async def ExtractLinks(self, emailHtml: str, + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = await self.__options.merge_options(baml_options).create_http_request_async(function_name="ExtractLinks", args={ + "emailHtml": emailHtml, + }, mode="stream") + return __result__ + async def ExtractProducts(self, newsletterText: str, + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = await self.__options.merge_options(baml_options).create_http_request_async(function_name="ExtractProducts", args={ + "newsletterText": newsletterText, + }, mode="stream") + return __result__ + async def ImproveTitles(self, articles: typing.List["types.ArticleInput"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = await self.__options.merge_options(baml_options).create_http_request_async(function_name="ImproveTitles", args={ + "articles": articles, + }, mode="stream") + return __result__ + async def ScoreArticles(self, articles: typing.List["types.ArticleInput"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = await self.__options.merge_options(baml_options).create_http_request_async(function_name="ScoreArticles", args={ + "articles": articles, + }, mode="stream") + return __result__ + async def SelectNotableProducts(self, products: typing.List["types.NewsletterProduct"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = await self.__options.merge_options(baml_options).create_http_request_async(function_name="SelectNotableProducts", args={ + "products": products, + }, mode="stream") + return __result__ + async def SelectProductLink(self, productName: str,productDescription: str,candidates: typing.List["types.SearchCandidate"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = await self.__options.merge_options(baml_options).create_http_request_async(function_name="SelectProductLink", args={ + "productName": productName,"productDescription": productDescription,"candidates": candidates, + }, mode="stream") + return __result__ + async def SemanticDedup(self, newArticles: typing.List["types.ArticleInput"],existingArticles: typing.List["types.ExistingArticle"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = await self.__options.merge_options(baml_options).create_http_request_async(function_name="SemanticDedup", args={ + "newArticles": newArticles,"existingArticles": existingArticles, + }, mode="stream") + return __result__ + async def SummarizeAndCategorize(self, title: str,content: str, + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = await self.__options.merge_options(baml_options).create_http_request_async(function_name="SummarizeAndCategorize", args={ + "title": title,"content": content, + }, mode="stream") + return __result__ + + +b = BamlAsyncClient(DoNotUseDirectlyCallManager({})) \ No newline at end of file diff --git a/backend/baml_client/config.py b/backend/baml_client/config.py new file mode 100644 index 0000000000..64b7fff31b --- /dev/null +++ b/backend/baml_client/config.py @@ -0,0 +1,102 @@ +# ---------------------------------------------------------------------------- +# +# Welcome to Baml! To use this generated code, please run the following: +# +# $ pip install baml +# +# ---------------------------------------------------------------------------- + +# This file was generated by BAML: please do not edit it. Instead, edit the +# BAML files and re-generate this code using: baml-cli generate +# baml-cli is available with the baml package. + +from __future__ import annotations + +import os +import warnings +import typing_extensions +import typing +import functools + +from baml_py.logging import ( + get_log_level as baml_get_log_level, + set_log_level as baml_set_log_level, +) +from .globals import reset_baml_env_vars + +rT = typing_extensions.TypeVar("rT") # return type +pT = typing_extensions.ParamSpec("pT") # parameters type + + +def _deprecated(message: str): + def decorator(func: typing.Callable[pT, rT]) -> typing.Callable[pT, rT]: + """Use this decorator to mark functions as deprecated. + Every time the decorated function runs, it will emit + a "deprecation" warning.""" + + @functools.wraps(func) + def new_func(*args: pT.args, **kwargs: pT.kwargs): + warnings.simplefilter("always", DeprecationWarning) # turn off filter + warnings.warn( + "Call to a deprecated function {}.".format(func.__name__) + message, + category=DeprecationWarning, + stacklevel=2, + ) + warnings.simplefilter("default", DeprecationWarning) # reset filter + return func(*args, **kwargs) + + return new_func + + return decorator + + +@_deprecated("Use os.environ['BAML_LOG'] instead") +def get_log_level(): + """ + Get the log level for the BAML Python client. + """ + return baml_get_log_level() + + +@_deprecated("Use os.environ['BAML_LOG'] instead") +def set_log_level( + level: typing_extensions.Literal["DEBUG", "INFO", "WARN", "ERROR", "OFF"] | str, +): + """ + Set the log level for the BAML Python client + """ + baml_set_log_level(level) + os.environ["BAML_LOG"] = level + + +@_deprecated("Use os.environ['BAML_LOG_JSON_MODE'] instead") +def set_log_json_mode(): + """ + Set the log JSON mode for the BAML Python client. + """ + os.environ["BAML_LOG_JSON_MODE"] = "true" + + +@_deprecated("Use os.environ['BAML_LOG_MAX_CHUNK_LENGTH'] instead") +def set_log_max_chunk_length(): + """ + Set the maximum log chunk length for the BAML Python client. + """ + os.environ["BAML_LOG_MAX_CHUNK_LENGTH"] = "1000" + + +def set_log_max_message_length(*args, **kwargs): + """ + Alias for set_log_max_chunk_length for compatibility with docs. + """ + return set_log_max_chunk_length(*args, **kwargs) + + +__all__ = [ + "set_log_level", + "get_log_level", + "set_log_json_mode", + "reset_baml_env_vars", + "set_log_max_message_length", + "set_log_max_chunk_length", +] diff --git a/backend/baml_client/globals.py b/backend/baml_client/globals.py new file mode 100644 index 0000000000..769e055bb3 --- /dev/null +++ b/backend/baml_client/globals.py @@ -0,0 +1,35 @@ +# ---------------------------------------------------------------------------- +# +# Welcome to Baml! To use this generated code, please run the following: +# +# $ pip install baml +# +# ---------------------------------------------------------------------------- + +# This file was generated by BAML: please do not edit it. Instead, edit the +# BAML files and re-generate this code using: baml-cli generate +# baml-cli is available with the baml package. + +from __future__ import annotations +import os +import warnings + +from baml_py import BamlCtxManager, BamlRuntime +from .inlinedbaml import get_baml_files +from typing import Dict + +DO_NOT_USE_DIRECTLY_UNLESS_YOU_KNOW_WHAT_YOURE_DOING_RUNTIME = BamlRuntime.from_files( + "baml_src", + get_baml_files(), + os.environ.copy() +) +DO_NOT_USE_DIRECTLY_UNLESS_YOU_KNOW_WHAT_YOURE_DOING_CTX = BamlCtxManager(DO_NOT_USE_DIRECTLY_UNLESS_YOU_KNOW_WHAT_YOURE_DOING_RUNTIME) + +def reset_baml_env_vars(env_vars: Dict[str, str]): + warnings.warn( + "reset_baml_env_vars is deprecated and should be removed. Environment variables are now lazily loaded on each function call", + DeprecationWarning, + stacklevel=2 + ) + +__all__ = [] diff --git a/backend/baml_client/inlinedbaml.py b/backend/baml_client/inlinedbaml.py new file mode 100644 index 0000000000..dd5dcec5cb --- /dev/null +++ b/backend/baml_client/inlinedbaml.py @@ -0,0 +1,28 @@ +# ---------------------------------------------------------------------------- +# +# Welcome to Baml! To use this generated code, please run the following: +# +# $ pip install baml +# +# ---------------------------------------------------------------------------- + +# This file was generated by BAML: please do not edit it. Instead, edit the +# BAML files and re-generate this code using: baml-cli generate +# baml-cli is available with the baml package. + +_file_map = { + + "clients.baml": "client Fast {\n provider openai-generic\n options {\n base_url \"https://integrate.api.nvidia.com/v1\"\n api_key env.NVIDIA_NIM_API_KEY\n model \"qwen/qwen3-next-80b-a3b-instruct\"\n timeout 60\n }\n}\n\nclient Nvidia {\n provider openai-generic\n options {\n base_url \"https://integrate.api.nvidia.com/v1\"\n api_key env.NVIDIA_NIM_API_KEY\n model \"moonshotai/kimi-k2.6\"\n timeout 60\n }\n}\n\nclient NvidiaGptOss {\n provider openai-generic\n options {\n base_url \"https://integrate.api.nvidia.com/v1\"\n api_key env.NVIDIA_NIM_API_KEY\n model \"openai/gpt-oss-120b\"\n timeout 60\n }\n}\n", + "dedup.baml": "class DedupMatch {\n url string @description(\"URL of the new article\")\n existingUrl string @description(\"URL of the existing article it duplicates\")\n}\n\nfunction SemanticDedup(\n newArticles: ArticleInput[],\n existingArticles: ExistingArticle[]\n) -> DedupMatch[] {\n client NvidiaGptOss\n prompt #\"\n {{ _.role(\"system\") }}\n You are a semantic similarity engine. You compare article pairs and determine whether they cover the same underlying story. You focus on substance, not surface-level keyword overlap.\n\n {{ _.role(\"user\") }}\n You are given two lists:\n 1. NEW articles that were just fetched\n 2. EXISTING articles already in our database from the last 14 days\n\n Your job: identify which NEW articles are about the same story as an EXISTING article. Two articles are \"the same story\" if they cover the same announcement, release, event, or topic - even if from different sources or with different angles.\n\n NEW articles:\n {% for a in newArticles %}\n {{ loop.index }}. [{{ a.source }}] \"{{ a.title }}\" - {{ a.url }}{% if a.trust %} [trust: {{ a.trust }}]{% endif %}\n {% if a.snippet %} {{ a.snippet }}{% endif %}\n {% endfor %}\n\n EXISTING articles:\n {% for a in existingArticles %}\n {{ loop.index }}. [{{ a.source }}] \"{{ a.title }}\" - {{ a.url }}\n {% endfor %}\n\n For each match, return the new article's URL and the existing article's URL.\n If there are no duplicates, return an empty list.\n\n {{ ctx.output_format }}\n \"#\n}\n\ntest dedup_no_matches {\n functions [SemanticDedup]\n args {\n newArticles [\n {\n url \"https://a.com/1\"\n title \"Claude 4 released\"\n source \"HN\"\n }\n ]\n existingArticles [\n {\n url \"https://b.com/1\"\n title \"The state of Rust in 2026\"\n source \"RSS\"\n }\n ]\n }\n}\n", + "discover.baml": "// Batched relevance classifier for the Substack discovery crawler.\n// One LLM call judges many candidate profiles at once (see ScoreArticles for\n// the array-in/array-out batching pattern). Classification runs on cheap\n// metadata (name + description) BEFORE any per-profile post fetch, and gates\n// both DB insertion and whether the crawler recurses into that profile.\n\nclass ProfileInput {\n handle string @description(\"Substack owner handle, echoed back in the verdict\")\n name string @description(\"Publication name\")\n description string? @description(\"Publication hero text and/or author bio, if known\")\n}\n\nclass ProfileVerdict {\n handle string @description(\"Must exactly match the input handle\")\n isAiRelated bool\n confidence int @description(\"0-100 confidence that AI/ML/LLMs is the PRIMARY focus\")\n}\n\nfunction ClassifyProfiles(profiles: ProfileInput[]) -> ProfileVerdict[] {\n client Nvidia\n prompt #\"\n {{ _.role(\"system\") }}\n You curate sources for a developer-focused AI news platform. For each Substack\n publication, decide whether artificial intelligence is its PRIMARY subject:\n AI/ML/LLMs, foundation models, AI engineering, AI products, or AI research.\n\n Mark isAiRelated = true ONLY when AI is clearly the main topic. Mark false for\n general tech, productivity, marketing, business, crypto, politics, lifestyle, or\n publications that merely mention AI in passing. When the signal is thin (sparse\n description, generic name), lean false and assign low confidence - the crawler\n prunes everything you reject, so false positives pollute the whole subtree.\n\n {{ _.role(\"user\") }}\n Classify every profile. Echo each handle back EXACTLY as given.\n\n {% for p in profiles %}\n {{ loop.index }}. handle={{ p.handle }} | {{ p.name }}{% if p.description %} — {{ p.description }}{% endif %}\n {% endfor %}\n\n {{ ctx.output_format }}\n \"#\n}\n", + "extract_links.baml": "class ExtractedLink {\n title string\n url string\n snippet string @description(\"One-sentence description of the article\")\n}\n\nfunction ExtractLinks(emailHtml: string) -> ExtractedLink[] {\n client NvidiaGptOss\n prompt #\"\n {{ _.role(\"system\") }}\n You are a precise link extraction engine. You parse newsletter HTML and identify external article links while filtering out tracking, admin, and promotional URLs.\n\n {{ _.role(\"user\") }}\n You are given the HTML body of a newsletter email. Extract all article links that point to external news stories, blog posts, research papers, or product announcements.\n\n For each article, return its title, URL, and a one-sentence snippet describing it.\n\n IGNORE these types of links:\n - Tracking/redirect URLs (e.g. links through email marketing platforms)\n - Unsubscribe, manage preferences, or email settings links\n - Social media profile links (twitter, linkedin, etc.)\n - Links back to the newsletter's own homepage, archive index, or subscription page (but DO include article/post links hosted on the newsletter's domain - curated newsletters often host their own content)\n - Sponsor/advertisement links\n - Job posting links\n\n RESOLVE redirect URLs: if a link is clearly a tracking redirect (contains /click, /track, utm_ params, etc.), try to extract the final destination URL from the href. Strip all UTM parameters from URLs.\n\n Newsletter HTML:\n {{ emailHtml }}\n\n If no relevant article links are found, return an empty list.\n\n {{ ctx.output_format }}\n \"#\n}\n\ntest extract_links_basic {\n functions [ExtractLinks]\n args {\n emailHtml \"Welcome to today's issue! [Read OpenAI's new paper](https://openai.com/papers/gpt-5). [Unsubscribe](https://newsletter.com/unsubscribe).\"\n }\n}\n", + "extract_products.baml": "// Product-centric newsletter extraction.\n//\n// Replaces the per-newsletter tracking-URL resolvers: instead of decoding each\n// provider's redirect scheme to recover the real link, we extract the *named\n// products* a newsletter reports on (from anchor text + surrounding prose),\n// keep only the notable ones, and rediscover their canonical URLs via web\n// search (src/sources/email.ts). SelectProductLink then picks the best\n// first-party result among the candidates.\n\nclass NewsletterProduct {\n name string @description(\"Exact product / tool / model / launch name\")\n description string @description(\"Concise phrase: what it is and does, usable verbatim as a web search query\")\n}\n\nfunction ExtractProducts(newsletterText: string) -> NewsletterProduct[] {\n client NvidiaGptOss\n prompt #\"\n {{ _.role(\"system\") }}\n You extract the AI/tech products, tools, models, and launches that a newsletter is reporting on. Work only from the text; never invent products that are not mentioned.\n\n {{ _.role(\"user\") }}\n Below is the text of a newsletter email. Links appear as [anchor text](url) but the URLs are often tracking redirects, so judge by the words, not the links.\n\n Identify every distinct product, tool, model, SDK, dataset, or launch the newsletter is reporting as news. For each, return:\n - name: the exact product/tool/model name\n - description: a concise phrase describing what it is and does, suitable as a web search query\n\n INCLUDE only real, named launches a reader could go use or read about.\n\n IGNORE:\n - the author's intro letter, essay, or personal commentary\n - sponsor blurbs, advertisements, \"brought to you by\", upgrade / subscribe / manage-preferences prompts\n - social-media embeds (an @handle with like / repost / reply counts) and the newsletter's own social links\n - section headers, navigation, and unsubscribe links\n\n Newsletter text:\n {{ newsletterText }}\n\n If the text names no qualifying products, return an empty list.\n\n {{ ctx.output_format }}\n \"#\n}\n\n// Notability gate: trims the extracted list to the launches actually worth\n// resolving, so we don't spend a web search on every incremental SDK bump.\n// Returns the 1-based indices of the products to KEEP.\nfunction SelectNotableProducts(products: NewsletterProduct[]) -> int[] {\n client Nvidia\n prompt #\"\n {{ _.role(\"user\") }}\n Below is a numbered list of products/tools/models a newsletter mentioned. Return the numbers of the ones that are NOTABLE enough to feature in an AI-news aggregator.\n\n KEEP a product if it is a distinct, real, individually newsworthy launch a reader would want to click: new models, significant new products or platforms, notable agents/tools, major releases.\n\n DROP:\n - minor or incremental items: small SDK/utility bumps, niche helper libraries, design skills, config tweaks\n - vague or marketing-only entries with no concrete product behind them\n - duplicates or sub-features of another item in the list\n\n Products:\n {% for p in products %}\n {{ loop.index }}. {{ p.name }} — {{ p.description }}\n {% endfor %}\n\n Return only the numbers to keep, as a JSON array of integers. If none qualify, return [].\n\n {{ ctx.output_format }}\n \"#\n}\n\nclass SearchCandidate {\n title string\n url string\n snippet string\n}\n\nclass ProductLinkChoice {\n index int @description(\"1-based index of the best first-party result, or 0 if none qualifies\")\n confidence float @description(\"0.0 - 1.0\")\n}\n\n// Picks the best canonical URL for a product among search candidates, biased\n// hard toward the official / first-party source and away from social posts and\n// SEO/aggregator pages. Returns index 0 when nothing is clearly the product.\nfunction SelectProductLink(\n productName: string,\n productDescription: string,\n candidates: SearchCandidate[]\n) -> ProductLinkChoice {\n client Nvidia\n prompt #\"\n {{ _.role(\"user\") }}\n A newsletter featured this item:\n name: {{ productName }}\n description: {{ productDescription }}\n\n Web search returned these candidate results:\n {% for c in candidates %}\n {{ loop.index }}. {{ c.title }}\n url: {{ c.url }}\n snippet: {{ c.snippet }}\n {% endfor %}\n\n Pick the ONE candidate that is the canonical, first-party source for this exact product — its official site, product page, model card, repo, or the vendor's own announcement.\n\n PREFER the official / first-party domain that matches the product or its maker.\n REJECT (do not pick) when it is the best available:\n - social-media posts (x.com, twitter.com, linkedin.com, reddit.com, threads, mastodon)\n - videos (youtube.com)\n - content-farm / SEO / generic aggregator or listicle pages that merely mention the product\n - a DIFFERENT product that happens to share the name\n\n Return the 1-based index of the best first-party result. If none of the candidates is clearly a first-party source for THIS product, return index 0.\n\n {{ ctx.output_format }}\n \"#\n}\n\ntest extract_products_basic {\n functions [ExtractProducts]\n args {\n newsletterText \"Headlines: [OpenAI ships GPT-5](https://sub.stack/redirect/2/abc), a new flagship model. Brought to you by Acme. [Unsubscribe](https://newsletter.com/unsub).\"\n }\n}\n", + "fix_titles.baml": "class TitleFix {\n url string @description(\"The exact URL from the matching input article - copy verbatim\")\n title string @description(\"Plain title text only. No surrounding quotes. No leading source name or bracket tag. Max 12 words. Return the input title verbatim if it is already clear, specific, and informative.\")\n}\n\nfunction ImproveTitles(articles: ArticleInput[]) -> TitleFix[] {\n client NvidiaGptOss\n prompt #\"\n {{ _.role(\"system\") }}\n You are a technical editor. You write clear, informative article titles for an AI developer news platform.\n\n Output rules (strict):\n - For each input article, return one TitleFix whose `url` exactly matches that article's URL.\n - The `title` field contains plain title text ONLY. Do NOT wrap it in quotes. Do NOT prefix it with \"[Source]\" or any source name. Do NOT include the URL.\n - Use only the snippet of the SAME article to inform the rewrite. Never blend information across articles.\n\n {{ _.role(\"user\") }}\n Decide for each article whether the existing title is already good. A good title is specific, informative, and technical/neutral in register - it tells a developer what the article is actually about.\n\n - If the existing title is already good, return it verbatim.\n - Otherwise rewrite it using only that article's snippet: specific, informative, max 12 words, technical/neutral register, no hype or filler.\n\n {% for a in articles %}\n --- Article {{ loop.index }} ---\n url: {{ a.url }}\n source: {{ a.source }}\n current_title: {{ a.title }}\n {% if a.snippet %}snippet: {{ a.snippet }}{% endif %}\n {% endfor %}\n\n {{ ctx.output_format }}\n \"#\n}\n\ntest improve_titles_rewrite_short {\n functions [ImproveTitles]\n args {\n articles [\n {\n url \"https://example.com/claude\"\n title \"Claude 4\"\n source \"HN\"\n snippet \"Anthropic today released Claude 4, a new flagship model with improved reasoning and a 1M-token context window.\"\n }\n ]\n }\n}\n\ntest improve_titles_keep_unchanged {\n functions [ImproveTitles]\n args {\n articles [\n {\n url \"https://example.com/post\"\n title \"Anthropic releases Claude 4 with 1M-token context window\"\n source \"HN\"\n snippet \"Anthropic today released Claude 4, a new flagship model with improved reasoning.\"\n }\n ]\n }\n}\n", + "generators.baml": "generator python {\n output_type \"python/pydantic\"\n output_dir \"../backend/\"\n version \"0.223.0\"\n}\n", + "score.baml": "class ScoredArticle {\n url string\n score int @description(\"1-100 developer-actionability rating\")\n}\n\nfunction ScoreArticles(articles: ArticleInput[]) -> ScoredArticle[] {\n client Nvidia\n prompt #\"\n {{ _.role(\"system\") }}\n You are a senior editorial analyst at a developer news platform. Your job is to evaluate articles for relevance and actionability for AI builders. You are precise, consistent, and ruthless about filtering noise.\n\n {{ _.role(\"user\") }}\n Score every article for developer-actionability on a 1-100 scale.\n\n STEP 1 - SCOPE CHECK (apply first, before scoring):\n Is the article about AI, ML, LLMs, foundation models, or AI-adjacent developer tools/infrastructure?\n - NO → score 1-20 and move on. Do NOT apply the scoring guide below.\n - Out-of-scope examples: text editors, parsers, version control tools, data structures (CRDTs, B-trees), memory management, general programming tutorials, non-AI open source projects, codebase audits, legacy code. These are general software engineering - not AI.\n\n STEP 2 - SCORE (only for in-scope articles):\n Audience: developers, startup founders, and tech leaders building with AI who want to ship faster.\n\n Score 91-100 is reserved for exceptional articles that are BOTH immediately actionable today AND fit one of these themes: local/on-device inference, privacy-preserving AI, efficiency breakthroughs (quantization, token optimization, running models on less hardware), or deep technical dives that explain how something actually works. A score in this range means \"a developer could open a terminal and act on this within the hour, AND it reveals a non-obvious insight or technique.\" Zero is a valid outcome - do not give 91+ just because something is the best of a weak batch.\n\n Models (new releases, benchmarks, evals, model cards, comparisons):\n - 81-90: New model release or major update, model system cards, open-weight models a developer can run today\n - 71-80: Meaningful benchmark or eval, model comparison with actionable conclusions\n\n Dev (SDKs, frameworks, CLI tools, IDE integrations, open-source projects, tutorials, deployment):\n - 81-90: New AI API or SDK, open-source AI tool/library a developer can use today\n - 71-80: Fine-tuning guide, RAG pattern, significant framework update, AI infrastructure (training, inference, memory optimization), deployment recipes\n\n Research (papers, breakthroughs, novel techniques):\n - 71-80: Research with immediate practical implications, AI security research\n - 51-60: Research with near-term practical implications\n\n Industry (funding, platform changes, acquisitions, partnerships, market shifts):\n - 51-60: Industry analysis with actionable takeaways, AI platform partnerships\n - 31-40: Funding rounds without product details, opinion/commentary with no actionable steps, \"AI is changing everything\" think pieces, personal anecdotes about using AI\n\n Upgrade to 91-100: if an article would score 81-90 AND fits the top-tier criteria above (local inference, privacy-preserving, efficiency breakthrough, or deep how-it-works dive), give it 91-100.\n\n Bottom tier:\n - 1-20: Non-AI topics (see step 1), regulation, politics, lawsuits, corporate drama\n\n Trust bonus: entries may include a [trust: high/medium/low] tag. Give +1 to high-trust sources when content quality is comparable.\n\n Articles:\n {% for a in articles %}\n {{ loop.index }}. [{{ a.source }}] \"{{ a.title }}\" - {{ a.url }}{% if a.trust %} [trust: {{ a.trust }}]{% endif %}\n {% if a.snippet %} {{ a.snippet }}{% endif %}\n {% endfor %}\n\n {{ ctx.output_format }}\n \"#\n}\n\ntest score_gpt5_release {\n functions [ScoreArticles]\n args {\n articles [\n {\n url \"https://openai.com/index/introducing-gpt-5\"\n title \"Introducing GPT-5\"\n source \"Hacker News\"\n trust \"medium\"\n }\n ]\n }\n}\n\ntest score_out_of_scope {\n functions [ScoreArticles]\n args {\n articles [\n {\n url \"https://example.com/crdt-deep-dive\"\n title \"A Deep Dive Into CRDTs and Conflict Resolution\"\n source \"Some Blog\"\n trust \"low\"\n }\n ]\n }\n}\n", + "shared.baml": "// Shared types used by multiple BAML functions.\n\nenum ArticleCategory {\n Models\n Dev\n Research\n}\n\nenum ArticleKind {\n Repo // GitHub/GitLab repository\n Paper // Academic paper, preprint, technical report\n Model // Model card or model release page\n Blog // Developer blog post, tutorial, how-to, opinion piece\n Product // Product launch page or product website\n Announcement // Official release post from a major AI lab\n}\n\n// Used as input to ScoreArticles, ImproveTitles, SemanticDedup.\n// Mirrors the fields the existing formatArticles() helper emits.\nclass ArticleInput {\n url string\n title string\n source string\n snippet string? @description(\"First ~200 chars of the article content, if any\")\n trust string? @description(\"\\\"high\\\" | \\\"medium\\\" | \\\"low\\\" - source trust tag\")\n}\n\n// Used as input to SemanticDedup for rows already in the DB.\nclass ExistingArticle {\n url string\n title string\n source string\n}\n", + "summarize.baml": "class SummarizeAndCategorizeResult {\n summary string @description(\"2-3 short factual lines separated by \\\\n\")\n categories ArticleCategory[] @description(\"1-2 categories\")\n kind ArticleKind\n}\n\nclass CategorizeOnlyResult {\n categories ArticleCategory[] @description(\"1-2 categories\")\n}\n\nclass ClassifyKindResult {\n kind ArticleKind\n}\n\nfunction SummarizeAndCategorize(title: string, content: string) -> SummarizeAndCategorizeResult {\n client NvidiaGptOss\n prompt #\"\n {{ _.role(\"system\") }}\n You are a technical writer for a developer news digest. Your readers are tech-savvy but busy. Write in plain, direct language.\n\n {{ _.role(\"user\") }}\n Summarize this article. Be plain and brief.\n\n Title: {{ title }}\n\n Content:\n {{ content }}\n\n 1. Write 2-3 lines. Keep each line to one short sentence. Rules:\n - Only state facts from the article.\n - No passive voice. No \"enables\", \"allows\", \"provides\".\n - Separate lines with a newline.\n 2. Assign 1-2 categories.\n 3. Assign a kind.\n\n Category definitions:\n - Models: New model releases, benchmarks, evals, model cards, model comparisons\n - Dev: Repos, tools, product launches, developer blogs, tutorials, how-tos, fine-tuning guides, deployment recipes, infrastructure updates\n - Research: Papers, breakthroughs, novel techniques with practical implications\n\n Kind definitions:\n - Repo: GitHub or GitLab repository\n - Paper: Academic paper, preprint, or long-form technical report\n - Model: Model card or model release page (e.g. HuggingFace)\n - Blog: Developer blog post, tutorial, how-to, or opinion piece\n - Product: Product launch page or product website\n - Announcement: Official release post from a major AI lab (OpenAI, Anthropic, Google, Meta, Mistral, etc.)\n\n {{ ctx.output_format }}\n \"#\n}\n\nfunction ClassifyKind(title: string, url: string, summary: string?) -> ClassifyKindResult {\n client NvidiaGptOss\n prompt #\"\n {{ _.role(\"system\") }}\n You are a technical librarian who classifies AI developer content by format.\n\n {{ _.role(\"user\") }}\n Classify this article's kind.\n\n Title: {{ title }}\n URL: {{ url }}\n {% if summary %}Summary: {{ summary }}{% endif %}\n\n Kind definitions:\n - Repo: GitHub or GitLab repository\n - Paper: Academic paper, preprint, or long-form technical report\n - Model: Model card or model release page (e.g. HuggingFace)\n - Blog: Developer blog post, tutorial, how-to, or opinion piece\n - Product: Product launch page or product website\n - Announcement: Official release post from a major AI lab (OpenAI, Anthropic, Google, Meta, Mistral, etc.)\n\n {{ ctx.output_format }}\n \"#\n}\n\nfunction CategorizeOnly(title: string) -> CategorizeOnlyResult {\n client NvidiaGptOss\n prompt #\"\n {{ _.role(\"system\") }}\n You are a technical librarian who classifies developer-focused AI articles.\n\n {{ _.role(\"user\") }}\n Assign 1-2 categories to this article title.\n\n Title: {{ title }}\n\n Category definitions:\n - Models: New model releases, benchmarks, evals, model cards, model comparisons\n - Dev: Repos, tools, product launches, developer blogs, tutorials, how-tos, fine-tuning guides, deployment recipes, infrastructure updates\n - Research: Papers, breakthroughs, novel techniques with practical implications\n\n {{ ctx.output_format }}\n \"#\n}\n\ntest summarize_basic {\n functions [SummarizeAndCategorize]\n args {\n title \"Anthropic releases Claude 4\"\n content \"Anthropic today launched Claude 4, a new flagship model. It features improved reasoning, a 1M-token context window, and native tool use. The model is available via API and Claude.ai starting today.\"\n }\n}\n\ntest categorize_only_basic {\n functions [CategorizeOnly]\n args {\n title \"OpenAI releases GPT-5 with 2M context\"\n }\n}\n", +} + +def get_baml_files(): + return _file_map \ No newline at end of file diff --git a/backend/baml_client/parser.py b/backend/baml_client/parser.py new file mode 100644 index 0000000000..f41c08fa06 --- /dev/null +++ b/backend/baml_client/parser.py @@ -0,0 +1,166 @@ +# ---------------------------------------------------------------------------- +# +# Welcome to Baml! To use this generated code, please run the following: +# +# $ pip install baml +# +# ---------------------------------------------------------------------------- + +# This file was generated by BAML: please do not edit it. Instead, edit the +# BAML files and re-generate this code using: baml-cli generate +# baml-cli is available with the baml package. + +import typing +import typing_extensions + + +from . import stream_types, types +from .runtime import DoNotUseDirectlyCallManager, BamlCallOptions + +class LlmResponseParser: + __options: DoNotUseDirectlyCallManager + + def __init__(self, options: DoNotUseDirectlyCallManager): + self.__options = options + + def CategorizeOnly( + self, llm_response: str, baml_options: BamlCallOptions = {}, + ) -> types.CategorizeOnlyResult: + __result__ = self.__options.merge_options(baml_options).parse_response(function_name="CategorizeOnly", llm_response=llm_response, mode="request") + return typing.cast(types.CategorizeOnlyResult, __result__) + + def ClassifyKind( + self, llm_response: str, baml_options: BamlCallOptions = {}, + ) -> types.ClassifyKindResult: + __result__ = self.__options.merge_options(baml_options).parse_response(function_name="ClassifyKind", llm_response=llm_response, mode="request") + return typing.cast(types.ClassifyKindResult, __result__) + + def ClassifyProfiles( + self, llm_response: str, baml_options: BamlCallOptions = {}, + ) -> typing.List["types.ProfileVerdict"]: + __result__ = self.__options.merge_options(baml_options).parse_response(function_name="ClassifyProfiles", llm_response=llm_response, mode="request") + return typing.cast(typing.List["types.ProfileVerdict"], __result__) + + def ExtractLinks( + self, llm_response: str, baml_options: BamlCallOptions = {}, + ) -> typing.List["types.ExtractedLink"]: + __result__ = self.__options.merge_options(baml_options).parse_response(function_name="ExtractLinks", llm_response=llm_response, mode="request") + return typing.cast(typing.List["types.ExtractedLink"], __result__) + + def ExtractProducts( + self, llm_response: str, baml_options: BamlCallOptions = {}, + ) -> typing.List["types.NewsletterProduct"]: + __result__ = self.__options.merge_options(baml_options).parse_response(function_name="ExtractProducts", llm_response=llm_response, mode="request") + return typing.cast(typing.List["types.NewsletterProduct"], __result__) + + def ImproveTitles( + self, llm_response: str, baml_options: BamlCallOptions = {}, + ) -> typing.List["types.TitleFix"]: + __result__ = self.__options.merge_options(baml_options).parse_response(function_name="ImproveTitles", llm_response=llm_response, mode="request") + return typing.cast(typing.List["types.TitleFix"], __result__) + + def ScoreArticles( + self, llm_response: str, baml_options: BamlCallOptions = {}, + ) -> typing.List["types.ScoredArticle"]: + __result__ = self.__options.merge_options(baml_options).parse_response(function_name="ScoreArticles", llm_response=llm_response, mode="request") + return typing.cast(typing.List["types.ScoredArticle"], __result__) + + def SelectNotableProducts( + self, llm_response: str, baml_options: BamlCallOptions = {}, + ) -> typing.List[int]: + __result__ = self.__options.merge_options(baml_options).parse_response(function_name="SelectNotableProducts", llm_response=llm_response, mode="request") + return typing.cast(typing.List[int], __result__) + + def SelectProductLink( + self, llm_response: str, baml_options: BamlCallOptions = {}, + ) -> types.ProductLinkChoice: + __result__ = self.__options.merge_options(baml_options).parse_response(function_name="SelectProductLink", llm_response=llm_response, mode="request") + return typing.cast(types.ProductLinkChoice, __result__) + + def SemanticDedup( + self, llm_response: str, baml_options: BamlCallOptions = {}, + ) -> typing.List["types.DedupMatch"]: + __result__ = self.__options.merge_options(baml_options).parse_response(function_name="SemanticDedup", llm_response=llm_response, mode="request") + return typing.cast(typing.List["types.DedupMatch"], __result__) + + def SummarizeAndCategorize( + self, llm_response: str, baml_options: BamlCallOptions = {}, + ) -> types.SummarizeAndCategorizeResult: + __result__ = self.__options.merge_options(baml_options).parse_response(function_name="SummarizeAndCategorize", llm_response=llm_response, mode="request") + return typing.cast(types.SummarizeAndCategorizeResult, __result__) + + + +class LlmStreamParser: + __options: DoNotUseDirectlyCallManager + + def __init__(self, options: DoNotUseDirectlyCallManager): + self.__options = options + + def CategorizeOnly( + self, llm_response: str, baml_options: BamlCallOptions = {}, + ) -> stream_types.CategorizeOnlyResult: + __result__ = self.__options.merge_options(baml_options).parse_response(function_name="CategorizeOnly", llm_response=llm_response, mode="stream") + return typing.cast(stream_types.CategorizeOnlyResult, __result__) + + def ClassifyKind( + self, llm_response: str, baml_options: BamlCallOptions = {}, + ) -> stream_types.ClassifyKindResult: + __result__ = self.__options.merge_options(baml_options).parse_response(function_name="ClassifyKind", llm_response=llm_response, mode="stream") + return typing.cast(stream_types.ClassifyKindResult, __result__) + + def ClassifyProfiles( + self, llm_response: str, baml_options: BamlCallOptions = {}, + ) -> typing.List["stream_types.ProfileVerdict"]: + __result__ = self.__options.merge_options(baml_options).parse_response(function_name="ClassifyProfiles", llm_response=llm_response, mode="stream") + return typing.cast(typing.List["stream_types.ProfileVerdict"], __result__) + + def ExtractLinks( + self, llm_response: str, baml_options: BamlCallOptions = {}, + ) -> typing.List["stream_types.ExtractedLink"]: + __result__ = self.__options.merge_options(baml_options).parse_response(function_name="ExtractLinks", llm_response=llm_response, mode="stream") + return typing.cast(typing.List["stream_types.ExtractedLink"], __result__) + + def ExtractProducts( + self, llm_response: str, baml_options: BamlCallOptions = {}, + ) -> typing.List["stream_types.NewsletterProduct"]: + __result__ = self.__options.merge_options(baml_options).parse_response(function_name="ExtractProducts", llm_response=llm_response, mode="stream") + return typing.cast(typing.List["stream_types.NewsletterProduct"], __result__) + + def ImproveTitles( + self, llm_response: str, baml_options: BamlCallOptions = {}, + ) -> typing.List["stream_types.TitleFix"]: + __result__ = self.__options.merge_options(baml_options).parse_response(function_name="ImproveTitles", llm_response=llm_response, mode="stream") + return typing.cast(typing.List["stream_types.TitleFix"], __result__) + + def ScoreArticles( + self, llm_response: str, baml_options: BamlCallOptions = {}, + ) -> typing.List["stream_types.ScoredArticle"]: + __result__ = self.__options.merge_options(baml_options).parse_response(function_name="ScoreArticles", llm_response=llm_response, mode="stream") + return typing.cast(typing.List["stream_types.ScoredArticle"], __result__) + + def SelectNotableProducts( + self, llm_response: str, baml_options: BamlCallOptions = {}, + ) -> typing.List[int]: + __result__ = self.__options.merge_options(baml_options).parse_response(function_name="SelectNotableProducts", llm_response=llm_response, mode="stream") + return typing.cast(typing.List[int], __result__) + + def SelectProductLink( + self, llm_response: str, baml_options: BamlCallOptions = {}, + ) -> stream_types.ProductLinkChoice: + __result__ = self.__options.merge_options(baml_options).parse_response(function_name="SelectProductLink", llm_response=llm_response, mode="stream") + return typing.cast(stream_types.ProductLinkChoice, __result__) + + def SemanticDedup( + self, llm_response: str, baml_options: BamlCallOptions = {}, + ) -> typing.List["stream_types.DedupMatch"]: + __result__ = self.__options.merge_options(baml_options).parse_response(function_name="SemanticDedup", llm_response=llm_response, mode="stream") + return typing.cast(typing.List["stream_types.DedupMatch"], __result__) + + def SummarizeAndCategorize( + self, llm_response: str, baml_options: BamlCallOptions = {}, + ) -> stream_types.SummarizeAndCategorizeResult: + __result__ = self.__options.merge_options(baml_options).parse_response(function_name="SummarizeAndCategorize", llm_response=llm_response, mode="stream") + return typing.cast(stream_types.SummarizeAndCategorizeResult, __result__) + + \ No newline at end of file diff --git a/backend/baml_client/runtime.py b/backend/baml_client/runtime.py new file mode 100644 index 0000000000..27fc3a9b45 --- /dev/null +++ b/backend/baml_client/runtime.py @@ -0,0 +1,361 @@ +# ---------------------------------------------------------------------------- +# +# Welcome to Baml! To use this generated code, please run the following: +# +# $ pip install baml +# +# ---------------------------------------------------------------------------- + +# This file was generated by BAML: please do not edit it. Instead, edit the +# BAML files and re-generate this code using: baml-cli generate +# baml-cli is available with the baml package. + +import os +import typing +import typing_extensions + +import baml_py + +from . import types, stream_types, type_builder +from .globals import DO_NOT_USE_DIRECTLY_UNLESS_YOU_KNOW_WHAT_YOURE_DOING_RUNTIME as __runtime__, DO_NOT_USE_DIRECTLY_UNLESS_YOU_KNOW_WHAT_YOURE_DOING_CTX as __ctx__manager__ + + +class BamlCallOptions(typing.TypedDict, total=False): + tb: typing_extensions.NotRequired[type_builder.TypeBuilder] + client_registry: typing_extensions.NotRequired[baml_py.baml_py.ClientRegistry] + client: typing_extensions.NotRequired[str] + env: typing_extensions.NotRequired[typing.Dict[str, typing.Optional[str]]] + tags: typing_extensions.NotRequired[typing.Dict[str, str]] + collector: typing_extensions.NotRequired[ + typing.Union[baml_py.baml_py.Collector, typing.List[baml_py.baml_py.Collector]] + ] + abort_controller: typing_extensions.NotRequired[baml_py.baml_py.AbortController] + on_tick: typing_extensions.NotRequired[typing.Callable[[str, baml_py.baml_py.FunctionLog], None]] + watchers: typing_extensions.NotRequired[typing.Any] # EventCollector type, will be overridden in generated clients + + +class _ResolvedBamlOptions: + tb: typing.Optional[baml_py.baml_py.TypeBuilder] + client_registry: typing.Optional[baml_py.baml_py.ClientRegistry] + collectors: typing.List[baml_py.baml_py.Collector] + env_vars: typing.Dict[str, str] + tags: typing.Dict[str, str] + abort_controller: typing.Optional[baml_py.baml_py.AbortController] + on_tick: typing.Optional[typing.Callable[[], None]] + watchers: typing.Optional[typing.Any] + + def __init__( + self, + tb: typing.Optional[baml_py.baml_py.TypeBuilder], + client_registry: typing.Optional[baml_py.baml_py.ClientRegistry], + collectors: typing.List[baml_py.baml_py.Collector], + env_vars: typing.Dict[str, str], + tags: typing.Dict[str, str], + abort_controller: typing.Optional[baml_py.baml_py.AbortController], + on_tick: typing.Optional[typing.Callable[[], None]], + watchers: typing.Optional[typing.Any], + ): + self.tb = tb + self.client_registry = client_registry + self.collectors = collectors + self.env_vars = env_vars + self.tags = tags + self.abort_controller = abort_controller + self.on_tick = on_tick + self.watchers = watchers + + + + +class DoNotUseDirectlyCallManager: + def __init__(self, baml_options: BamlCallOptions): + self.__baml_options = baml_options + + def __getstate__(self): + # Return state needed for pickling + return {"baml_options": self.__baml_options} + + def __setstate__(self, state): + # Restore state from pickling + self.__baml_options = state["baml_options"] + + def __resolve(self) -> _ResolvedBamlOptions: + tb = self.__baml_options.get("tb") + if tb is not None: + baml_tb = tb._tb # type: ignore (we know how to use this private attribute) + else: + baml_tb = None + client_registry = self.__baml_options.get("client_registry") + client = self.__baml_options.get("client") + + # If client is provided, it takes precedence (creates/overrides client_registry primary) + if client is not None: + if client_registry is None: + client_registry = baml_py.baml_py.ClientRegistry() + client_registry.set_primary(client) + + collector = self.__baml_options.get("collector") + collectors_as_list = ( + collector + if isinstance(collector, list) + else [collector] if collector is not None else [] + ) + env_vars = os.environ.copy() + for k, v in self.__baml_options.get("env", {}).items(): + if v is not None: + env_vars[k] = v + else: + env_vars.pop(k, None) + + tags = self.__baml_options.get("tags", {}) or {} + + abort_controller = self.__baml_options.get("abort_controller") + + on_tick = self.__baml_options.get("on_tick") + if on_tick is not None: + collector = baml_py.baml_py.Collector("on-tick-collector") + collectors_as_list.append(collector) + def on_tick_wrapper(): + log = collector.last + if log is not None: + on_tick("Unknown", log) + else: + on_tick_wrapper = None + + watchers = self.__baml_options.get("watchers") + + return _ResolvedBamlOptions( + baml_tb, + client_registry, + collectors_as_list, + env_vars, + tags, + abort_controller, + on_tick_wrapper, + watchers, + ) + + def merge_options(self, options: BamlCallOptions) -> "DoNotUseDirectlyCallManager": + return DoNotUseDirectlyCallManager({**self.__baml_options, **options}) + + async def call_function_async( + self, *, function_name: str, args: typing.Dict[str, typing.Any] + ) -> baml_py.baml_py.FunctionResult: + resolved_options = self.__resolve() + + # Check if already aborted + if resolved_options.abort_controller is not None and resolved_options.abort_controller.aborted: + raise baml_py.baml_py.BamlAbortError("Operation was aborted") + + return await __runtime__.call_function( + function_name, + args, + # ctx + __ctx__manager__.clone_context(), + # tb + resolved_options.tb, + # cr + resolved_options.client_registry, + # collectors + resolved_options.collectors, + # env_vars + resolved_options.env_vars, + # tags + resolved_options.tags, + # abort_controller + resolved_options.abort_controller, + # watchers + resolved_options.watchers, + ) + + def call_function_sync( + self, *, function_name: str, args: typing.Dict[str, typing.Any] + ) -> baml_py.baml_py.FunctionResult: + resolved_options = self.__resolve() + + # Check if already aborted + if resolved_options.abort_controller is not None and resolved_options.abort_controller.aborted: + raise baml_py.baml_py.BamlAbortError("Operation was aborted") + + ctx = __ctx__manager__.get() + return __runtime__.call_function_sync( + function_name, + args, + # ctx + ctx, + # tb + resolved_options.tb, + # cr + resolved_options.client_registry, + # collectors + resolved_options.collectors, + # env_vars + resolved_options.env_vars, + # tags + resolved_options.tags, + # abort_controller + resolved_options.abort_controller, + # watchers + resolved_options.watchers, + ) + + def create_async_stream( + self, + *, + function_name: str, + args: typing.Dict[str, typing.Any], + ) -> typing.Tuple[baml_py.baml_py.RuntimeContextManager, baml_py.baml_py.FunctionResultStream]: + resolved_options = self.__resolve() + ctx = __ctx__manager__.clone_context() + result = __runtime__.stream_function( + function_name, + args, + # this is always None, we set this later! + # on_event + None, + # ctx + ctx, + # tb + resolved_options.tb, + # cr + resolved_options.client_registry, + # collectors + resolved_options.collectors, + # env_vars + resolved_options.env_vars, + # tags + resolved_options.tags, + # on_tick + resolved_options.on_tick, + # abort_controller + resolved_options.abort_controller, + ) + return ctx, result + + def create_sync_stream( + self, + *, + function_name: str, + args: typing.Dict[str, typing.Any], + ) -> typing.Tuple[baml_py.baml_py.RuntimeContextManager, baml_py.baml_py.SyncFunctionResultStream]: + resolved_options = self.__resolve() + if resolved_options.on_tick is not None: + raise ValueError("on_tick is not supported for sync streams. Please use async streams instead.") + ctx = __ctx__manager__.get() + result = __runtime__.stream_function_sync( + function_name, + args, + # this is always None, we set this later! + # on_event + None, + # ctx + ctx, + # tb + resolved_options.tb, + # cr + resolved_options.client_registry, + # collectors + resolved_options.collectors, + # env_vars + resolved_options.env_vars, + # tags + resolved_options.tags, + # on_tick + # always None! sync streams don't support on_tick + None, + # abort_controller + resolved_options.abort_controller, + ) + return ctx, result + + async def create_http_request_async( + self, + *, + function_name: str, + args: typing.Dict[str, typing.Any], + mode: typing_extensions.Literal["stream", "request"], + ) -> baml_py.baml_py.HTTPRequest: + resolved_options = self.__resolve() + return await __runtime__.build_request( + function_name, + args, + # ctx + __ctx__manager__.clone_context(), + # tb + resolved_options.tb, + # cr + resolved_options.client_registry, + # env_vars + resolved_options.env_vars, + # is_stream + mode == "stream", + ) + + def create_http_request_sync( + self, + *, + function_name: str, + args: typing.Dict[str, typing.Any], + mode: typing_extensions.Literal["stream", "request"], + ) -> baml_py.baml_py.HTTPRequest: + resolved_options = self.__resolve() + return __runtime__.build_request_sync( + function_name, + args, + # ctx + __ctx__manager__.get(), + # tb + resolved_options.tb, + # cr + resolved_options.client_registry, + # env_vars + resolved_options.env_vars, + # is_stream + mode == "stream", + ) + + def parse_response(self, *, function_name: str, llm_response: str, mode: typing_extensions.Literal["stream", "request"]) -> typing.Any: + resolved_options = self.__resolve() + return __runtime__.parse_llm_response( + function_name, + llm_response, + # enum_module + types, + # cls_module + types, + # partial_cls_module + stream_types, + # allow_partials + mode == "stream", + # ctx + __ctx__manager__.get(), + # tb + resolved_options.tb, + # cr + resolved_options.client_registry, + # env_vars + resolved_options.env_vars, + ) + + +def disassemble(function: typing.Callable) -> None: + import inspect + from . import b + + if not callable(function): + print(f"disassemble: object {function} is not a Baml function") + return + + is_client_method = False + + for (method_name, _) in inspect.getmembers(b, predicate=inspect.ismethod): + if method_name == function.__name__: + is_client_method = True + break + + if not is_client_method: + print(f"disassemble: function {function.__name__} is not a Baml function") + return + + print(f"----- function {function.__name__} -----") + __runtime__.disassemble(function.__name__) \ No newline at end of file diff --git a/backend/baml_client/stream_types.py b/backend/baml_client/stream_types.py new file mode 100644 index 0000000000..2032f01469 --- /dev/null +++ b/backend/baml_client/stream_types.py @@ -0,0 +1,94 @@ +# ---------------------------------------------------------------------------- +# +# Welcome to Baml! To use this generated code, please run the following: +# +# $ pip install baml +# +# ---------------------------------------------------------------------------- + +# This file was generated by BAML: please do not edit it. Instead, edit the +# BAML files and re-generate this code using: baml-cli generate +# baml-cli is available with the baml package. + +import typing +import typing_extensions +from pydantic import BaseModel, ConfigDict, Field + +import baml_py + +from . import types + +StreamStateValueT = typing.TypeVar('StreamStateValueT') +class StreamState(BaseModel, typing.Generic[StreamStateValueT]): + value: StreamStateValueT + state: typing_extensions.Literal["Pending", "Incomplete", "Complete"] +# ######################################################################### +# Generated classes (14) +# ######################################################################### + +class ArticleInput(BaseModel): + url: typing.Optional[str] = None + title: typing.Optional[str] = None + source: typing.Optional[str] = None + snippet: typing.Optional[str] = Field(default=None, description='First ~200 chars of the article content, if any') + trust: typing.Optional[str] = Field(default=None, description='"high" | "medium" | "low" - source trust tag') + +class CategorizeOnlyResult(BaseModel): + categories: typing.List[types.ArticleCategory] = Field(description='1-2 categories') + +class ClassifyKindResult(BaseModel): + kind: typing.Optional[types.ArticleKind] = None + +class DedupMatch(BaseModel): + url: typing.Optional[str] = Field(default=None, description='URL of the new article') + existingUrl: typing.Optional[str] = Field(default=None, description='URL of the existing article it duplicates') + +class ExistingArticle(BaseModel): + url: typing.Optional[str] = None + title: typing.Optional[str] = None + source: typing.Optional[str] = None + +class ExtractedLink(BaseModel): + title: typing.Optional[str] = None + url: typing.Optional[str] = None + snippet: typing.Optional[str] = Field(default=None, description='One-sentence description of the article') + +class NewsletterProduct(BaseModel): + name: typing.Optional[str] = Field(default=None, description='Exact product / tool / model / launch name') + description: typing.Optional[str] = Field(default=None, description='Concise phrase: what it is and does, usable verbatim as a web search query') + +class ProductLinkChoice(BaseModel): + index: typing.Optional[int] = Field(default=None, description='1-based index of the best first-party result, or 0 if none qualifies') + confidence: typing.Optional[float] = Field(default=None, description='0.0 - 1.0') + +class ProfileInput(BaseModel): + handle: typing.Optional[str] = Field(default=None, description='Substack owner handle, echoed back in the verdict') + name: typing.Optional[str] = Field(default=None, description='Publication name') + description: typing.Optional[str] = Field(default=None, description='Publication hero text and/or author bio, if known') + +class ProfileVerdict(BaseModel): + handle: typing.Optional[str] = Field(default=None, description='Must exactly match the input handle') + isAiRelated: typing.Optional[bool] = None + confidence: typing.Optional[int] = Field(default=None, description='0-100 confidence that AI/ML/LLMs is the PRIMARY focus') + +class ScoredArticle(BaseModel): + url: typing.Optional[str] = None + score: typing.Optional[int] = Field(default=None, description='1-100 developer-actionability rating') + +class SearchCandidate(BaseModel): + title: typing.Optional[str] = None + url: typing.Optional[str] = None + snippet: typing.Optional[str] = None + +class SummarizeAndCategorizeResult(BaseModel): + summary: typing.Optional[str] = Field(default=None, description='2-3 short factual lines separated by \\n') + categories: typing.List[types.ArticleCategory] = Field(description='1-2 categories') + kind: typing.Optional[types.ArticleKind] = None + +class TitleFix(BaseModel): + url: typing.Optional[str] = Field(default=None, description='The exact URL from the matching input article - copy verbatim') + title: typing.Optional[str] = Field(default=None, description='Plain title text only. No surrounding quotes. No leading source name or bracket tag. Max 12 words. Return the input title verbatim if it is already clear, specific, and informative.') + +# ######################################################################### +# Generated type aliases (0) +# ######################################################################### diff --git a/backend/baml_client/sync_client.py b/backend/baml_client/sync_client.py new file mode 100644 index 0000000000..0654247051 --- /dev/null +++ b/backend/baml_client/sync_client.py @@ -0,0 +1,564 @@ +# ---------------------------------------------------------------------------- +# +# Welcome to Baml! To use this generated code, please run the following: +# +# $ pip install baml +# +# ---------------------------------------------------------------------------- + +# This file was generated by BAML: please do not edit it. Instead, edit the +# BAML files and re-generate this code using: baml-cli generate +# baml-cli is available with the baml package. + +import typing +import typing_extensions +import baml_py + +from . import stream_types, types, type_builder +from .parser import LlmResponseParser, LlmStreamParser +from .runtime import DoNotUseDirectlyCallManager, BamlCallOptions +from .globals import DO_NOT_USE_DIRECTLY_UNLESS_YOU_KNOW_WHAT_YOURE_DOING_RUNTIME as __runtime__ + +class BamlSyncClient: + __options: DoNotUseDirectlyCallManager + __stream_client: "BamlStreamClient" + __http_request: "BamlHttpRequestClient" + __http_stream_request: "BamlHttpStreamRequestClient" + __llm_response_parser: LlmResponseParser + __llm_stream_parser: LlmStreamParser + + def __init__(self, options: DoNotUseDirectlyCallManager): + self.__options = options + self.__stream_client = BamlStreamClient(options) + self.__http_request = BamlHttpRequestClient(options) + self.__http_stream_request = BamlHttpStreamRequestClient(options) + self.__llm_response_parser = LlmResponseParser(options) + self.__llm_stream_parser = LlmStreamParser(options) + + def __getstate__(self): + # Return state needed for pickling + return {"options": self.__options} + + def __setstate__(self, state): + # Restore state from pickling + self.__options = state["options"] + self.__stream_client = BamlStreamClient(self.__options) + self.__http_request = BamlHttpRequestClient(self.__options) + self.__http_stream_request = BamlHttpStreamRequestClient(self.__options) + self.__llm_response_parser = LlmResponseParser(self.__options) + self.__llm_stream_parser = LlmStreamParser(self.__options) + + def with_options(self, + tb: typing.Optional[type_builder.TypeBuilder] = None, + client_registry: typing.Optional[baml_py.baml_py.ClientRegistry] = None, + client: typing.Optional[str] = None, + collector: typing.Optional[typing.Union[baml_py.baml_py.Collector, typing.List[baml_py.baml_py.Collector]]] = None, + env: typing.Optional[typing.Dict[str, typing.Optional[str]]] = None, + tags: typing.Optional[typing.Dict[str, str]] = None, + on_tick: typing.Optional[typing.Callable[[str, baml_py.baml_py.FunctionLog], None]] = None, + ) -> "BamlSyncClient": + options: BamlCallOptions = {} + if tb is not None: + options["tb"] = tb + if client_registry is not None: + options["client_registry"] = client_registry + if client is not None: + options["client"] = client + if collector is not None: + options["collector"] = collector + if env is not None: + options["env"] = env + if tags is not None: + options["tags"] = tags + if on_tick is not None: + options["on_tick"] = on_tick + return BamlSyncClient(self.__options.merge_options(options)) + + @property + def stream(self): + return self.__stream_client + + @property + def request(self): + return self.__http_request + + @property + def stream_request(self): + return self.__http_stream_request + + @property + def parse(self): + return self.__llm_response_parser + + @property + def parse_stream(self): + return self.__llm_stream_parser + + def CategorizeOnly(self, title: str, + baml_options: BamlCallOptions = {}, + ) -> types.CategorizeOnlyResult: + # Check if on_tick is provided + if 'on_tick' in baml_options: + __stream__ = self.stream.CategorizeOnly(title=title, + baml_options=baml_options) + return __stream__.get_final_response() + else: + # Original non-streaming code + __result__ = self.__options.merge_options(baml_options).call_function_sync(function_name="CategorizeOnly", args={ + "title": title, + }) + return typing.cast(types.CategorizeOnlyResult, __result__.cast_to(types, types, stream_types, False, __runtime__)) + def ClassifyKind(self, title: str,url: str,summary: typing.Optional[str] = None, + baml_options: BamlCallOptions = {}, + ) -> types.ClassifyKindResult: + # Check if on_tick is provided + if 'on_tick' in baml_options: + __stream__ = self.stream.ClassifyKind(title=title,url=url,summary=summary, + baml_options=baml_options) + return __stream__.get_final_response() + else: + # Original non-streaming code + __result__ = self.__options.merge_options(baml_options).call_function_sync(function_name="ClassifyKind", args={ + "title": title,"url": url,"summary": summary, + }) + return typing.cast(types.ClassifyKindResult, __result__.cast_to(types, types, stream_types, False, __runtime__)) + def ClassifyProfiles(self, profiles: typing.List["types.ProfileInput"], + baml_options: BamlCallOptions = {}, + ) -> typing.List["types.ProfileVerdict"]: + # Check if on_tick is provided + if 'on_tick' in baml_options: + __stream__ = self.stream.ClassifyProfiles(profiles=profiles, + baml_options=baml_options) + return __stream__.get_final_response() + else: + # Original non-streaming code + __result__ = self.__options.merge_options(baml_options).call_function_sync(function_name="ClassifyProfiles", args={ + "profiles": profiles, + }) + return typing.cast(typing.List["types.ProfileVerdict"], __result__.cast_to(types, types, stream_types, False, __runtime__)) + def ExtractLinks(self, emailHtml: str, + baml_options: BamlCallOptions = {}, + ) -> typing.List["types.ExtractedLink"]: + # Check if on_tick is provided + if 'on_tick' in baml_options: + __stream__ = self.stream.ExtractLinks(emailHtml=emailHtml, + baml_options=baml_options) + return __stream__.get_final_response() + else: + # Original non-streaming code + __result__ = self.__options.merge_options(baml_options).call_function_sync(function_name="ExtractLinks", args={ + "emailHtml": emailHtml, + }) + return typing.cast(typing.List["types.ExtractedLink"], __result__.cast_to(types, types, stream_types, False, __runtime__)) + def ExtractProducts(self, newsletterText: str, + baml_options: BamlCallOptions = {}, + ) -> typing.List["types.NewsletterProduct"]: + # Check if on_tick is provided + if 'on_tick' in baml_options: + __stream__ = self.stream.ExtractProducts(newsletterText=newsletterText, + baml_options=baml_options) + return __stream__.get_final_response() + else: + # Original non-streaming code + __result__ = self.__options.merge_options(baml_options).call_function_sync(function_name="ExtractProducts", args={ + "newsletterText": newsletterText, + }) + return typing.cast(typing.List["types.NewsletterProduct"], __result__.cast_to(types, types, stream_types, False, __runtime__)) + def ImproveTitles(self, articles: typing.List["types.ArticleInput"], + baml_options: BamlCallOptions = {}, + ) -> typing.List["types.TitleFix"]: + # Check if on_tick is provided + if 'on_tick' in baml_options: + __stream__ = self.stream.ImproveTitles(articles=articles, + baml_options=baml_options) + return __stream__.get_final_response() + else: + # Original non-streaming code + __result__ = self.__options.merge_options(baml_options).call_function_sync(function_name="ImproveTitles", args={ + "articles": articles, + }) + return typing.cast(typing.List["types.TitleFix"], __result__.cast_to(types, types, stream_types, False, __runtime__)) + def ScoreArticles(self, articles: typing.List["types.ArticleInput"], + baml_options: BamlCallOptions = {}, + ) -> typing.List["types.ScoredArticle"]: + # Check if on_tick is provided + if 'on_tick' in baml_options: + __stream__ = self.stream.ScoreArticles(articles=articles, + baml_options=baml_options) + return __stream__.get_final_response() + else: + # Original non-streaming code + __result__ = self.__options.merge_options(baml_options).call_function_sync(function_name="ScoreArticles", args={ + "articles": articles, + }) + return typing.cast(typing.List["types.ScoredArticle"], __result__.cast_to(types, types, stream_types, False, __runtime__)) + def SelectNotableProducts(self, products: typing.List["types.NewsletterProduct"], + baml_options: BamlCallOptions = {}, + ) -> typing.List[int]: + # Check if on_tick is provided + if 'on_tick' in baml_options: + __stream__ = self.stream.SelectNotableProducts(products=products, + baml_options=baml_options) + return __stream__.get_final_response() + else: + # Original non-streaming code + __result__ = self.__options.merge_options(baml_options).call_function_sync(function_name="SelectNotableProducts", args={ + "products": products, + }) + return typing.cast(typing.List[int], __result__.cast_to(types, types, stream_types, False, __runtime__)) + def SelectProductLink(self, productName: str,productDescription: str,candidates: typing.List["types.SearchCandidate"], + baml_options: BamlCallOptions = {}, + ) -> types.ProductLinkChoice: + # Check if on_tick is provided + if 'on_tick' in baml_options: + __stream__ = self.stream.SelectProductLink(productName=productName,productDescription=productDescription,candidates=candidates, + baml_options=baml_options) + return __stream__.get_final_response() + else: + # Original non-streaming code + __result__ = self.__options.merge_options(baml_options).call_function_sync(function_name="SelectProductLink", args={ + "productName": productName,"productDescription": productDescription,"candidates": candidates, + }) + return typing.cast(types.ProductLinkChoice, __result__.cast_to(types, types, stream_types, False, __runtime__)) + def SemanticDedup(self, newArticles: typing.List["types.ArticleInput"],existingArticles: typing.List["types.ExistingArticle"], + baml_options: BamlCallOptions = {}, + ) -> typing.List["types.DedupMatch"]: + # Check if on_tick is provided + if 'on_tick' in baml_options: + __stream__ = self.stream.SemanticDedup(newArticles=newArticles,existingArticles=existingArticles, + baml_options=baml_options) + return __stream__.get_final_response() + else: + # Original non-streaming code + __result__ = self.__options.merge_options(baml_options).call_function_sync(function_name="SemanticDedup", args={ + "newArticles": newArticles,"existingArticles": existingArticles, + }) + return typing.cast(typing.List["types.DedupMatch"], __result__.cast_to(types, types, stream_types, False, __runtime__)) + def SummarizeAndCategorize(self, title: str,content: str, + baml_options: BamlCallOptions = {}, + ) -> types.SummarizeAndCategorizeResult: + # Check if on_tick is provided + if 'on_tick' in baml_options: + __stream__ = self.stream.SummarizeAndCategorize(title=title,content=content, + baml_options=baml_options) + return __stream__.get_final_response() + else: + # Original non-streaming code + __result__ = self.__options.merge_options(baml_options).call_function_sync(function_name="SummarizeAndCategorize", args={ + "title": title,"content": content, + }) + return typing.cast(types.SummarizeAndCategorizeResult, __result__.cast_to(types, types, stream_types, False, __runtime__)) + + + +class BamlStreamClient: + __options: DoNotUseDirectlyCallManager + + def __init__(self, options: DoNotUseDirectlyCallManager): + self.__options = options + + def CategorizeOnly(self, title: str, + baml_options: BamlCallOptions = {}, + ) -> baml_py.BamlSyncStream[stream_types.CategorizeOnlyResult, types.CategorizeOnlyResult]: + __ctx__, __result__ = self.__options.merge_options(baml_options).create_sync_stream(function_name="CategorizeOnly", args={ + "title": title, + }) + return baml_py.BamlSyncStream[stream_types.CategorizeOnlyResult, types.CategorizeOnlyResult]( + __result__, + lambda x: typing.cast(stream_types.CategorizeOnlyResult, x.cast_to(types, types, stream_types, True, __runtime__)), + lambda x: typing.cast(types.CategorizeOnlyResult, x.cast_to(types, types, stream_types, False, __runtime__)), + __ctx__, + ) + def ClassifyKind(self, title: str,url: str,summary: typing.Optional[str] = None, + baml_options: BamlCallOptions = {}, + ) -> baml_py.BamlSyncStream[stream_types.ClassifyKindResult, types.ClassifyKindResult]: + __ctx__, __result__ = self.__options.merge_options(baml_options).create_sync_stream(function_name="ClassifyKind", args={ + "title": title,"url": url,"summary": summary, + }) + return baml_py.BamlSyncStream[stream_types.ClassifyKindResult, types.ClassifyKindResult]( + __result__, + lambda x: typing.cast(stream_types.ClassifyKindResult, x.cast_to(types, types, stream_types, True, __runtime__)), + lambda x: typing.cast(types.ClassifyKindResult, x.cast_to(types, types, stream_types, False, __runtime__)), + __ctx__, + ) + def ClassifyProfiles(self, profiles: typing.List["types.ProfileInput"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.BamlSyncStream[typing.List["stream_types.ProfileVerdict"], typing.List["types.ProfileVerdict"]]: + __ctx__, __result__ = self.__options.merge_options(baml_options).create_sync_stream(function_name="ClassifyProfiles", args={ + "profiles": profiles, + }) + return baml_py.BamlSyncStream[typing.List["stream_types.ProfileVerdict"], typing.List["types.ProfileVerdict"]]( + __result__, + lambda x: typing.cast(typing.List["stream_types.ProfileVerdict"], x.cast_to(types, types, stream_types, True, __runtime__)), + lambda x: typing.cast(typing.List["types.ProfileVerdict"], x.cast_to(types, types, stream_types, False, __runtime__)), + __ctx__, + ) + def ExtractLinks(self, emailHtml: str, + baml_options: BamlCallOptions = {}, + ) -> baml_py.BamlSyncStream[typing.List["stream_types.ExtractedLink"], typing.List["types.ExtractedLink"]]: + __ctx__, __result__ = self.__options.merge_options(baml_options).create_sync_stream(function_name="ExtractLinks", args={ + "emailHtml": emailHtml, + }) + return baml_py.BamlSyncStream[typing.List["stream_types.ExtractedLink"], typing.List["types.ExtractedLink"]]( + __result__, + lambda x: typing.cast(typing.List["stream_types.ExtractedLink"], x.cast_to(types, types, stream_types, True, __runtime__)), + lambda x: typing.cast(typing.List["types.ExtractedLink"], x.cast_to(types, types, stream_types, False, __runtime__)), + __ctx__, + ) + def ExtractProducts(self, newsletterText: str, + baml_options: BamlCallOptions = {}, + ) -> baml_py.BamlSyncStream[typing.List["stream_types.NewsletterProduct"], typing.List["types.NewsletterProduct"]]: + __ctx__, __result__ = self.__options.merge_options(baml_options).create_sync_stream(function_name="ExtractProducts", args={ + "newsletterText": newsletterText, + }) + return baml_py.BamlSyncStream[typing.List["stream_types.NewsletterProduct"], typing.List["types.NewsletterProduct"]]( + __result__, + lambda x: typing.cast(typing.List["stream_types.NewsletterProduct"], x.cast_to(types, types, stream_types, True, __runtime__)), + lambda x: typing.cast(typing.List["types.NewsletterProduct"], x.cast_to(types, types, stream_types, False, __runtime__)), + __ctx__, + ) + def ImproveTitles(self, articles: typing.List["types.ArticleInput"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.BamlSyncStream[typing.List["stream_types.TitleFix"], typing.List["types.TitleFix"]]: + __ctx__, __result__ = self.__options.merge_options(baml_options).create_sync_stream(function_name="ImproveTitles", args={ + "articles": articles, + }) + return baml_py.BamlSyncStream[typing.List["stream_types.TitleFix"], typing.List["types.TitleFix"]]( + __result__, + lambda x: typing.cast(typing.List["stream_types.TitleFix"], x.cast_to(types, types, stream_types, True, __runtime__)), + lambda x: typing.cast(typing.List["types.TitleFix"], x.cast_to(types, types, stream_types, False, __runtime__)), + __ctx__, + ) + def ScoreArticles(self, articles: typing.List["types.ArticleInput"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.BamlSyncStream[typing.List["stream_types.ScoredArticle"], typing.List["types.ScoredArticle"]]: + __ctx__, __result__ = self.__options.merge_options(baml_options).create_sync_stream(function_name="ScoreArticles", args={ + "articles": articles, + }) + return baml_py.BamlSyncStream[typing.List["stream_types.ScoredArticle"], typing.List["types.ScoredArticle"]]( + __result__, + lambda x: typing.cast(typing.List["stream_types.ScoredArticle"], x.cast_to(types, types, stream_types, True, __runtime__)), + lambda x: typing.cast(typing.List["types.ScoredArticle"], x.cast_to(types, types, stream_types, False, __runtime__)), + __ctx__, + ) + def SelectNotableProducts(self, products: typing.List["types.NewsletterProduct"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.BamlSyncStream[typing.List[int], typing.List[int]]: + __ctx__, __result__ = self.__options.merge_options(baml_options).create_sync_stream(function_name="SelectNotableProducts", args={ + "products": products, + }) + return baml_py.BamlSyncStream[typing.List[int], typing.List[int]]( + __result__, + lambda x: typing.cast(typing.List[int], x.cast_to(types, types, stream_types, True, __runtime__)), + lambda x: typing.cast(typing.List[int], x.cast_to(types, types, stream_types, False, __runtime__)), + __ctx__, + ) + def SelectProductLink(self, productName: str,productDescription: str,candidates: typing.List["types.SearchCandidate"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.BamlSyncStream[stream_types.ProductLinkChoice, types.ProductLinkChoice]: + __ctx__, __result__ = self.__options.merge_options(baml_options).create_sync_stream(function_name="SelectProductLink", args={ + "productName": productName,"productDescription": productDescription,"candidates": candidates, + }) + return baml_py.BamlSyncStream[stream_types.ProductLinkChoice, types.ProductLinkChoice]( + __result__, + lambda x: typing.cast(stream_types.ProductLinkChoice, x.cast_to(types, types, stream_types, True, __runtime__)), + lambda x: typing.cast(types.ProductLinkChoice, x.cast_to(types, types, stream_types, False, __runtime__)), + __ctx__, + ) + def SemanticDedup(self, newArticles: typing.List["types.ArticleInput"],existingArticles: typing.List["types.ExistingArticle"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.BamlSyncStream[typing.List["stream_types.DedupMatch"], typing.List["types.DedupMatch"]]: + __ctx__, __result__ = self.__options.merge_options(baml_options).create_sync_stream(function_name="SemanticDedup", args={ + "newArticles": newArticles,"existingArticles": existingArticles, + }) + return baml_py.BamlSyncStream[typing.List["stream_types.DedupMatch"], typing.List["types.DedupMatch"]]( + __result__, + lambda x: typing.cast(typing.List["stream_types.DedupMatch"], x.cast_to(types, types, stream_types, True, __runtime__)), + lambda x: typing.cast(typing.List["types.DedupMatch"], x.cast_to(types, types, stream_types, False, __runtime__)), + __ctx__, + ) + def SummarizeAndCategorize(self, title: str,content: str, + baml_options: BamlCallOptions = {}, + ) -> baml_py.BamlSyncStream[stream_types.SummarizeAndCategorizeResult, types.SummarizeAndCategorizeResult]: + __ctx__, __result__ = self.__options.merge_options(baml_options).create_sync_stream(function_name="SummarizeAndCategorize", args={ + "title": title,"content": content, + }) + return baml_py.BamlSyncStream[stream_types.SummarizeAndCategorizeResult, types.SummarizeAndCategorizeResult]( + __result__, + lambda x: typing.cast(stream_types.SummarizeAndCategorizeResult, x.cast_to(types, types, stream_types, True, __runtime__)), + lambda x: typing.cast(types.SummarizeAndCategorizeResult, x.cast_to(types, types, stream_types, False, __runtime__)), + __ctx__, + ) + + +class BamlHttpRequestClient: + __options: DoNotUseDirectlyCallManager + + def __init__(self, options: DoNotUseDirectlyCallManager): + self.__options = options + + def CategorizeOnly(self, title: str, + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = self.__options.merge_options(baml_options).create_http_request_sync(function_name="CategorizeOnly", args={ + "title": title, + }, mode="request") + return __result__ + def ClassifyKind(self, title: str,url: str,summary: typing.Optional[str] = None, + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = self.__options.merge_options(baml_options).create_http_request_sync(function_name="ClassifyKind", args={ + "title": title,"url": url,"summary": summary, + }, mode="request") + return __result__ + def ClassifyProfiles(self, profiles: typing.List["types.ProfileInput"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = self.__options.merge_options(baml_options).create_http_request_sync(function_name="ClassifyProfiles", args={ + "profiles": profiles, + }, mode="request") + return __result__ + def ExtractLinks(self, emailHtml: str, + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = self.__options.merge_options(baml_options).create_http_request_sync(function_name="ExtractLinks", args={ + "emailHtml": emailHtml, + }, mode="request") + return __result__ + def ExtractProducts(self, newsletterText: str, + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = self.__options.merge_options(baml_options).create_http_request_sync(function_name="ExtractProducts", args={ + "newsletterText": newsletterText, + }, mode="request") + return __result__ + def ImproveTitles(self, articles: typing.List["types.ArticleInput"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = self.__options.merge_options(baml_options).create_http_request_sync(function_name="ImproveTitles", args={ + "articles": articles, + }, mode="request") + return __result__ + def ScoreArticles(self, articles: typing.List["types.ArticleInput"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = self.__options.merge_options(baml_options).create_http_request_sync(function_name="ScoreArticles", args={ + "articles": articles, + }, mode="request") + return __result__ + def SelectNotableProducts(self, products: typing.List["types.NewsletterProduct"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = self.__options.merge_options(baml_options).create_http_request_sync(function_name="SelectNotableProducts", args={ + "products": products, + }, mode="request") + return __result__ + def SelectProductLink(self, productName: str,productDescription: str,candidates: typing.List["types.SearchCandidate"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = self.__options.merge_options(baml_options).create_http_request_sync(function_name="SelectProductLink", args={ + "productName": productName,"productDescription": productDescription,"candidates": candidates, + }, mode="request") + return __result__ + def SemanticDedup(self, newArticles: typing.List["types.ArticleInput"],existingArticles: typing.List["types.ExistingArticle"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = self.__options.merge_options(baml_options).create_http_request_sync(function_name="SemanticDedup", args={ + "newArticles": newArticles,"existingArticles": existingArticles, + }, mode="request") + return __result__ + def SummarizeAndCategorize(self, title: str,content: str, + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = self.__options.merge_options(baml_options).create_http_request_sync(function_name="SummarizeAndCategorize", args={ + "title": title,"content": content, + }, mode="request") + return __result__ + + +class BamlHttpStreamRequestClient: + __options: DoNotUseDirectlyCallManager + + def __init__(self, options: DoNotUseDirectlyCallManager): + self.__options = options + + def CategorizeOnly(self, title: str, + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = self.__options.merge_options(baml_options).create_http_request_sync(function_name="CategorizeOnly", args={ + "title": title, + }, mode="stream") + return __result__ + def ClassifyKind(self, title: str,url: str,summary: typing.Optional[str] = None, + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = self.__options.merge_options(baml_options).create_http_request_sync(function_name="ClassifyKind", args={ + "title": title,"url": url,"summary": summary, + }, mode="stream") + return __result__ + def ClassifyProfiles(self, profiles: typing.List["types.ProfileInput"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = self.__options.merge_options(baml_options).create_http_request_sync(function_name="ClassifyProfiles", args={ + "profiles": profiles, + }, mode="stream") + return __result__ + def ExtractLinks(self, emailHtml: str, + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = self.__options.merge_options(baml_options).create_http_request_sync(function_name="ExtractLinks", args={ + "emailHtml": emailHtml, + }, mode="stream") + return __result__ + def ExtractProducts(self, newsletterText: str, + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = self.__options.merge_options(baml_options).create_http_request_sync(function_name="ExtractProducts", args={ + "newsletterText": newsletterText, + }, mode="stream") + return __result__ + def ImproveTitles(self, articles: typing.List["types.ArticleInput"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = self.__options.merge_options(baml_options).create_http_request_sync(function_name="ImproveTitles", args={ + "articles": articles, + }, mode="stream") + return __result__ + def ScoreArticles(self, articles: typing.List["types.ArticleInput"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = self.__options.merge_options(baml_options).create_http_request_sync(function_name="ScoreArticles", args={ + "articles": articles, + }, mode="stream") + return __result__ + def SelectNotableProducts(self, products: typing.List["types.NewsletterProduct"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = self.__options.merge_options(baml_options).create_http_request_sync(function_name="SelectNotableProducts", args={ + "products": products, + }, mode="stream") + return __result__ + def SelectProductLink(self, productName: str,productDescription: str,candidates: typing.List["types.SearchCandidate"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = self.__options.merge_options(baml_options).create_http_request_sync(function_name="SelectProductLink", args={ + "productName": productName,"productDescription": productDescription,"candidates": candidates, + }, mode="stream") + return __result__ + def SemanticDedup(self, newArticles: typing.List["types.ArticleInput"],existingArticles: typing.List["types.ExistingArticle"], + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = self.__options.merge_options(baml_options).create_http_request_sync(function_name="SemanticDedup", args={ + "newArticles": newArticles,"existingArticles": existingArticles, + }, mode="stream") + return __result__ + def SummarizeAndCategorize(self, title: str,content: str, + baml_options: BamlCallOptions = {}, + ) -> baml_py.baml_py.HTTPRequest: + __result__ = self.__options.merge_options(baml_options).create_http_request_sync(function_name="SummarizeAndCategorize", args={ + "title": title,"content": content, + }, mode="stream") + return __result__ + + +b = BamlSyncClient(DoNotUseDirectlyCallManager({})) \ No newline at end of file diff --git a/backend/baml_client/tracing.py b/backend/baml_client/tracing.py new file mode 100644 index 0000000000..06725593c3 --- /dev/null +++ b/backend/baml_client/tracing.py @@ -0,0 +1,22 @@ +# ---------------------------------------------------------------------------- +# +# Welcome to Baml! To use this generated code, please run the following: +# +# $ pip install baml +# +# ---------------------------------------------------------------------------- + +# This file was generated by BAML: please do not edit it. Instead, edit the +# BAML files and re-generate this code using: baml-cli generate +# baml-cli is available with the baml package. + +from .globals import DO_NOT_USE_DIRECTLY_UNLESS_YOU_KNOW_WHAT_YOURE_DOING_CTX + +trace = DO_NOT_USE_DIRECTLY_UNLESS_YOU_KNOW_WHAT_YOURE_DOING_CTX.trace_fn +set_tags = DO_NOT_USE_DIRECTLY_UNLESS_YOU_KNOW_WHAT_YOURE_DOING_CTX.upsert_tags +def flush(): + DO_NOT_USE_DIRECTLY_UNLESS_YOU_KNOW_WHAT_YOURE_DOING_CTX.flush() +on_log_event = DO_NOT_USE_DIRECTLY_UNLESS_YOU_KNOW_WHAT_YOURE_DOING_CTX.on_log_event + + +__all__ = ['trace', 'set_tags', "flush", "on_log_event"] diff --git a/backend/baml_client/type_builder.py b/backend/baml_client/type_builder.py new file mode 100644 index 0000000000..e52762479a --- /dev/null +++ b/backend/baml_client/type_builder.py @@ -0,0 +1,844 @@ +# ---------------------------------------------------------------------------- +# +# Welcome to Baml! To use this generated code, please run the following: +# +# $ pip install baml +# +# ---------------------------------------------------------------------------- + +# This file was generated by BAML: please do not edit it. Instead, edit the +# BAML files and re-generate this code using: baml-cli generate +# baml-cli is available with the baml package. + +import typing +from baml_py import type_builder +from baml_py import baml_py +# These are exports, not used here, hence the linter is disabled +from baml_py.baml_py import FieldType, EnumValueBuilder, EnumBuilder, ClassBuilder # noqa: F401 # pylint: disable=unused-import +from .globals import DO_NOT_USE_DIRECTLY_UNLESS_YOU_KNOW_WHAT_YOURE_DOING_RUNTIME + +class TypeBuilder(type_builder.TypeBuilder): + def __init__(self): + super().__init__(classes=set( + ["ArticleInput","CategorizeOnlyResult","ClassifyKindResult","DedupMatch","ExistingArticle","ExtractedLink","NewsletterProduct","ProductLinkChoice","ProfileInput","ProfileVerdict","ScoredArticle","SearchCandidate","SummarizeAndCategorizeResult","TitleFix",] + ), enums=set( + ["ArticleCategory","ArticleKind",] + ), runtime=DO_NOT_USE_DIRECTLY_UNLESS_YOU_KNOW_WHAT_YOURE_DOING_RUNTIME) + + # ######################################################################### + # Generated enums 2 + # ######################################################################### + + @property + def ArticleCategory(self) -> "ArticleCategoryViewer": + return ArticleCategoryViewer(self) + + @property + def ArticleKind(self) -> "ArticleKindViewer": + return ArticleKindViewer(self) + + + # ######################################################################### + # Generated classes 14 + # ######################################################################### + + @property + def ArticleInput(self) -> "ArticleInputViewer": + return ArticleInputViewer(self) + + @property + def CategorizeOnlyResult(self) -> "CategorizeOnlyResultViewer": + return CategorizeOnlyResultViewer(self) + + @property + def ClassifyKindResult(self) -> "ClassifyKindResultViewer": + return ClassifyKindResultViewer(self) + + @property + def DedupMatch(self) -> "DedupMatchViewer": + return DedupMatchViewer(self) + + @property + def ExistingArticle(self) -> "ExistingArticleViewer": + return ExistingArticleViewer(self) + + @property + def ExtractedLink(self) -> "ExtractedLinkViewer": + return ExtractedLinkViewer(self) + + @property + def NewsletterProduct(self) -> "NewsletterProductViewer": + return NewsletterProductViewer(self) + + @property + def ProductLinkChoice(self) -> "ProductLinkChoiceViewer": + return ProductLinkChoiceViewer(self) + + @property + def ProfileInput(self) -> "ProfileInputViewer": + return ProfileInputViewer(self) + + @property + def ProfileVerdict(self) -> "ProfileVerdictViewer": + return ProfileVerdictViewer(self) + + @property + def ScoredArticle(self) -> "ScoredArticleViewer": + return ScoredArticleViewer(self) + + @property + def SearchCandidate(self) -> "SearchCandidateViewer": + return SearchCandidateViewer(self) + + @property + def SummarizeAndCategorizeResult(self) -> "SummarizeAndCategorizeResultViewer": + return SummarizeAndCategorizeResultViewer(self) + + @property + def TitleFix(self) -> "TitleFixViewer": + return TitleFixViewer(self) + + + +# ######################################################################### +# Generated enums 2 +# ######################################################################### + +class ArticleCategoryAst: + def __init__(self, tb: type_builder.TypeBuilder): + _tb = tb._tb # type: ignore (we know how to use this private attribute) + self._bldr = _tb.enum("ArticleCategory") + self._values: typing.Set[str] = set([ "Models", "Dev", "Research", ]) + self._vals = ArticleCategoryValues(self._bldr, self._values) + + def type(self) -> baml_py.FieldType: + return self._bldr.field() + + @property + def values(self) -> "ArticleCategoryValues": + return self._vals + + +class ArticleCategoryViewer(ArticleCategoryAst): + def __init__(self, tb: type_builder.TypeBuilder): + super().__init__(tb) + + + def list_values(self) -> typing.List[typing.Tuple[str, type_builder.EnumValueViewer]]: + return [(name, type_builder.EnumValueViewer(self._bldr.value(name))) for name in self._values] + + +class ArticleCategoryValues: + def __init__(self, enum_bldr: baml_py.EnumBuilder, values: typing.Set[str]): + self.__bldr = enum_bldr + self.__values = values # type: ignore (we know how to use this private attribute) # noqa: F821 + + + + @property + def Models(self) -> type_builder.EnumValueViewer: + return type_builder.EnumValueViewer(self.__bldr.value("Models")) + + @property + def Dev(self) -> type_builder.EnumValueViewer: + return type_builder.EnumValueViewer(self.__bldr.value("Dev")) + + @property + def Research(self) -> type_builder.EnumValueViewer: + return type_builder.EnumValueViewer(self.__bldr.value("Research")) + + + + +class ArticleKindAst: + def __init__(self, tb: type_builder.TypeBuilder): + _tb = tb._tb # type: ignore (we know how to use this private attribute) + self._bldr = _tb.enum("ArticleKind") + self._values: typing.Set[str] = set([ "Repo", "Paper", "Model", "Blog", "Product", "Announcement", ]) + self._vals = ArticleKindValues(self._bldr, self._values) + + def type(self) -> baml_py.FieldType: + return self._bldr.field() + + @property + def values(self) -> "ArticleKindValues": + return self._vals + + +class ArticleKindViewer(ArticleKindAst): + def __init__(self, tb: type_builder.TypeBuilder): + super().__init__(tb) + + + def list_values(self) -> typing.List[typing.Tuple[str, type_builder.EnumValueViewer]]: + return [(name, type_builder.EnumValueViewer(self._bldr.value(name))) for name in self._values] + + +class ArticleKindValues: + def __init__(self, enum_bldr: baml_py.EnumBuilder, values: typing.Set[str]): + self.__bldr = enum_bldr + self.__values = values # type: ignore (we know how to use this private attribute) # noqa: F821 + + + + @property + def Repo(self) -> type_builder.EnumValueViewer: + return type_builder.EnumValueViewer(self.__bldr.value("Repo")) + + @property + def Paper(self) -> type_builder.EnumValueViewer: + return type_builder.EnumValueViewer(self.__bldr.value("Paper")) + + @property + def Model(self) -> type_builder.EnumValueViewer: + return type_builder.EnumValueViewer(self.__bldr.value("Model")) + + @property + def Blog(self) -> type_builder.EnumValueViewer: + return type_builder.EnumValueViewer(self.__bldr.value("Blog")) + + @property + def Product(self) -> type_builder.EnumValueViewer: + return type_builder.EnumValueViewer(self.__bldr.value("Product")) + + @property + def Announcement(self) -> type_builder.EnumValueViewer: + return type_builder.EnumValueViewer(self.__bldr.value("Announcement")) + + + + + +# ######################################################################### +# Generated classes 14 +# ######################################################################### + +class ArticleInputAst: + def __init__(self, tb: type_builder.TypeBuilder): + _tb = tb._tb # type: ignore (we know how to use this private attribute) + self._bldr = _tb.class_("ArticleInput") + self._properties: typing.Set[str] = set([ "url", "title", "source", "snippet", "trust", ]) + self._props = ArticleInputProperties(self._bldr, self._properties) + + def type(self) -> baml_py.FieldType: + return self._bldr.field() + + @property + def props(self) -> "ArticleInputProperties": + return self._props + + +class ArticleInputViewer(ArticleInputAst): + def __init__(self, tb: type_builder.TypeBuilder): + super().__init__(tb) + + + def list_properties(self) -> typing.List[typing.Tuple[str, type_builder.ClassPropertyViewer]]: + return [(name, type_builder.ClassPropertyViewer(self._bldr.property(name))) for name in self._properties] + + + +class ArticleInputProperties: + def __init__(self, bldr: baml_py.ClassBuilder, properties: typing.Set[str]): + self.__bldr = bldr + self.__properties = properties # type: ignore (we know how to use this private attribute) # noqa: F821 + + + + @property + def url(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("url")) + + @property + def title(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("title")) + + @property + def source(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("source")) + + @property + def snippet(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("snippet")) + + @property + def trust(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("trust")) + + + + +class CategorizeOnlyResultAst: + def __init__(self, tb: type_builder.TypeBuilder): + _tb = tb._tb # type: ignore (we know how to use this private attribute) + self._bldr = _tb.class_("CategorizeOnlyResult") + self._properties: typing.Set[str] = set([ "categories", ]) + self._props = CategorizeOnlyResultProperties(self._bldr, self._properties) + + def type(self) -> baml_py.FieldType: + return self._bldr.field() + + @property + def props(self) -> "CategorizeOnlyResultProperties": + return self._props + + +class CategorizeOnlyResultViewer(CategorizeOnlyResultAst): + def __init__(self, tb: type_builder.TypeBuilder): + super().__init__(tb) + + + def list_properties(self) -> typing.List[typing.Tuple[str, type_builder.ClassPropertyViewer]]: + return [(name, type_builder.ClassPropertyViewer(self._bldr.property(name))) for name in self._properties] + + + +class CategorizeOnlyResultProperties: + def __init__(self, bldr: baml_py.ClassBuilder, properties: typing.Set[str]): + self.__bldr = bldr + self.__properties = properties # type: ignore (we know how to use this private attribute) # noqa: F821 + + + + @property + def categories(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("categories")) + + + + +class ClassifyKindResultAst: + def __init__(self, tb: type_builder.TypeBuilder): + _tb = tb._tb # type: ignore (we know how to use this private attribute) + self._bldr = _tb.class_("ClassifyKindResult") + self._properties: typing.Set[str] = set([ "kind", ]) + self._props = ClassifyKindResultProperties(self._bldr, self._properties) + + def type(self) -> baml_py.FieldType: + return self._bldr.field() + + @property + def props(self) -> "ClassifyKindResultProperties": + return self._props + + +class ClassifyKindResultViewer(ClassifyKindResultAst): + def __init__(self, tb: type_builder.TypeBuilder): + super().__init__(tb) + + + def list_properties(self) -> typing.List[typing.Tuple[str, type_builder.ClassPropertyViewer]]: + return [(name, type_builder.ClassPropertyViewer(self._bldr.property(name))) for name in self._properties] + + + +class ClassifyKindResultProperties: + def __init__(self, bldr: baml_py.ClassBuilder, properties: typing.Set[str]): + self.__bldr = bldr + self.__properties = properties # type: ignore (we know how to use this private attribute) # noqa: F821 + + + + @property + def kind(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("kind")) + + + + +class DedupMatchAst: + def __init__(self, tb: type_builder.TypeBuilder): + _tb = tb._tb # type: ignore (we know how to use this private attribute) + self._bldr = _tb.class_("DedupMatch") + self._properties: typing.Set[str] = set([ "url", "existingUrl", ]) + self._props = DedupMatchProperties(self._bldr, self._properties) + + def type(self) -> baml_py.FieldType: + return self._bldr.field() + + @property + def props(self) -> "DedupMatchProperties": + return self._props + + +class DedupMatchViewer(DedupMatchAst): + def __init__(self, tb: type_builder.TypeBuilder): + super().__init__(tb) + + + def list_properties(self) -> typing.List[typing.Tuple[str, type_builder.ClassPropertyViewer]]: + return [(name, type_builder.ClassPropertyViewer(self._bldr.property(name))) for name in self._properties] + + + +class DedupMatchProperties: + def __init__(self, bldr: baml_py.ClassBuilder, properties: typing.Set[str]): + self.__bldr = bldr + self.__properties = properties # type: ignore (we know how to use this private attribute) # noqa: F821 + + + + @property + def url(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("url")) + + @property + def existingUrl(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("existingUrl")) + + + + +class ExistingArticleAst: + def __init__(self, tb: type_builder.TypeBuilder): + _tb = tb._tb # type: ignore (we know how to use this private attribute) + self._bldr = _tb.class_("ExistingArticle") + self._properties: typing.Set[str] = set([ "url", "title", "source", ]) + self._props = ExistingArticleProperties(self._bldr, self._properties) + + def type(self) -> baml_py.FieldType: + return self._bldr.field() + + @property + def props(self) -> "ExistingArticleProperties": + return self._props + + +class ExistingArticleViewer(ExistingArticleAst): + def __init__(self, tb: type_builder.TypeBuilder): + super().__init__(tb) + + + def list_properties(self) -> typing.List[typing.Tuple[str, type_builder.ClassPropertyViewer]]: + return [(name, type_builder.ClassPropertyViewer(self._bldr.property(name))) for name in self._properties] + + + +class ExistingArticleProperties: + def __init__(self, bldr: baml_py.ClassBuilder, properties: typing.Set[str]): + self.__bldr = bldr + self.__properties = properties # type: ignore (we know how to use this private attribute) # noqa: F821 + + + + @property + def url(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("url")) + + @property + def title(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("title")) + + @property + def source(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("source")) + + + + +class ExtractedLinkAst: + def __init__(self, tb: type_builder.TypeBuilder): + _tb = tb._tb # type: ignore (we know how to use this private attribute) + self._bldr = _tb.class_("ExtractedLink") + self._properties: typing.Set[str] = set([ "title", "url", "snippet", ]) + self._props = ExtractedLinkProperties(self._bldr, self._properties) + + def type(self) -> baml_py.FieldType: + return self._bldr.field() + + @property + def props(self) -> "ExtractedLinkProperties": + return self._props + + +class ExtractedLinkViewer(ExtractedLinkAst): + def __init__(self, tb: type_builder.TypeBuilder): + super().__init__(tb) + + + def list_properties(self) -> typing.List[typing.Tuple[str, type_builder.ClassPropertyViewer]]: + return [(name, type_builder.ClassPropertyViewer(self._bldr.property(name))) for name in self._properties] + + + +class ExtractedLinkProperties: + def __init__(self, bldr: baml_py.ClassBuilder, properties: typing.Set[str]): + self.__bldr = bldr + self.__properties = properties # type: ignore (we know how to use this private attribute) # noqa: F821 + + + + @property + def title(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("title")) + + @property + def url(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("url")) + + @property + def snippet(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("snippet")) + + + + +class NewsletterProductAst: + def __init__(self, tb: type_builder.TypeBuilder): + _tb = tb._tb # type: ignore (we know how to use this private attribute) + self._bldr = _tb.class_("NewsletterProduct") + self._properties: typing.Set[str] = set([ "name", "description", ]) + self._props = NewsletterProductProperties(self._bldr, self._properties) + + def type(self) -> baml_py.FieldType: + return self._bldr.field() + + @property + def props(self) -> "NewsletterProductProperties": + return self._props + + +class NewsletterProductViewer(NewsletterProductAst): + def __init__(self, tb: type_builder.TypeBuilder): + super().__init__(tb) + + + def list_properties(self) -> typing.List[typing.Tuple[str, type_builder.ClassPropertyViewer]]: + return [(name, type_builder.ClassPropertyViewer(self._bldr.property(name))) for name in self._properties] + + + +class NewsletterProductProperties: + def __init__(self, bldr: baml_py.ClassBuilder, properties: typing.Set[str]): + self.__bldr = bldr + self.__properties = properties # type: ignore (we know how to use this private attribute) # noqa: F821 + + + + @property + def name(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("name")) + + @property + def description(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("description")) + + + + +class ProductLinkChoiceAst: + def __init__(self, tb: type_builder.TypeBuilder): + _tb = tb._tb # type: ignore (we know how to use this private attribute) + self._bldr = _tb.class_("ProductLinkChoice") + self._properties: typing.Set[str] = set([ "index", "confidence", ]) + self._props = ProductLinkChoiceProperties(self._bldr, self._properties) + + def type(self) -> baml_py.FieldType: + return self._bldr.field() + + @property + def props(self) -> "ProductLinkChoiceProperties": + return self._props + + +class ProductLinkChoiceViewer(ProductLinkChoiceAst): + def __init__(self, tb: type_builder.TypeBuilder): + super().__init__(tb) + + + def list_properties(self) -> typing.List[typing.Tuple[str, type_builder.ClassPropertyViewer]]: + return [(name, type_builder.ClassPropertyViewer(self._bldr.property(name))) for name in self._properties] + + + +class ProductLinkChoiceProperties: + def __init__(self, bldr: baml_py.ClassBuilder, properties: typing.Set[str]): + self.__bldr = bldr + self.__properties = properties # type: ignore (we know how to use this private attribute) # noqa: F821 + + + + @property + def index(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("index")) + + @property + def confidence(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("confidence")) + + + + +class ProfileInputAst: + def __init__(self, tb: type_builder.TypeBuilder): + _tb = tb._tb # type: ignore (we know how to use this private attribute) + self._bldr = _tb.class_("ProfileInput") + self._properties: typing.Set[str] = set([ "handle", "name", "description", ]) + self._props = ProfileInputProperties(self._bldr, self._properties) + + def type(self) -> baml_py.FieldType: + return self._bldr.field() + + @property + def props(self) -> "ProfileInputProperties": + return self._props + + +class ProfileInputViewer(ProfileInputAst): + def __init__(self, tb: type_builder.TypeBuilder): + super().__init__(tb) + + + def list_properties(self) -> typing.List[typing.Tuple[str, type_builder.ClassPropertyViewer]]: + return [(name, type_builder.ClassPropertyViewer(self._bldr.property(name))) for name in self._properties] + + + +class ProfileInputProperties: + def __init__(self, bldr: baml_py.ClassBuilder, properties: typing.Set[str]): + self.__bldr = bldr + self.__properties = properties # type: ignore (we know how to use this private attribute) # noqa: F821 + + + + @property + def handle(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("handle")) + + @property + def name(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("name")) + + @property + def description(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("description")) + + + + +class ProfileVerdictAst: + def __init__(self, tb: type_builder.TypeBuilder): + _tb = tb._tb # type: ignore (we know how to use this private attribute) + self._bldr = _tb.class_("ProfileVerdict") + self._properties: typing.Set[str] = set([ "handle", "isAiRelated", "confidence", ]) + self._props = ProfileVerdictProperties(self._bldr, self._properties) + + def type(self) -> baml_py.FieldType: + return self._bldr.field() + + @property + def props(self) -> "ProfileVerdictProperties": + return self._props + + +class ProfileVerdictViewer(ProfileVerdictAst): + def __init__(self, tb: type_builder.TypeBuilder): + super().__init__(tb) + + + def list_properties(self) -> typing.List[typing.Tuple[str, type_builder.ClassPropertyViewer]]: + return [(name, type_builder.ClassPropertyViewer(self._bldr.property(name))) for name in self._properties] + + + +class ProfileVerdictProperties: + def __init__(self, bldr: baml_py.ClassBuilder, properties: typing.Set[str]): + self.__bldr = bldr + self.__properties = properties # type: ignore (we know how to use this private attribute) # noqa: F821 + + + + @property + def handle(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("handle")) + + @property + def isAiRelated(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("isAiRelated")) + + @property + def confidence(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("confidence")) + + + + +class ScoredArticleAst: + def __init__(self, tb: type_builder.TypeBuilder): + _tb = tb._tb # type: ignore (we know how to use this private attribute) + self._bldr = _tb.class_("ScoredArticle") + self._properties: typing.Set[str] = set([ "url", "score", ]) + self._props = ScoredArticleProperties(self._bldr, self._properties) + + def type(self) -> baml_py.FieldType: + return self._bldr.field() + + @property + def props(self) -> "ScoredArticleProperties": + return self._props + + +class ScoredArticleViewer(ScoredArticleAst): + def __init__(self, tb: type_builder.TypeBuilder): + super().__init__(tb) + + + def list_properties(self) -> typing.List[typing.Tuple[str, type_builder.ClassPropertyViewer]]: + return [(name, type_builder.ClassPropertyViewer(self._bldr.property(name))) for name in self._properties] + + + +class ScoredArticleProperties: + def __init__(self, bldr: baml_py.ClassBuilder, properties: typing.Set[str]): + self.__bldr = bldr + self.__properties = properties # type: ignore (we know how to use this private attribute) # noqa: F821 + + + + @property + def url(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("url")) + + @property + def score(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("score")) + + + + +class SearchCandidateAst: + def __init__(self, tb: type_builder.TypeBuilder): + _tb = tb._tb # type: ignore (we know how to use this private attribute) + self._bldr = _tb.class_("SearchCandidate") + self._properties: typing.Set[str] = set([ "title", "url", "snippet", ]) + self._props = SearchCandidateProperties(self._bldr, self._properties) + + def type(self) -> baml_py.FieldType: + return self._bldr.field() + + @property + def props(self) -> "SearchCandidateProperties": + return self._props + + +class SearchCandidateViewer(SearchCandidateAst): + def __init__(self, tb: type_builder.TypeBuilder): + super().__init__(tb) + + + def list_properties(self) -> typing.List[typing.Tuple[str, type_builder.ClassPropertyViewer]]: + return [(name, type_builder.ClassPropertyViewer(self._bldr.property(name))) for name in self._properties] + + + +class SearchCandidateProperties: + def __init__(self, bldr: baml_py.ClassBuilder, properties: typing.Set[str]): + self.__bldr = bldr + self.__properties = properties # type: ignore (we know how to use this private attribute) # noqa: F821 + + + + @property + def title(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("title")) + + @property + def url(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("url")) + + @property + def snippet(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("snippet")) + + + + +class SummarizeAndCategorizeResultAst: + def __init__(self, tb: type_builder.TypeBuilder): + _tb = tb._tb # type: ignore (we know how to use this private attribute) + self._bldr = _tb.class_("SummarizeAndCategorizeResult") + self._properties: typing.Set[str] = set([ "summary", "categories", "kind", ]) + self._props = SummarizeAndCategorizeResultProperties(self._bldr, self._properties) + + def type(self) -> baml_py.FieldType: + return self._bldr.field() + + @property + def props(self) -> "SummarizeAndCategorizeResultProperties": + return self._props + + +class SummarizeAndCategorizeResultViewer(SummarizeAndCategorizeResultAst): + def __init__(self, tb: type_builder.TypeBuilder): + super().__init__(tb) + + + def list_properties(self) -> typing.List[typing.Tuple[str, type_builder.ClassPropertyViewer]]: + return [(name, type_builder.ClassPropertyViewer(self._bldr.property(name))) for name in self._properties] + + + +class SummarizeAndCategorizeResultProperties: + def __init__(self, bldr: baml_py.ClassBuilder, properties: typing.Set[str]): + self.__bldr = bldr + self.__properties = properties # type: ignore (we know how to use this private attribute) # noqa: F821 + + + + @property + def summary(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("summary")) + + @property + def categories(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("categories")) + + @property + def kind(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("kind")) + + + + +class TitleFixAst: + def __init__(self, tb: type_builder.TypeBuilder): + _tb = tb._tb # type: ignore (we know how to use this private attribute) + self._bldr = _tb.class_("TitleFix") + self._properties: typing.Set[str] = set([ "url", "title", ]) + self._props = TitleFixProperties(self._bldr, self._properties) + + def type(self) -> baml_py.FieldType: + return self._bldr.field() + + @property + def props(self) -> "TitleFixProperties": + return self._props + + +class TitleFixViewer(TitleFixAst): + def __init__(self, tb: type_builder.TypeBuilder): + super().__init__(tb) + + + def list_properties(self) -> typing.List[typing.Tuple[str, type_builder.ClassPropertyViewer]]: + return [(name, type_builder.ClassPropertyViewer(self._bldr.property(name))) for name in self._properties] + + + +class TitleFixProperties: + def __init__(self, bldr: baml_py.ClassBuilder, properties: typing.Set[str]): + self.__bldr = bldr + self.__properties = properties # type: ignore (we know how to use this private attribute) # noqa: F821 + + + + @property + def url(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("url")) + + @property + def title(self) -> type_builder.ClassPropertyViewer: + return type_builder.ClassPropertyViewer(self.__bldr.property("title")) + + + diff --git a/backend/baml_client/type_map.py b/backend/baml_client/type_map.py new file mode 100644 index 0000000000..72cf02e092 --- /dev/null +++ b/backend/baml_client/type_map.py @@ -0,0 +1,66 @@ +# ---------------------------------------------------------------------------- +# +# Welcome to Baml! To use this generated code, please run the following: +# +# $ pip install baml +# +# ---------------------------------------------------------------------------- + +# This file was generated by BAML: please do not edit it. Instead, edit the +# BAML files and re-generate this code using: baml-cli generate +# baml-cli is available with the baml package. + +from . import types +from . import stream_types + + +type_map = { + + "types.ArticleInput": types.ArticleInput, + "stream_types.ArticleInput": stream_types.ArticleInput, + + "types.CategorizeOnlyResult": types.CategorizeOnlyResult, + "stream_types.CategorizeOnlyResult": stream_types.CategorizeOnlyResult, + + "types.ClassifyKindResult": types.ClassifyKindResult, + "stream_types.ClassifyKindResult": stream_types.ClassifyKindResult, + + "types.DedupMatch": types.DedupMatch, + "stream_types.DedupMatch": stream_types.DedupMatch, + + "types.ExistingArticle": types.ExistingArticle, + "stream_types.ExistingArticle": stream_types.ExistingArticle, + + "types.ExtractedLink": types.ExtractedLink, + "stream_types.ExtractedLink": stream_types.ExtractedLink, + + "types.NewsletterProduct": types.NewsletterProduct, + "stream_types.NewsletterProduct": stream_types.NewsletterProduct, + + "types.ProductLinkChoice": types.ProductLinkChoice, + "stream_types.ProductLinkChoice": stream_types.ProductLinkChoice, + + "types.ProfileInput": types.ProfileInput, + "stream_types.ProfileInput": stream_types.ProfileInput, + + "types.ProfileVerdict": types.ProfileVerdict, + "stream_types.ProfileVerdict": stream_types.ProfileVerdict, + + "types.ScoredArticle": types.ScoredArticle, + "stream_types.ScoredArticle": stream_types.ScoredArticle, + + "types.SearchCandidate": types.SearchCandidate, + "stream_types.SearchCandidate": stream_types.SearchCandidate, + + "types.SummarizeAndCategorizeResult": types.SummarizeAndCategorizeResult, + "stream_types.SummarizeAndCategorizeResult": stream_types.SummarizeAndCategorizeResult, + + "types.TitleFix": types.TitleFix, + "stream_types.TitleFix": stream_types.TitleFix, + + + "types.ArticleCategory": types.ArticleCategory, + + "types.ArticleKind": types.ArticleKind, + +} \ No newline at end of file diff --git a/backend/baml_client/types.py b/backend/baml_client/types.py new file mode 100644 index 0000000000..2886b228b7 --- /dev/null +++ b/backend/baml_client/types.py @@ -0,0 +1,125 @@ +# ---------------------------------------------------------------------------- +# +# Welcome to Baml! To use this generated code, please run the following: +# +# $ pip install baml +# +# ---------------------------------------------------------------------------- + +# This file was generated by BAML: please do not edit it. Instead, edit the +# BAML files and re-generate this code using: baml-cli generate +# baml-cli is available with the baml package. + +import typing +import typing_extensions +from enum import Enum + + +from pydantic import BaseModel, ConfigDict, Field + + +import baml_py + +CheckT = typing_extensions.TypeVar('CheckT') +CheckName = typing_extensions.TypeVar('CheckName', bound=str) + +class Check(BaseModel): + name: str + expression: str + status: str +class Checked(BaseModel, typing.Generic[CheckT, CheckName]): + value: CheckT + checks: typing.Dict[CheckName, Check] + +def get_checks(checks: typing.Dict[CheckName, Check]) -> typing.List[Check]: + return list(checks.values()) + +def all_succeeded(checks: typing.Dict[CheckName, Check]) -> bool: + return all(check.status == "succeeded" for check in get_checks(checks)) +# ######################################################################### +# Generated enums (2) +# ######################################################################### + +class ArticleCategory(str, Enum): + Models = "Models" + Dev = "Dev" + Research = "Research" + +class ArticleKind(str, Enum): + Repo = "Repo" + Paper = "Paper" + Model = "Model" + Blog = "Blog" + Product = "Product" + Announcement = "Announcement" + +# ######################################################################### +# Generated classes (14) +# ######################################################################### + +class ArticleInput(BaseModel): + url: str + title: str + source: str + snippet: typing.Optional[str] = Field(default=None, description='First ~200 chars of the article content, if any') + trust: typing.Optional[str] = Field(default=None, description='"high" | "medium" | "low" - source trust tag') + +class CategorizeOnlyResult(BaseModel): + categories: typing.List[ArticleCategory] = Field(description='1-2 categories') + +class ClassifyKindResult(BaseModel): + kind: ArticleKind + +class DedupMatch(BaseModel): + url: str = Field(description='URL of the new article') + existingUrl: str = Field(description='URL of the existing article it duplicates') + +class ExistingArticle(BaseModel): + url: str + title: str + source: str + +class ExtractedLink(BaseModel): + title: str + url: str + snippet: str = Field(description='One-sentence description of the article') + +class NewsletterProduct(BaseModel): + name: str = Field(description='Exact product / tool / model / launch name') + description: str = Field(description='Concise phrase: what it is and does, usable verbatim as a web search query') + +class ProductLinkChoice(BaseModel): + index: int = Field(description='1-based index of the best first-party result, or 0 if none qualifies') + confidence: float = Field(description='0.0 - 1.0') + +class ProfileInput(BaseModel): + handle: str = Field(description='Substack owner handle, echoed back in the verdict') + name: str = Field(description='Publication name') + description: typing.Optional[str] = Field(default=None, description='Publication hero text and/or author bio, if known') + +class ProfileVerdict(BaseModel): + handle: str = Field(description='Must exactly match the input handle') + isAiRelated: bool + confidence: int = Field(description='0-100 confidence that AI/ML/LLMs is the PRIMARY focus') + +class ScoredArticle(BaseModel): + url: str + score: int = Field(description='1-100 developer-actionability rating') + +class SearchCandidate(BaseModel): + title: str + url: str + snippet: str + +class SummarizeAndCategorizeResult(BaseModel): + summary: str = Field(description='2-3 short factual lines separated by \\n') + categories: typing.List[ArticleCategory] = Field(description='1-2 categories') + kind: ArticleKind + +class TitleFix(BaseModel): + url: str = Field(description='The exact URL from the matching input article - copy verbatim') + title: str = Field(description='Plain title text only. No surrounding quotes. No leading source name or bracket tag. Max 12 words. Return the input title verbatim if it is already clear, specific, and informative.') + +# ######################################################################### +# Generated type aliases (0) +# ######################################################################### diff --git a/backend/baml_client/watchers.py b/backend/baml_client/watchers.py new file mode 100644 index 0000000000..347146f66a --- /dev/null +++ b/backend/baml_client/watchers.py @@ -0,0 +1,44 @@ +# ---------------------------------------------------------------------------- +# +# Welcome to Baml! To use this generated code, please run the following: +# +# $ pip install baml +# +# ---------------------------------------------------------------------------- + +# This file was generated by BAML: please do not edit it. Instead, edit the +# BAML files and re-generate this code using: baml-cli generate +# baml-cli is available with the baml package. + +from typing import Callable, Any, Protocol, Generic, TypeVar, overload, Literal +import threading + +T = TypeVar("T") + +class BlockEvent: + def __init__(self, block_label: str, event_type: str): + self.block_label = block_label + self.event_type = event_type # "enter" | "exit" + +class VarEvent(Generic[T]): + def __init__(self, variable_name: str, value: T, timestamp: str, function_name: str): + self.variable_name = variable_name + self.value = value + self.timestamp = timestamp + self.function_name = function_name + +BlockHandler = Callable[[BlockEvent], None] +VarEventHandler = Callable[[VarEvent[T]], None] +StreamHandler = Callable[[Any], None] # Stream will be an async iterator + +class InternalEventBindings(Protocol): + function_name: str + block: list[BlockHandler] + vars: dict[str, list[VarEventHandler[Any]]] + streams: dict[str, list[StreamHandler]] + functions: dict[str, "InternalEventBindings"] + +class EventCollectorInternal(Protocol): + def __handlers__(self) -> InternalEventBindings: + ... + diff --git a/backend/pipeline/__init__.py b/backend/pipeline/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/backend/pipeline/crontab b/backend/pipeline/crontab new file mode 100644 index 0000000000..4130b59070 --- /dev/null +++ b/backend/pipeline/crontab @@ -0,0 +1 @@ +0 4 * * * cd /app/backend && python -m pipeline.run diff --git a/backend/pipeline/run.py b/backend/pipeline/run.py new file mode 100644 index 0000000000..883a230022 --- /dev/null +++ b/backend/pipeline/run.py @@ -0,0 +1,459 @@ +"""Pipeline entry point. Run with: python -m pipeline.run""" + +from __future__ import annotations + +import os +import sys +import time +from datetime import UTC, datetime, timedelta + +from model2vec import StaticModel +from sqlmodel import Session, create_engine, select + +from app.models_agentique import Article, ScoredUrl +from baml_client import b +from baml_client.types import ArticleInput, ExistingArticle +from pipeline.sources.ainews import fetch_ai_news +from pipeline.sources.extract_content import re_extract_full_content +from pipeline.sources.hn import fetch_hn +from pipeline.sources.substack import fetch_substack +from pipeline.steps import ( + PROMPT_CONTENT_CAP, + SCORE_THRESHOLD, + TRUST_BY_SOURCE, + github_repo_from_content, + kind_from_url, +) +from pipeline.utils import log, sanitize_llm_text, strip_title_wrappers, wait_ms + + +def _build_db_url() -> str: + server = os.environ["POSTGRES_SERVER"] + port = os.environ.get("POSTGRES_PORT", "5432") + user = os.environ["POSTGRES_USER"] + password = os.environ.get("POSTGRES_PASSWORD", "") + db = os.environ.get("POSTGRES_DB", "") + return f"postgresql+psycopg://{user}:{password}@{server}:{port}/{db}" + + +_engine = create_engine(_build_db_url()) + +_model: StaticModel | None = None + + +def _get_model() -> StaticModel: + global _model + if _model is None: + _model = StaticModel.from_pretrained("minishlab/potion-base-8M") + return _model + + +def _embed(text: str) -> list[float]: + return _get_model().encode([text])[0].tolist() + + +SOURCES = [ + {"label": "Hacker News", "fetcher": fetch_hn}, + {"label": "AI News", "fetcher": fetch_ai_news}, + {"label": "Substack", "fetcher": fetch_substack}, +] + + +def _to_baml_input(a: dict) -> ArticleInput: + """Build a BAML ArticleInput from a fetched-article dict (snippet capped at 200).""" + return ArticleInput( + url=a["url"], + title=a["title"], + source=a["source"], + snippet=a.get("content", "")[:200] if a.get("content") else None, + trust=TRUST_BY_SOURCE.get(a["source"]), + ) + + +def run_pipeline() -> None: + log("=== Pipeline start ===") + start = time.time() + + with Session(_engine) as session: + for src in SOURCES: + log(f"\n=== Processing {src['label']} ===") + + fetched = _fetch_source(src["fetcher"], src["label"]) + fresh = _filter_known_urls(session, fetched, src["label"]) + alive = _filter_dead_domains(fresh, src["label"]) + unique = _dedup_semantic(session, alive, src["label"]) + scored = _score_articles(session, unique) + inserted = _insert_articles(session, scored) + _improve_titles(session, inserted) + with_content = _extract_full_content(session, inserted) + processed = _summarize_and_categorize(session, with_content) + _embed_articles(session, processed) + + elapsed = f"{time.time() - start:.1f}" + log(f"=== Pipeline complete in {elapsed}s ===") + + +# ─── Step 01 ──────────────────────────────────────────────────────────────── + + +def _fetch_source(fetcher, label: str) -> list[dict]: + articles = fetcher() + if not articles: + log(f"No articles from {label}") + return articles + + +# ─── Step 02 ──────────────────────────────────────────────────────────────── + + +def _filter_known_urls( + session: Session, articles: list[dict], label: str +) -> list[dict]: + if not articles: + return [] + all_urls = [a["url"] for a in articles] + + existing_urls = set( + session.exec(select(Article.url).where(Article.url.in_(all_urls))).all() + ) + scored_urls = set( + session.exec(select(ScoredUrl.url).where(ScoredUrl.url.in_(all_urls))).all() + ) + + fresh = [ + a + for a in articles + if a["url"] not in existing_urls and a["url"] not in scored_urls + ] + + if existing_urls or scored_urls: + log( + f" Filtered {len(existing_urls)} known + {len(scored_urls)} already-scored URLs" + ) + if not fresh: + log(f" No new articles from {label}") + return [] + log(f" {len(fresh)} new articles to process") + return fresh + + +# ─── Step 02b ─────────────────────────────────────────────────────────────── + + +def _filter_dead_domains(articles: list[dict], label: str) -> list[dict]: + if not articles: + return articles + + from urllib.parse import urlparse + + import dns.resolver + + def is_resolvable(url: str) -> bool: + try: + host = urlparse(url).hostname + if not host: + return False + dns.resolver.resolve(host, "A") + return True + except dns.resolver.NXDOMAIN: + return False + except Exception: + return True # Other errors (timeout, etc.) - assume alive + + results = [(a, is_resolvable(a["url"])) for a in articles] + alive = [a for a, ok in results if ok] + dead = [a for a, ok in results if not ok] + for a in dead: + log(f" Dropped dead URL: {a['url']}") + if dead: + log(f" Filtered {len(dead)} dead-domain URLs from {label}") + return alive + + +# ─── Step 03 ──────────────────────────────────────────────────────────────── + + +def _dedup_semantic(session: Session, articles: list[dict], label: str) -> list[dict]: + if not articles: + return articles + + cutoff = datetime.now(UTC) - timedelta(days=14) + recent_db = session.exec( + select(Article).where(Article.published_at >= cutoff) + ).all() + + if not recent_db: + return articles + + log(f" Deduplicating against {len(recent_db)} recent DB articles...") + + new_inputs = [_to_baml_input(a) for a in articles] + existing_inputs = [ + ExistingArticle(url=str(art.url), title=art.title, source=art.source) + for art in recent_db + ] + + try: + matches = b.SemanticDedup(new_inputs, existing_inputs) + merged_urls = {m.url for m in matches} + for m in matches: + log(f" Dropped duplicate: {m.url} (matches existing: {m.existingUrl})") + if merged_urls: + log(f" {len(merged_urls)} articles dropped as duplicates") + unique = [a for a in articles if a["url"] not in merged_urls] + if not unique: + log(f" No new unique articles from {label}") + return unique + except Exception as e: + log(f" Dedup failed, continuing without: {e}") + return articles + + +# ─── Step 04 ──────────────────────────────────────────────────────────────── + + +def _score_articles(session: Session, articles: list[dict]) -> list[dict]: + if not articles: + return [] + + log(f" Scoring {len(articles)} articles in batches of 5...") + + BATCH = 5 + all_scores: list[dict] = [] + for i in range(0, len(articles), BATCH): + batch_inputs = [_to_baml_input(a) for a in articles[i : i + BATCH]] + result = b.ScoreArticles(batch_inputs) + all_scores.extend({"url": r.url, "score": r.score} for r in result) + log(f" batch {i // BATCH + 1}/{(len(articles) + BATCH - 1) // BATCH} done") + wait_ms(1000) + + score_by_url = {s["url"]: s["score"] for s in all_scores} + scored = [] + for a in articles: + score = score_by_url.get(a["url"], 0) + if a["source"] == "Ben's Bites": + score = min(score + 10, 100) + scored.append({**a, "score": score}) + + scored.sort(key=lambda x: x["score"], reverse=True) + kept = [s for s in scored if s["score"] >= SCORE_THRESHOLD] + log(f" {len(kept)} articles pass scoring (threshold: {SCORE_THRESHOLD})") + + # Record ALL evaluated URLs (including sub-threshold) + for a in articles: + session.merge(ScoredUrl(url=a["url"])) + session.commit() + + return kept + + +# ─── Step 05 ──────────────────────────────────────────────────────────────── + + +def _insert_articles(session: Session, scored: list[dict]) -> list[dict]: + if not scored: + return [] + + by_url: dict[str, dict] = {} + for item in scored: + existing = by_url.get(item["url"]) + if not existing or item["score"] > existing["score"]: + by_url[item["url"]] = item + + inserted = [] + for item in by_url.values(): + item["title"] = sanitize_llm_text(item["title"]) + pub_at = None + if item.get("published_date"): + try: + from email.utils import parsedate_to_datetime + + try: + pub_at = parsedate_to_datetime(item["published_date"]) + except Exception: + pub_at = datetime.fromisoformat( + item["published_date"].replace("Z", "+00:00") + ) + except Exception: + pass + + article = Article( + title=item["title"], + source=item["source"], + source_type=item["source_type"], + url=item["url"], + published_at=pub_at, + score=item["score"], + content=item.get("content") or "", + ) + session.add(article) + session.flush() + assert article.id is not None + log(f" Inserted #{article.id}: [{item['score']}/100] {item['title']}") + inserted.append({**item, "id": article.id}) + + session.commit() + return inserted + + +# ─── Step 06 ──────────────────────────────────────────────────────────────── + + +def _improve_titles(session: Session, inserted: list[dict]) -> None: + if not inserted: + return + + log(f" Improving {len(inserted)} titles...") + + for item in inserted: + art_id = item["id"] + try: + fixes = b.ImproveTitles([_to_baml_input(item)]) + raw = fixes[0].title if fixes else None + if not raw: + continue + sanitized = sanitize_llm_text(strip_title_wrappers(raw)) + if not sanitized or sanitized == item["title"]: + continue + if item["source"].lower() in sanitized.lower(): + log(f' Skip rewrite #{art_id} (source name leaked): "{sanitized}"') + continue + old_title = item["title"] + article = session.get(Article, art_id) + if article: + article.title = sanitized + session.add(article) + session.commit() + item["title"] = sanitized + log(f' Improved title #{art_id}: "{old_title}" → "{sanitized}"') + except Exception as e: + log(f" Title improve failed for #{art_id}, continuing: {e}") + + +# ─── Step 07 ──────────────────────────────────────────────────────────────── + + +def _extract_full_content(session: Session, inserted: list[dict]) -> list[dict]: + if not inserted: + return [] + + to_extract = [a for a in inserted if a["source_type"] not in ("aiNews", "rss")] + content_map = re_extract_full_content([{"url": a["url"]} for a in to_extract]) + + for item in to_extract: + full = content_map.get(item["url"]) + if full: + article = session.get(Article, item["id"]) + if article: + article.content = full + session.add(article) + session.commit() + + result = [] + for item in inserted: + if item["source_type"] in ("aiNews", "rss"): + result.append({**item, "full_content": item.get("content", "")}) + else: + result.append({**item, "full_content": content_map.get(item["url"], "")}) + return result + + +# ─── Step 08 ──────────────────────────────────────────────────────────────── + + +def _summarize_and_categorize(session: Session, items: list[dict]) -> list[dict]: + if not items: + return [] + + log(f" Summarizing and categorizing {len(items)} articles...") + processed = [] + + for item in items: + art_id = item["id"] + full_content = item.get("full_content", "") + summary = "" + categories: list[str] = [] + kind: str | None = kind_from_url(item["url"]) + + try: + if full_content: + result = b.SummarizeAndCategorize( + item["title"], full_content[:PROMPT_CONTENT_CAP] + ) + summary = sanitize_llm_text(result.summary or "") + categories = [c.lower() for c in result.categories] + if not kind: + kind = result.kind.value.lower() + if kind == "blog" and github_repo_from_content(full_content): + kind = "repo" + else: + result = b.CategorizeOnly(item["title"]) + categories = [c.lower() for c in result.categories] + if not kind: + kr = b.ClassifyKind(item["title"], item["url"], None) + kind = kr.kind.value.lower() + except Exception as e: + log(f" Summarize/categorize failed for #{art_id}: {e}") + + article = session.get(Article, art_id) + if article: + article.summary = summary + article.categories = categories + if kind: + article.kind = kind + session.add(article) + + processed.append( + { + "id": art_id, + "url": item["url"], + "title": item["title"], + "score": item["score"], + "summary": summary, + "categories": categories, + } + ) + + session.commit() + log(" Done summarizing and categorizing") + return processed + + +# ─── Step 09 ──────────────────────────────────────────────────────────────── + + +def _embed_articles(session: Session, items: list[dict]) -> None: + if not items: + return + + log(f" Embedding {len(items)} articles...") + + for item in items: + art_id = item["id"] + try: + text = ( + f"{item['title']}\n\n{item['summary']}" + if item.get("summary") + else item["title"] + ) + vec = _embed(text) + article = session.get(Article, art_id) + if article: + article.embedding = vec + session.add(article) + except Exception as e: + log(f" Embed failed for #{art_id}: {e}") + + session.commit() + + +# ─── CLI ──────────────────────────────────────────────────────────────────── + +if __name__ == "__main__": + try: + run_pipeline() + sys.exit(0) + except Exception as e: + print(f"Pipeline failed: {e}", file=sys.stderr) + raise + sys.exit(1) diff --git a/backend/pipeline/sources/__init__.py b/backend/pipeline/sources/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/backend/pipeline/sources/ainews.py b/backend/pipeline/sources/ainews.py new file mode 100644 index 0000000000..91e845902e --- /dev/null +++ b/backend/pipeline/sources/ainews.py @@ -0,0 +1,264 @@ +"""AI News source - extracts sub-stories from the news.smol.ai RSS feed.""" + +from __future__ import annotations + +import re +from html import unescape + +from pipeline.sources.utils import fetch_with_timeout, is_within_window +from pipeline.utils import log + +FEED_URL = "https://news.smol.ai/rss.xml" +MAX_CONTENT_LENGTH = 1400 +MIN_REDDIT_BODY_LENGTH = 120 +MIN_TWITTER_TITLE_LENGTH = 10 + + +# --- minimal RSS parsing (no feedparser dep for this source) --- + + +def _pick_tag(block: str, tag: str) -> str: + match = re.search(rf"<{tag}>([\s\S]*?)", block) + if not match: + return "" + val = match.group(1) + cdata = re.match(r"^$", val) + return cdata.group(1) if cdata else val + + +def _parse_feed(xml: str) -> list[dict]: + items = [] + for chunk in xml.split("")[1:]: + body = chunk.split("")[0] + items.append( + { + "title": _pick_tag(body, "title"), + "link": _pick_tag(body, "link"), + "content_html": unescape(_pick_tag(body, "content:encoded")), + "pub_date": _pick_tag(body, "pubDate"), + } + ) + return items + + +# --- HTML helpers --- + + +def _strip_tags(html: str) -> str: + return re.sub(r"\s+", " ", re.sub(r"<[^>]+>", " ", html)).strip() + + +def _first_bold(html: str) -> str: + m = re.search(r"]*>([\s\S]*?)", html) + return _strip_tags(m.group(1)) if m else "" + + +def _host_of(url: str) -> str: + try: + from urllib.parse import urlparse + + return urlparse(url).hostname.removeprefix("www.") + except Exception: + return "" + + +def _collect_links(html: str) -> list[dict]: + return [ + { + "url": m.group(1), + "host": _host_of(m.group(1)), + "text": _strip_tags(m.group(2)), + } + for m in re.finditer(r']+href="([^"]+)"[^>]*>([\s\S]*?)', html) + ] + + +def _slice_section(html: str, heading_rx: re.Pattern) -> str: + start = heading_rx.search(html) + if not start: + return "" + after = html[start.end() :] + next_h1 = re.search(r"]*>", after, re.IGNORECASE) + return after[: next_h1.start()] if next_h1 else after + + +BLOG_HOST_RX = re.compile( + r"\b(openai|anthropic|deepmind|google|meta|microsoft|nvidia|mistral|unsloth|" + r"databricks|cohere|stability|perplexity|vercel|modal|together|replicate|groq)\b" +) + +PRIMARY_PRIORITY = ["github", "huggingface", "arxiv", "blog", "reddit", "tweet"] + +_JUNK_HOSTS = { + "news.smol.ai", + "latent.space", + "support.substack.com", + "i.redd.it", + "preview.redd.it", +} + + +def _classify_host(host: str) -> str | None: + if host in ("github.com",) or host.endswith(".github.io"): + return "github" + if host in ("huggingface.co", "hf.co"): + return "huggingface" + if host in ("arxiv.org", "ar5iv.labs.arxiv.org"): + return "arxiv" + if ( + BLOG_HOST_RX.search(host) + or host.endswith(".ai") + or host.endswith(".dev") + or "substack.com" in host + ): + return "blog" + if host in ("reddit.com",) or host.endswith(".reddit.com"): + return "reddit" + if host in ("x.com", "twitter.com"): + return "tweet" + return None + + +def _is_junk(link: dict) -> bool: + if not link["url"]: + return True + if link["host"] in _JUNK_HOSTS: + return True + if "twitter.com/i/lists/" in link["url"] or "x.com/i/" in link["url"]: + return True + return False + + +def _pick_primary(links: list[dict]) -> dict: + clean = [lnk for lnk in links if not _is_junk(lnk)] + if not clean: + return {"url": "", "kind": "other"} + for kind in PRIMARY_PRIORITY: + hit = next((lnk for lnk in clean if _classify_host(lnk["host"]) == kind), None) + if hit: + return {"url": hit["url"], "kind": kind} + return {"url": clean[0]["url"], "kind": "other"} + + +# --- Twitter Recap --- + + +def _extract_twitter_recap(html: str) -> dict | None: + region = _slice_section( + html, re.compile(r"]*>\s*AI Twitter Recap\s*
  • ", re.IGNORECASE) + ) + if not region: + return None + title = _first_bold(region) + if not title or len(title) < MIN_TWITTER_TITLE_LENGTH: + return None + primary = _pick_primary(_collect_links(region)) + if not primary["url"]: + return None + bullets = [ + _strip_tags(m.group(1)) for m in re.finditer(r"
  • ([\s\S]*?)
  • ", region) + ][:3] + content = " ".join(bullets) or _strip_tags(region) + return { + "title": title, + "url": primary["url"], + "content": content[:MAX_CONTENT_LENGTH], + } + + +# --- Reddit Recap --- + +REDDIT_ANCHOR_RX = re.compile( + r']+href="(https?://(?:www\.)?reddit\.com/r/[^"]+/comments/[^"]+)"[^>]*>([\s\S]*?)' +) + + +def _extract_reddit_recap(html: str) -> list[dict]: + region = _slice_section( + html, re.compile(r"]*>\s*AI Reddit Recap\s*", re.IGNORECASE) + ) + if not region: + return [] + + anchors = [ + { + "url": m.group(1), + "title": _strip_tags(m.group(2)), + "start": m.start(), + "end": m.end(), + } + for m in REDDIT_ANCHOR_RX.finditer(region) + ] + + stories = [] + for i, anchor in enumerate(anchors): + next_start = anchors[i + 1]["start"] if i + 1 < len(anchors) else len(region) + after = region[anchor["end"] :] + heading_rel = re.search(r"]*>", after, re.IGNORECASE) + heading_abs = ( + anchor["end"] + heading_rel.start() if heading_rel else len(region) + ) + body_end = min(next_start, heading_abs) + body = region[anchor["start"] : body_end] + content = _strip_tags(body) + if len(content) < MIN_REDDIT_BODY_LENGTH: + continue + primary = _pick_primary(_collect_links(body)) + stories.append( + { + "title": anchor["title"] or "(untitled)", + "url": primary["url"] or anchor["url"], + "content": content[:MAX_CONTENT_LENGTH], + } + ) + return stories + + +# --- fetch --- + + +def fetch_ai_news() -> list[dict]: + log("Fetching AI News feed...") + try: + resp = fetch_with_timeout(FEED_URL) + if not resp.is_success: + raise ValueError(f"Status {resp.status_code}") + xml = resp.text + except Exception as e: + log(f" AI News fetch FAILED: {e}") + return [] + + items = [it for it in _parse_feed(xml) if is_within_window(it["pub_date"])] + log(f" AI News: {len(items)} issues within window") + + articles: list[dict] = [] + for item in items: + if re.match(r"^not much happened", item["title"], re.IGNORECASE): + continue + twitter = _extract_twitter_recap(item["content_html"]) + if twitter: + articles.append( + { + **twitter, + "published_date": item["pub_date"], + "source": "AI News", + "source_type": "aiNews", + } + ) + for reddit in _extract_reddit_recap(item["content_html"]): + articles.append( + { + **reddit, + "published_date": item["pub_date"], + "source": "AI News", + "source_type": "aiNews", + } + ) + + by_url: dict[str, dict] = {} + for a in articles: + if a["url"] not in by_url: + by_url[a["url"]] = a + + log(f"AI News: {len(by_url)} articles extracted") + return list(by_url.values()) diff --git a/backend/pipeline/sources/extract_content.py b/backend/pipeline/sources/extract_content.py new file mode 100644 index 0000000000..ff2ce21657 --- /dev/null +++ b/backend/pipeline/sources/extract_content.py @@ -0,0 +1,147 @@ +from __future__ import annotations + +import re +from concurrent.futures import ThreadPoolExecutor, as_completed + +import trafilatura + +from pipeline.sources.utils import fetch_with_timeout +from pipeline.utils import log + +SKIP_DOMAINS: set[str] = {"x.com", "twitter.com"} +SNIPPET_MAX_LENGTH = 500 +EXTRACT_TIMEOUT_SECS = 5.0 +CONCURRENCY = 5 + +BLOCKER_PATTERNS: list[re.Pattern] = [ + re.compile(r"something went wrong.*don't fret", re.IGNORECASE | re.DOTALL), + re.compile(r"disable.*privacy\s+extensions", re.IGNORECASE), + re.compile(r"privacy\s+extensions.*and.*retry", re.IGNORECASE), + re.compile(r"please\s+(?:sign|log)\s*in", re.IGNORECASE), + re.compile(r"sign\s*in\s+to\s+(?:continue|read|access)", re.IGNORECASE), + re.compile(r"log\s*in\s+to\s+(?:continue|read|access)", re.IGNORECASE), + re.compile(r"subscribe\s+to\s+(?:continue|read|access|unlock)", re.IGNORECASE), + re.compile( + r"create\s+an?\s+account\s+to\s+(?:continue|read|access)", re.IGNORECASE + ), + re.compile(r"enable\s+javascript\s+to\s+(?:continue|view|use)", re.IGNORECASE), + re.compile(r"javascript\s+is\s+(?:disabled|required)", re.IGNORECASE), + re.compile(r"access\s+denied", re.IGNORECASE), + re.compile(r"403\s+forbidden", re.IGNORECASE), +] + + +def _should_skip(url: str) -> bool: + try: + from urllib.parse import urlparse + + host = urlparse(url).hostname or "" + return any(host == d or host.endswith(f".{d}") for d in SKIP_DOMAINS) + except Exception: + return True + + +def _is_blocker(text: str) -> bool: + if len(text) < 50: + return True + return any(p.search(text) for p in BLOCKER_PATTERNS) + + +def _fetch_html(url: str) -> str: + if _should_skip(url): + return "" + try: + resp = fetch_with_timeout(url, timeout=EXTRACT_TIMEOUT_SECS) + if not resp.is_success: + return "" + ct = resp.headers.get("content-type", "") + if "text/html" not in ct: + return "" + return resp.text + except Exception: + return "" + + +def _extract_text(html: str, max_length: int | None = None) -> str: + if not html: + return "" + text = trafilatura.extract(html, include_comments=False, include_tables=False) or "" + text = re.sub(r"\s+", " ", text).strip() + if not text or _is_blocker(text): + return "" + return text[:max_length] if max_length else text + + +def _extract_one_snippet(url: str) -> tuple[str, str]: + return url, _extract_text(_fetch_html(url), SNIPPET_MAX_LENGTH) + + +def _extract_one_full(url: str, idx: int, total: int) -> tuple[str, str]: + log(f" [{idx + 1}/{total}] Fetching: {url}") + html = _fetch_html(url) + text = _extract_text(html) + log( + f" [{idx + 1}/{total}] {'OK (' + str(len(text)) + ' chars)' if text else 'no content'}: {url}" + ) + return url, text + + +def extract_content(articles: list[dict]) -> list[dict]: + """Fill in missing content snippets for a list of article dicts.""" + needs = [a for a in articles if not a.get("content")] + if not needs: + return articles + + unique_urls = list(dict.fromkeys(a["url"] for a in needs)) + log(f" Extracting content for {len(unique_urls)} URLs...") + + snippet_map: dict[str, str] = {} + with ThreadPoolExecutor(max_workers=CONCURRENCY) as executor: + futures = { + executor.submit(_extract_one_snippet, url): url for url in unique_urls + } + for future in as_completed(futures): + try: + url, text = future.result() + if text: + snippet_map[url] = text + except Exception: + pass + + log(f" Extracted {len(snippet_map)}/{len(unique_urls)} snippets") + + result = [] + for a in articles: + if not a.get("content") and a["url"] in snippet_map: + result.append({**a, "content": snippet_map[a["url"]]}) + else: + result.append(a) + return result + + +def re_extract_full_content(articles: list[dict]) -> dict[str, str]: + """Re-fetch full article text for already-inserted articles. Returns url->text map.""" + if not articles: + return {} + + unique_urls = list(dict.fromkeys(a["url"] for a in articles)) + log(f" Re-extracting full content for {len(unique_urls)} URLs...") + + content_map: dict[str, str] = {} + total = len(unique_urls) + + with ThreadPoolExecutor(max_workers=CONCURRENCY) as executor: + futures = { + executor.submit(_extract_one_full, url, idx, total): url + for idx, url in enumerate(unique_urls) + } + for future in as_completed(futures): + try: + url, text = future.result() + if text: + content_map[url] = text + except Exception: + pass + + log(f" Re-extracted {len(content_map)}/{len(unique_urls)} full texts") + return content_map diff --git a/backend/pipeline/sources/hn.py b/backend/pipeline/sources/hn.py new file mode 100644 index 0000000000..039aea222b --- /dev/null +++ b/backend/pipeline/sources/hn.py @@ -0,0 +1,78 @@ +from __future__ import annotations + +import re +from concurrent.futures import ThreadPoolExecutor + +from pipeline.sources.extract_content import extract_content +from pipeline.sources.utils import clean_title, fetch_with_timeout, is_within_window +from pipeline.utils import log + +HN_TOP = "https://hacker-news.firebaseio.com/v0/topstories.json" +HN_ITEM = "https://hacker-news.firebaseio.com/v0/item" +HN_FETCH_LIMIT = 200 + +HN_AI_KEYWORDS = re.compile( + r"\b(ai|llm|gpt|claude|gemini|llama|openai|anthropic|deepseek|mistral|opencode|" + r"tokens|transformer|diffusion|machine.?learning|deep.?learning|neural.?net|" + r"language.?model|artificial.?intelligen|stable.?diffusion|midjourney|copilot|" + r"chatbot|rag|fine.?tun|embedding|token|lora|rlhf|gguf|ollama|hugging.?face)\b", + re.IGNORECASE, +) + + +def _fetch_item(item_id: int) -> dict | None: + try: + resp = fetch_with_timeout(f"{HN_ITEM}/{item_id}.json", timeout=10.0) + return resp.json() + except Exception: + return None + + +def fetch_hn() -> list[dict]: + log("Fetching Hacker News top stories...") + try: + resp = fetch_with_timeout(HN_TOP) + ids: list[int] = resp.json() + except Exception as e: + log(f" HN top stories fetch failed: {e}") + return [] + + top_ids = ids[:HN_FETCH_LIMIT] + + with ThreadPoolExecutor(max_workers=20) as executor: + results = list(executor.map(_fetch_item, top_ids)) + + articles: list[dict] = [] + for item in results: + if not item or item.get("type") != "story" or not item.get("title"): + continue + if not HN_AI_KEYWORDS.search(item["title"]): + continue + pub_date = ( + __import__("datetime") + .datetime.fromtimestamp( + item["time"], tz=__import__("datetime").timezone.utc + ) + .isoformat() + if item.get("time") + else None + ) + if not is_within_window(pub_date): + continue + articles.append( + { + "title": clean_title(item["title"]), + "url": item.get("url") + or f"https://news.ycombinator.com/item?id={item['id']}", + "content": "", + "published_date": pub_date + or __import__("datetime") + .datetime.now(__import__("datetime").timezone.utc) + .isoformat(), + "source": "Hacker News", + "source_type": "hackerNews", + } + ) + + log(f"Hacker News: {len(articles)} AI-related stories") + return extract_content(articles) diff --git a/backend/pipeline/sources/substack-sources.json b/backend/pipeline/sources/substack-sources.json new file mode 100644 index 0000000000..c3fd0f6541 --- /dev/null +++ b/backend/pipeline/sources/substack-sources.json @@ -0,0 +1,430 @@ +[ + { + "name": "Nate's Substack", + "rssUrl": "https://natesnewsletter.substack.com/feed" + }, + { + "name": "Interconnects AI", + "rssUrl": "https://www.interconnects.ai/feed" + }, + { + "name": "AI Supremacy", + "rssUrl": "https://www.ai-supremacy.com/feed" + }, + { + "name": "The AI Maker", + "rssUrl": "https://aimaker.substack.com/feed" + }, + { + "name": "Understanding AI", + "rssUrl": "https://www.understandingai.org/feed" + }, + { + "name": "AI Tidbits", + "rssUrl": "https://www.aitidbits.ai/feed" + }, + { + "name": "Deep (Learning) Focus", + "rssUrl": "https://cameronrwolfe.substack.com/feed" + }, + { + "name": "AI Newsletter", + "rssUrl": "https://nlp.elvissaravia.com/feed" + }, + { + "name": "Artificial Ignorance", + "rssUrl": "https://www.ignorance.ai/feed" + }, + { + "name": "AI by Hand", + "rssUrl": "https://www.byhand.ai/feed" + }, + { + "name": "Practical AI for Solo Entrepreneurs", + "rssUrl": "https://soloailab.substack.com/feed" + }, + { + "name": "Last Week in AI", + "rssUrl": "https://lastweekin.ai/feed" + }, + { + "name": "The Generative Programmer", + "rssUrl": "https://generativeprogrammer.com/feed" + }, + { + "name": "Designing with AI", + "rssUrl": "https://newsletter.victordibia.com/feed" + }, + { + "name": "Andrej Karpathy", + "rssUrl": "https://karpathy.substack.com/feed" + }, + { + "name": "Ben's Bites", + "rssUrl": "https://www.bensbites.com/feed" + }, + { + "name": "Machine Learning Pills", + "rssUrl": "https://mlpills.substack.com/feed" + }, + { + "name": "Chipstrat", + "rssUrl": "https://www.chipstrat.com/feed" + }, + { + "name": "Making AI Accessible", + "rssUrl": "https://louisbouchard.substack.com/feed" + }, + { + "name": "Redwood Research", + "rssUrl": "https://blog.redwoodresearch.org/feed" + }, + { + "name": "Works on My Machine", + "rssUrl": "https://worksonmymachine.ai/feed" + }, + { + "name": "Hamel's Substack", + "rssUrl": "https://hamelhusain.substack.com/feed" + }, + { + "name": "The AI Engineer", + "rssUrl": "https://newsletter.owainlewis.com/feed" + }, + { + "name": "Trelis Research", + "rssUrl": "https://trelis.substack.com/feed" + }, + { + "name": "Gradient Flow", + "rssUrl": "https://gradientflow.substack.com/feed" + }, + { + "name": "Generally Intelligent", + "rssUrl": "https://generallyintelligent.substack.com/feed" + }, + { + "name": "Building AI Products From Scratch", + "rssUrl": "https://mikikobazeley.substack.com/feed" + }, + { + "name": "LLM Watch", + "rssUrl": "https://www.llmwatch.com/feed" + }, + { + "name": "Loop Engineering", + "rssUrl": "https://linas.substack.com/feed" + }, + { + "name": "Cobus Greyling on LLMs", + "rssUrl": "https://cobusgreyling.substack.com/feed" + }, + { + "name": "Elevate by Addy Osmani", + "rssUrl": "https://addyo.substack.com/feed" + }, + { + "name": "DiamantAI", + "rssUrl": "https://newsletter.diamant-ai.com/feed" + }, + { + "name": "MLWhiz", + "rssUrl": "https://www.mlwhiz.com/feed" + }, + { + "name": "Semantics & Systems", + "rssUrl": "https://khaledea.substack.com/feed" + }, + { + "name": "Token Contributions", + "rssUrl": "https://tokencontributions.substack.com/feed" + }, + { + "name": "Generative History", + "rssUrl": "https://generativehistory.substack.com/feed" + }, + { + "name": "Digital Thoughts", + "rssUrl": "https://thoughts.jock.pl/feed" + }, + { + "name": "Modern Mom Playbook", + "rssUrl": "https://modernmomplaybook.substack.com/feed" + }, + { + "name": "Prompt-Led Product | For PMs Building in the AI Era", + "rssUrl": "https://promptledproduct.substack.com/feed" + }, + { + "name": "AI Weekender", + "rssUrl": "https://aiweekender.substack.com/feed" + }, + { + "name": "Senior Data Science Lead", + "rssUrl": "https://joseparreogarcia.substack.com/feed" + }, + { + "name": "AI Espresso | your tech brew", + "rssUrl": "https://aiespressotechbrew.substack.com/feed" + }, + { + "name": "AI by Aakash", + "rssUrl": "https://www.aibyaakash.com/feed" + }, + { + "name": "Engincan Veske", + "rssUrl": "https://engincanveske.substack.com/feed" + }, + { + "name": "ModelCraft", + "rssUrl": "https://modelcraft.substack.com/feed" + }, + { + "name": "Vik's Newsletter", + "rssUrl": "https://www.viksnewsletter.com/feed" + }, + { + "name": "Standout Systems by Teodora", + "rssUrl": "https://teodoracoach.substack.com/feed" + }, + { + "name": "The Circuit", + "rssUrl": "https://metacircuits.substack.com/feed" + }, + { + "name": "Artificial Enigma", + "rssUrl": "https://idakaukonen.substack.com/feed" + }, + { + "name": "Travis Sparks - Sparkry.AI + Neurodivergence + Business", + "rssUrl": "https://sparkryai.substack.com/feed" + }, + { + "name": "AI Disruption", + "rssUrl": "https://aidisruption.ai/feed" + }, + { + "name": "Cash & Cache", + "rssUrl": "https://cashandcache.substack.com/feed" + }, + { + "name": "Prosper", + "rssUrl": "https://prosperinai.substack.com/feed" + }, + { + "name": "AI Superhero", + "rssUrl": "https://shmulc.substack.com/feed" + }, + { + "name": "AI blew my mind", + "rssUrl": "https://aiblewmymind.substack.com/feed" + }, + { + "name": "ToxSec - AI and Cybersecurity", + "rssUrl": "https://www.toxsec.com/feed" + }, + { + "name": "The Ai Rabbit Hole", + "rssUrl": "https://jtnovelo2131.substack.com/feed" + }, + { + "name": "The Zhang-ularity", + "rssUrl": "https://fzhang.substack.com/feed" + }, + { + "name": "Asymmetric Jump", + "rssUrl": "https://asymmetricjump.substack.com/feed" + }, + { + "name": "Automato: Smarter Work in the Age of AI", + "rssUrl": "https://automato.substack.com/feed" + }, + { + "name": "Empathetic AI Lab", + "rssUrl": "https://aicompanionlab.substack.com/feed" + }, + { + "name": "Leadership in Change", + "rssUrl": "https://leadershipinchange.com/feed" + }, + { + "name": "The FoLD", + "rssUrl": "https://liamdarmody.substack.com/feed" + }, + { + "name": "AI Echoes", + "rssUrl": "https://aiechoes.substack.com/feed" + }, + { + "name": "AI in public", + "rssUrl": "https://humzakhalid.substack.com/feed" + }, + { + "name": "Artificial Code", + "rssUrl": "https://artificialcode.substack.com/feed" + }, + { + "name": "Purposeful AI", + "rssUrl": "https://purposefulai.substack.com/feed" + }, + { + "name": "Shrivu's Substack", + "rssUrl": "https://blog.sshh.io/feed" + }, + { + "name": "The AI Architect", + "rssUrl": "https://mvidmar.substack.com/feed" + }, + { + "name": "The Humans in the Loop", + "rssUrl": "https://www.thehumansintheloop.ai/feed" + }, + { + "name": "AI Enhanced Engineer", + "rssUrl": "https://aienhancedengineer.substack.com/feed" + }, + { + "name": "Product with Attitude", + "rssUrl": "https://karozieminski.substack.com/feed" + }, + { + "name": "And Yet It Moves", + "rssUrl": "https://andyetitmoves.substack.com/feed" + }, + { + "name": "Department of Product", + "rssUrl": "https://departmentofproduct.substack.com/feed" + }, + { + "name": "Design with AI", + "rssUrl": "https://designwithai.substack.com/feed" + }, + { + "name": "Limited Edition Jonathan", + "rssUrl": "https://limitededitionjonathan.substack.com/feed" + }, + { + "name": "Product Growth", + "rssUrl": "https://www.news.aakashg.com/feed" + }, + { + "name": "The Outer Loop", + "rssUrl": "https://theouterloop.substack.com/feed" + }, + { + "name": "Co-Write with AI", + "rssUrl": "https://articles.cowritewithai.com/feed" + }, + { + "name": "Exploring ChatGPT", + "rssUrl": "https://exploringchatgpt.substack.com/feed" + }, + { + "name": "Hello AI World", + "rssUrl": "https://malihaarshad1.substack.com/feed" + }, + { + "name": "Savvy Sloth", + "rssUrl": "https://savvysloth.substack.com/feed" + }, + { + "name": "Turing Post", + "rssUrl": "https://turingpost.substack.com/feed" + }, + { + "name": "Marily’s AI Product Academy Newsletter", + "rssUrl": "https://marily.substack.com/feed" + }, + { + "name": "ByteByteGo Newsletter", + "rssUrl": "https://blog.bytebytego.com/feed" + }, + { + "name": "The Tech Buffet", + "rssUrl": "https://thetechbuffet.substack.com/feed" + }, + { + "name": "SwirlAI Newsletter", + "rssUrl": "https://www.newsletter.swirlai.com/feed" + }, + { + "name": "Simon Willison’s Newsletter", + "rssUrl": "https://simonw.substack.com/feed" + }, + { + "name": "Ahead of AI", + "rssUrl": "https://magazine.sebastianraschka.com/feed" + }, + { + "name": "The Pipe & The Line", + "rssUrl": "https://thepipeandtheline.substack.com/feed" + }, + { + "name": "Coding with Intelligence", + "rssUrl": "https://codingwithintelligence.com/feed" + }, + { + "name": "AI for Software Engineers", + "rssUrl": "https://www.aiforswes.com/feed" + }, + { + "name": "Thonk From First Principles", + "rssUrl": "https://www.thonking.ai/feed" + }, + { + "name": "The Kaitchup – AI on a Budget", + "rssUrl": "https://kaitchup.substack.com/feed" + }, + { + "name": "ThursdAI - Highest signal weekly AI news show", + "rssUrl": "https://sub.thursdai.news/feed" + }, + { + "name": "The AI Break", + "rssUrl": "https://theaibreak.substack.com/feed" + }, + { + "name": "Artificial Corner", + "rssUrl": "https://artificialcorner.com/feed" + }, + { + "name": "The Ontologist", + "rssUrl": "https://ontologist.substack.com/feed" + }, + { + "name": "The Technical Executive", + "rssUrl": "https://sderosiaux.substack.com/feed" + }, + { + "name": "AI Health Uncut", + "rssUrl": "https://www.fixhealth.ai/feed" + }, + { + "name": "Exploring Artificial Intelligence", + "rssUrl": "https://exploringartificialintelligence.substack.com/feed" + }, + { + "name": "All Agents Considered", + "rssUrl": "https://allagentsconsidered.substack.com/feed" + }, + { + "name": "ai.tism", + "rssUrl": "https://aitism.substack.com/feed" + }, + { + "name": "Practical AI Brief", + "rssUrl": "https://practicalaibrief.substack.com/feed" + }, + { + "name": "Matt Paige", + "rssUrl": "https://mattpaige68.substack.com/feed" + }, + { + "name": "Artificial Intelligence Learning 🤖🧠🦾", + "rssUrl": "https://offthegridxp.substack.com/feed" + }, + { + "name": "Machine Learning At Scale", + "rssUrl": "https://machinelearningatscale.substack.com/feed" + } +] diff --git a/backend/pipeline/sources/substack.py b/backend/pipeline/sources/substack.py new file mode 100644 index 0000000000..e4f36fff42 --- /dev/null +++ b/backend/pipeline/sources/substack.py @@ -0,0 +1,105 @@ +from __future__ import annotations + +import os +import time +from concurrent.futures import ThreadPoolExecutor, as_completed + +import feedparser +import httpx + +from pipeline.sources.utils import BROWSER_HEADERS, clean_title, is_within_window +from pipeline.utils import log + +_PROXY_URL = os.environ.get("RESIDENTIAL_PROXY_URL") + +if _PROXY_URL: + try: + from urllib.parse import urlparse + + _u = urlparse(_PROXY_URL) + log( + f"Substack proxy: {_u.scheme}://{_u.hostname}:{_u.port or '(default)'} (auth: {'yes' if _u.username else 'no'})" + ) + except Exception: + log(f"Substack proxy: set but unparseable (len {len(_PROXY_URL)})") +else: + log("Substack proxy: none (RESIDENTIAL_PROXY_URL unset)") + + +def _fetch_feed_xml(url: str, retries: int = 2, backoff: float = 2.0) -> str: + for attempt in range(retries + 1): + use_proxy = attempt > 0 and bool(_PROXY_URL) + kwargs: dict = { + "headers": BROWSER_HEADERS, + "timeout": 15.0, + "follow_redirects": True, + } + if use_proxy: + kwargs["proxy"] = _PROXY_URL + try: + with httpx.Client(**kwargs) as client: + resp = client.get(url) + except Exception as e: + raise RuntimeError( + f"fetch failed{'(via proxy)' if use_proxy else ''}: {e}" + ) from e + + if resp.is_success: + return resp.text + if resp.status_code in (403, 429) and attempt < retries and _PROXY_URL: + time.sleep(backoff * (2**attempt)) + continue + raise RuntimeError(f"Status code {resp.status_code}") + + raise RuntimeError("Exhausted retries") + + +def _fetch_source(source: dict) -> list[dict]: + name = source["name"] + rss_url = source["rssUrl"] + log(f"Fetching {name}...") + try: + xml = _fetch_feed_xml(rss_url) + feed = feedparser.parse(xml) + items = feed.get("entries", []) + within = [ + it + for it in items + if is_within_window(it.get("published") or it.get("updated")) + ] + log(f" {name}: {len(within)} in window") + return [ + { + "title": clean_title(it.get("title") or "(no title)"), + "url": it.get("link") or "", + "content": it.get("summary") or "", + "published_date": it.get("published") or it.get("updated") or "", + "source": name, + "source_type": "rss", + } + for it in within + ] + except Exception as e: + log(f" FAILED {name}: {e}") + return [] + + +def fetch_substack() -> list[dict]: + import json + import pathlib + + sources_path = pathlib.Path(__file__).parent / "substack-sources.json" + with open(sources_path) as f: + sources: list[dict] = json.load(f) + + articles: list[dict] = [] + with ThreadPoolExecutor(max_workers=10) as executor: + futures = {executor.submit(_fetch_source, src): src for src in sources} + for future in as_completed(futures): + try: + articles.extend(future.result()) + except Exception: + pass + + log(f"Substack: {len(articles)} articles") + return articles diff --git a/backend/pipeline/sources/utils.py b/backend/pipeline/sources/utils.py new file mode 100644 index 0000000000..85173b32d2 --- /dev/null +++ b/backend/pipeline/sources/utils.py @@ -0,0 +1,55 @@ +from __future__ import annotations + +import re +from datetime import UTC, datetime + +import httpx + +HN_PREFIX_RE = re.compile(r"^(?:Show|Launch|Ask|Tell) HN:\s*", re.IGNORECASE) +WINDOW_HOURS = 168 +FETCH_TIMEOUT_SECS = 15.0 + +BROWSER_HEADERS = { + "User-Agent": ( + "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) " + "AppleWebKit/537.36 (KHTML, like Gecko) Chrome/124.0.0.0 Safari/537.36" + ), + "Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8", + "Accept-Language": "en-US,en;q=0.9", +} + + +def clean_title(title: str) -> str: + return HN_PREFIX_RE.sub("", title).strip() + + +def is_within_window(date_str: str | None, window_hours: int = WINDOW_HOURS) -> bool: + if not date_str: + return True + try: + from email.utils import parsedate_to_datetime + + try: + published = parsedate_to_datetime(date_str) + except Exception: + published = datetime.fromisoformat(date_str.replace("Z", "+00:00")) + now = datetime.now(UTC) + hours_ago = (now - published.astimezone(UTC)).total_seconds() / 3600 + return hours_ago <= window_hours + except Exception: + return True + + +def fetch_with_timeout( + url: str, + timeout: float = FETCH_TIMEOUT_SECS, + proxy: str | None = None, + headers: dict | None = None, +) -> httpx.Response: + kwargs: dict = {"timeout": timeout, "follow_redirects": True} + if proxy: + kwargs["proxy"] = proxy + if headers: + kwargs["headers"] = headers + with httpx.Client(**kwargs) as client: + return client.get(url) diff --git a/backend/pipeline/steps.py b/backend/pipeline/steps.py new file mode 100644 index 0000000000..5e37a9ee64 --- /dev/null +++ b/backend/pipeline/steps.py @@ -0,0 +1,60 @@ +from __future__ import annotations + +import re + +SCORE_THRESHOLD = 76 +PROMPT_CONTENT_CAP = 1500 + +NON_REPO_OWNERS = { + "features", + "login", + "pricing", + "about", + "marketplace", + "explore", + "topics", + "collections", + "trending", + "sponsors", + "orgs", + "apps", + "contact", + "security", +} + +GITHUB_REPO_RE = re.compile( + r"https?://(?:www\.)?github\.com/([A-Za-z0-9_.-]+)/([A-Za-z0-9_.-]+)" +) + + +def github_repo_from_content(content: str) -> str | None: + match = GITHUB_REPO_RE.search(content) + if not match: + return None + owner, repo = match.group(1), match.group(2) + if owner.lower() in NON_REPO_OWNERS: + return None + return f"https://github.com/{owner}/{repo}" + + +def kind_from_url(url: str) -> str | None: + try: + from urllib.parse import urlparse + + host = urlparse(url).hostname or "" + host = host.removeprefix("www.") + if host in ("github.com", "gitlab.com"): + return "repo" + if host in ("huggingface.co", "hf.co"): + return "model" + if host in ("arxiv.org", "ar5iv.labs.arxiv.org"): + return "paper" + except Exception: + pass + return None + + +TRUST_BY_SOURCE: dict[str, str] = { + "Hacker News": "high", + "AI News": "high", +} diff --git a/backend/pipeline/utils.py b/backend/pipeline/utils.py new file mode 100644 index 0000000000..12e629a124 --- /dev/null +++ b/backend/pipeline/utils.py @@ -0,0 +1,48 @@ +from datetime import UTC, datetime + +import regex + + +def log(message: str) -> None: + ts = datetime.now(UTC).isoformat() + print(f"[{ts}] {message}") + + +def wait_ms(ms: int) -> None: + import time + + time.sleep(ms / 1000) + + +def strip_title_wrappers(text: str) -> str: + """Remove LLM echo artifacts: leading [Source] tags, numbering, surrounding quotes.""" + s = text.strip() + s = regex.sub(r"^\[[^\]]+\]\s*", "", s) + s = regex.sub(r"^\d+\.\s*", "", s) + pairs = [('"', '"'), ("'", "'"), ("“", "”"), ("‘", "’")] + for open_, close in pairs: + if s.startswith(open_) and s.endswith(close) and len(s) >= 2: + s = s[len(open_) : len(s) - len(close)].strip() + break + return s + + +def sanitize_llm_text(text: str) -> str: + """Strip smart quotes, arrows, emoji, and extra whitespace from LLM output.""" + s = text + s = regex.sub(r"[‘’‚]", "'", s) + s = regex.sub(r"[“”„]", '"', s) + s = regex.sub(r"→", "->", s) + s = regex.sub(r"←", "<-", s) + s = regex.sub(r"↔", "<->", s) + s = regex.sub(r"[–—]", "-", s) + s = regex.sub(r"…", "...", s) + s = regex.sub(r"[•‣◦▪▫]", "-", s) + s = regex.sub( + r"[\p{Emoji_Presentation}\p{Extended_Pictographic}]️?" + r"(‍[\p{Emoji_Presentation}\p{Extended_Pictographic}]️?)*", + "", + s, + ) + s = regex.sub(r" {2,}", " ", s) + return s.strip() diff --git a/backend/pyproject.toml b/backend/pyproject.toml index 4552d7483f..53dc3aa85a 100644 --- a/backend/pyproject.toml +++ b/backend/pyproject.toml @@ -21,6 +21,11 @@ dependencies = [ "pwdlib[argon2,bcrypt]>=0.3.0", "pgvector>=0.3.0", "model2vec>=0.4.0", + "baml-py>=0.223.0", + "trafilatura>=2.0.0", + "feedparser>=6.0.0", + "dnspython>=2.6.0", + "regex>=2024.0.0", ] [dependency-groups] @@ -67,6 +72,10 @@ ignore = [ # Preserve types, even if a file imports `from __future__ import annotations`. keep-runtime-typing = true +[tool.ruff.lint.per-file-ignores] +# The pipeline logs to stdout via print() so supercronic captures it in container logs. +"pipeline/**" = ["T201"] + [tool.coverage.run] source = ["app"] dynamic_context = "test_function" diff --git a/baml_src/clients.baml b/baml_src/clients.baml new file mode 100644 index 0000000000..e9eaa343cc --- /dev/null +++ b/baml_src/clients.baml @@ -0,0 +1,29 @@ +client Fast { + provider openai-generic + options { + base_url "https://integrate.api.nvidia.com/v1" + api_key env.NVIDIA_NIM_API_KEY + model "qwen/qwen3-next-80b-a3b-instruct" + timeout 60 + } +} + +client Nvidia { + provider openai-generic + options { + base_url "https://integrate.api.nvidia.com/v1" + api_key env.NVIDIA_NIM_API_KEY + model "moonshotai/kimi-k2.6" + timeout 60 + } +} + +client NvidiaGptOss { + provider openai-generic + options { + base_url "https://integrate.api.nvidia.com/v1" + api_key env.NVIDIA_NIM_API_KEY + model "openai/gpt-oss-120b" + timeout 60 + } +} diff --git a/baml_src/dedup.baml b/baml_src/dedup.baml new file mode 100644 index 0000000000..fd536bb051 --- /dev/null +++ b/baml_src/dedup.baml @@ -0,0 +1,58 @@ +class DedupMatch { + url string @description("URL of the new article") + existingUrl string @description("URL of the existing article it duplicates") +} + +function SemanticDedup( + newArticles: ArticleInput[], + existingArticles: ExistingArticle[] +) -> DedupMatch[] { + client NvidiaGptOss + prompt #" + {{ _.role("system") }} + You are a semantic similarity engine. You compare article pairs and determine whether they cover the same underlying story. You focus on substance, not surface-level keyword overlap. + + {{ _.role("user") }} + You are given two lists: + 1. NEW articles that were just fetched + 2. EXISTING articles already in our database from the last 14 days + + Your job: identify which NEW articles are about the same story as an EXISTING article. Two articles are "the same story" if they cover the same announcement, release, event, or topic - even if from different sources or with different angles. + + NEW articles: + {% for a in newArticles %} + {{ loop.index }}. [{{ a.source }}] "{{ a.title }}" - {{ a.url }}{% if a.trust %} [trust: {{ a.trust }}]{% endif %} + {% if a.snippet %} {{ a.snippet }}{% endif %} + {% endfor %} + + EXISTING articles: + {% for a in existingArticles %} + {{ loop.index }}. [{{ a.source }}] "{{ a.title }}" - {{ a.url }} + {% endfor %} + + For each match, return the new article's URL and the existing article's URL. + If there are no duplicates, return an empty list. + + {{ ctx.output_format }} + "# +} + +test dedup_no_matches { + functions [SemanticDedup] + args { + newArticles [ + { + url "https://a.com/1" + title "Claude 4 released" + source "HN" + } + ] + existingArticles [ + { + url "https://b.com/1" + title "The state of Rust in 2026" + source "RSS" + } + ] + } +} diff --git a/baml_src/discover.baml b/baml_src/discover.baml new file mode 100644 index 0000000000..30a55c1ad4 --- /dev/null +++ b/baml_src/discover.baml @@ -0,0 +1,42 @@ +// Batched relevance classifier for the Substack discovery crawler. +// One LLM call judges many candidate profiles at once (see ScoreArticles for +// the array-in/array-out batching pattern). Classification runs on cheap +// metadata (name + description) BEFORE any per-profile post fetch, and gates +// both DB insertion and whether the crawler recurses into that profile. + +class ProfileInput { + handle string @description("Substack owner handle, echoed back in the verdict") + name string @description("Publication name") + description string? @description("Publication hero text and/or author bio, if known") +} + +class ProfileVerdict { + handle string @description("Must exactly match the input handle") + isAiRelated bool + confidence int @description("0-100 confidence that AI/ML/LLMs is the PRIMARY focus") +} + +function ClassifyProfiles(profiles: ProfileInput[]) -> ProfileVerdict[] { + client Nvidia + prompt #" + {{ _.role("system") }} + You curate sources for a developer-focused AI news platform. For each Substack + publication, decide whether artificial intelligence is its PRIMARY subject: + AI/ML/LLMs, foundation models, AI engineering, AI products, or AI research. + + Mark isAiRelated = true ONLY when AI is clearly the main topic. Mark false for + general tech, productivity, marketing, business, crypto, politics, lifestyle, or + publications that merely mention AI in passing. When the signal is thin (sparse + description, generic name), lean false and assign low confidence - the crawler + prunes everything you reject, so false positives pollute the whole subtree. + + {{ _.role("user") }} + Classify every profile. Echo each handle back EXACTLY as given. + + {% for p in profiles %} + {{ loop.index }}. handle={{ p.handle }} | {{ p.name }}{% if p.description %} — {{ p.description }}{% endif %} + {% endfor %} + + {{ ctx.output_format }} + "# +} diff --git a/baml_src/extract_links.baml b/baml_src/extract_links.baml new file mode 100644 index 0000000000..579c0d8aa4 --- /dev/null +++ b/baml_src/extract_links.baml @@ -0,0 +1,42 @@ +class ExtractedLink { + title string + url string + snippet string @description("One-sentence description of the article") +} + +function ExtractLinks(emailHtml: string) -> ExtractedLink[] { + client NvidiaGptOss + prompt #" + {{ _.role("system") }} + You are a precise link extraction engine. You parse newsletter HTML and identify external article links while filtering out tracking, admin, and promotional URLs. + + {{ _.role("user") }} + You are given the HTML body of a newsletter email. Extract all article links that point to external news stories, blog posts, research papers, or product announcements. + + For each article, return its title, URL, and a one-sentence snippet describing it. + + IGNORE these types of links: + - Tracking/redirect URLs (e.g. links through email marketing platforms) + - Unsubscribe, manage preferences, or email settings links + - Social media profile links (twitter, linkedin, etc.) + - Links back to the newsletter's own homepage, archive index, or subscription page (but DO include article/post links hosted on the newsletter's domain - curated newsletters often host their own content) + - Sponsor/advertisement links + - Job posting links + + RESOLVE redirect URLs: if a link is clearly a tracking redirect (contains /click, /track, utm_ params, etc.), try to extract the final destination URL from the href. Strip all UTM parameters from URLs. + + Newsletter HTML: + {{ emailHtml }} + + If no relevant article links are found, return an empty list. + + {{ ctx.output_format }} + "# +} + +test extract_links_basic { + functions [ExtractLinks] + args { + emailHtml "Welcome to today's issue! [Read OpenAI's new paper](https://openai.com/papers/gpt-5). [Unsubscribe](https://newsletter.com/unsubscribe)." + } +} diff --git a/baml_src/extract_products.baml b/baml_src/extract_products.baml new file mode 100644 index 0000000000..9e5f5a531a --- /dev/null +++ b/baml_src/extract_products.baml @@ -0,0 +1,125 @@ +// Product-centric newsletter extraction. +// +// Replaces the per-newsletter tracking-URL resolvers: instead of decoding each +// provider's redirect scheme to recover the real link, we extract the *named +// products* a newsletter reports on (from anchor text + surrounding prose), +// keep only the notable ones, and rediscover their canonical URLs via web +// search (src/sources/email.ts). SelectProductLink then picks the best +// first-party result among the candidates. + +class NewsletterProduct { + name string @description("Exact product / tool / model / launch name") + description string @description("Concise phrase: what it is and does, usable verbatim as a web search query") +} + +function ExtractProducts(newsletterText: string) -> NewsletterProduct[] { + client NvidiaGptOss + prompt #" + {{ _.role("system") }} + You extract the AI/tech products, tools, models, and launches that a newsletter is reporting on. Work only from the text; never invent products that are not mentioned. + + {{ _.role("user") }} + Below is the text of a newsletter email. Links appear as [anchor text](url) but the URLs are often tracking redirects, so judge by the words, not the links. + + Identify every distinct product, tool, model, SDK, dataset, or launch the newsletter is reporting as news. For each, return: + - name: the exact product/tool/model name + - description: a concise phrase describing what it is and does, suitable as a web search query + + INCLUDE only real, named launches a reader could go use or read about. + + IGNORE: + - the author's intro letter, essay, or personal commentary + - sponsor blurbs, advertisements, "brought to you by", upgrade / subscribe / manage-preferences prompts + - social-media embeds (an @handle with like / repost / reply counts) and the newsletter's own social links + - section headers, navigation, and unsubscribe links + + Newsletter text: + {{ newsletterText }} + + If the text names no qualifying products, return an empty list. + + {{ ctx.output_format }} + "# +} + +// Notability gate: trims the extracted list to the launches actually worth +// resolving, so we don't spend a web search on every incremental SDK bump. +// Returns the 1-based indices of the products to KEEP. +function SelectNotableProducts(products: NewsletterProduct[]) -> int[] { + client Nvidia + prompt #" + {{ _.role("user") }} + Below is a numbered list of products/tools/models a newsletter mentioned. Return the numbers of the ones that are NOTABLE enough to feature in an AI-news aggregator. + + KEEP a product if it is a distinct, real, individually newsworthy launch a reader would want to click: new models, significant new products or platforms, notable agents/tools, major releases. + + DROP: + - minor or incremental items: small SDK/utility bumps, niche helper libraries, design skills, config tweaks + - vague or marketing-only entries with no concrete product behind them + - duplicates or sub-features of another item in the list + + Products: + {% for p in products %} + {{ loop.index }}. {{ p.name }} — {{ p.description }} + {% endfor %} + + Return only the numbers to keep, as a JSON array of integers. If none qualify, return []. + + {{ ctx.output_format }} + "# +} + +class SearchCandidate { + title string + url string + snippet string +} + +class ProductLinkChoice { + index int @description("1-based index of the best first-party result, or 0 if none qualifies") + confidence float @description("0.0 - 1.0") +} + +// Picks the best canonical URL for a product among search candidates, biased +// hard toward the official / first-party source and away from social posts and +// SEO/aggregator pages. Returns index 0 when nothing is clearly the product. +function SelectProductLink( + productName: string, + productDescription: string, + candidates: SearchCandidate[] +) -> ProductLinkChoice { + client Nvidia + prompt #" + {{ _.role("user") }} + A newsletter featured this item: + name: {{ productName }} + description: {{ productDescription }} + + Web search returned these candidate results: + {% for c in candidates %} + {{ loop.index }}. {{ c.title }} + url: {{ c.url }} + snippet: {{ c.snippet }} + {% endfor %} + + Pick the ONE candidate that is the canonical, first-party source for this exact product — its official site, product page, model card, repo, or the vendor's own announcement. + + PREFER the official / first-party domain that matches the product or its maker. + REJECT (do not pick) when it is the best available: + - social-media posts (x.com, twitter.com, linkedin.com, reddit.com, threads, mastodon) + - videos (youtube.com) + - content-farm / SEO / generic aggregator or listicle pages that merely mention the product + - a DIFFERENT product that happens to share the name + + Return the 1-based index of the best first-party result. If none of the candidates is clearly a first-party source for THIS product, return index 0. + + {{ ctx.output_format }} + "# +} + +test extract_products_basic { + functions [ExtractProducts] + args { + newsletterText "Headlines: [OpenAI ships GPT-5](https://sub.stack/redirect/2/abc), a new flagship model. Brought to you by Acme. [Unsubscribe](https://newsletter.com/unsub)." + } +} diff --git a/baml_src/fix_titles.baml b/baml_src/fix_titles.baml new file mode 100644 index 0000000000..9239b53d20 --- /dev/null +++ b/baml_src/fix_titles.baml @@ -0,0 +1,61 @@ +class TitleFix { + url string @description("The exact URL from the matching input article - copy verbatim") + title string @description("Plain title text only. No surrounding quotes. No leading source name or bracket tag. Max 12 words. Return the input title verbatim if it is already clear, specific, and informative.") +} + +function ImproveTitles(articles: ArticleInput[]) -> TitleFix[] { + client NvidiaGptOss + prompt #" + {{ _.role("system") }} + You are a technical editor. You write clear, informative article titles for an AI developer news platform. + + Output rules (strict): + - For each input article, return one TitleFix whose `url` exactly matches that article's URL. + - The `title` field contains plain title text ONLY. Do NOT wrap it in quotes. Do NOT prefix it with "[Source]" or any source name. Do NOT include the URL. + - Use only the snippet of the SAME article to inform the rewrite. Never blend information across articles. + + {{ _.role("user") }} + Decide for each article whether the existing title is already good. A good title is specific, informative, and technical/neutral in register - it tells a developer what the article is actually about. + + - If the existing title is already good, return it verbatim. + - Otherwise rewrite it using only that article's snippet: specific, informative, max 12 words, technical/neutral register, no hype or filler. + + {% for a in articles %} + --- Article {{ loop.index }} --- + url: {{ a.url }} + source: {{ a.source }} + current_title: {{ a.title }} + {% if a.snippet %}snippet: {{ a.snippet }}{% endif %} + {% endfor %} + + {{ ctx.output_format }} + "# +} + +test improve_titles_rewrite_short { + functions [ImproveTitles] + args { + articles [ + { + url "https://example.com/claude" + title "Claude 4" + source "HN" + snippet "Anthropic today released Claude 4, a new flagship model with improved reasoning and a 1M-token context window." + } + ] + } +} + +test improve_titles_keep_unchanged { + functions [ImproveTitles] + args { + articles [ + { + url "https://example.com/post" + title "Anthropic releases Claude 4 with 1M-token context window" + source "HN" + snippet "Anthropic today released Claude 4, a new flagship model with improved reasoning." + } + ] + } +} diff --git a/baml_src/generators.baml b/baml_src/generators.baml new file mode 100644 index 0000000000..c5ab04792f --- /dev/null +++ b/baml_src/generators.baml @@ -0,0 +1,5 @@ +generator python { + output_type "python/pydantic" + output_dir "../backend/" + version "0.223.0" +} diff --git a/baml_src/score.baml b/baml_src/score.baml new file mode 100644 index 0000000000..01d73713df --- /dev/null +++ b/baml_src/score.baml @@ -0,0 +1,84 @@ +class ScoredArticle { + url string + score int @description("1-100 developer-actionability rating") +} + +function ScoreArticles(articles: ArticleInput[]) -> ScoredArticle[] { + client Nvidia + prompt #" + {{ _.role("system") }} + You are a senior editorial analyst at a developer news platform. Your job is to evaluate articles for relevance and actionability for AI builders. You are precise, consistent, and ruthless about filtering noise. + + {{ _.role("user") }} + Score every article for developer-actionability on a 1-100 scale. + + STEP 1 - SCOPE CHECK (apply first, before scoring): + Is the article about AI, ML, LLMs, foundation models, or AI-adjacent developer tools/infrastructure? + - NO → score 1-20 and move on. Do NOT apply the scoring guide below. + - Out-of-scope examples: text editors, parsers, version control tools, data structures (CRDTs, B-trees), memory management, general programming tutorials, non-AI open source projects, codebase audits, legacy code. These are general software engineering - not AI. + + STEP 2 - SCORE (only for in-scope articles): + Audience: developers, startup founders, and tech leaders building with AI who want to ship faster. + + Score 91-100 is reserved for exceptional articles that are BOTH immediately actionable today AND fit one of these themes: local/on-device inference, privacy-preserving AI, efficiency breakthroughs (quantization, token optimization, running models on less hardware), or deep technical dives that explain how something actually works. A score in this range means "a developer could open a terminal and act on this within the hour, AND it reveals a non-obvious insight or technique." Zero is a valid outcome - do not give 91+ just because something is the best of a weak batch. + + Models (new releases, benchmarks, evals, model cards, comparisons): + - 81-90: New model release or major update, model system cards, open-weight models a developer can run today + - 71-80: Meaningful benchmark or eval, model comparison with actionable conclusions + + Dev (SDKs, frameworks, CLI tools, IDE integrations, open-source projects, tutorials, deployment): + - 81-90: New AI API or SDK, open-source AI tool/library a developer can use today + - 71-80: Fine-tuning guide, RAG pattern, significant framework update, AI infrastructure (training, inference, memory optimization), deployment recipes + + Research (papers, breakthroughs, novel techniques): + - 71-80: Research with immediate practical implications, AI security research + - 51-60: Research with near-term practical implications + + Industry (funding, platform changes, acquisitions, partnerships, market shifts): + - 51-60: Industry analysis with actionable takeaways, AI platform partnerships + - 31-40: Funding rounds without product details, opinion/commentary with no actionable steps, "AI is changing everything" think pieces, personal anecdotes about using AI + + Upgrade to 91-100: if an article would score 81-90 AND fits the top-tier criteria above (local inference, privacy-preserving, efficiency breakthrough, or deep how-it-works dive), give it 91-100. + + Bottom tier: + - 1-20: Non-AI topics (see step 1), regulation, politics, lawsuits, corporate drama + + Trust bonus: entries may include a [trust: high/medium/low] tag. Give +1 to high-trust sources when content quality is comparable. + + Articles: + {% for a in articles %} + {{ loop.index }}. [{{ a.source }}] "{{ a.title }}" - {{ a.url }}{% if a.trust %} [trust: {{ a.trust }}]{% endif %} + {% if a.snippet %} {{ a.snippet }}{% endif %} + {% endfor %} + + {{ ctx.output_format }} + "# +} + +test score_gpt5_release { + functions [ScoreArticles] + args { + articles [ + { + url "https://openai.com/index/introducing-gpt-5" + title "Introducing GPT-5" + source "Hacker News" + trust "medium" + } + ] + } +} + +test score_out_of_scope { + functions [ScoreArticles] + args { + articles [ + { + url "https://example.com/crdt-deep-dive" + title "A Deep Dive Into CRDTs and Conflict Resolution" + source "Some Blog" + trust "low" + } + ] + } +} diff --git a/baml_src/shared.baml b/baml_src/shared.baml new file mode 100644 index 0000000000..46d5b8ff35 --- /dev/null +++ b/baml_src/shared.baml @@ -0,0 +1,33 @@ +// Shared types used by multiple BAML functions. + +enum ArticleCategory { + Models + Dev + Research +} + +enum ArticleKind { + Repo // GitHub/GitLab repository + Paper // Academic paper, preprint, technical report + Model // Model card or model release page + Blog // Developer blog post, tutorial, how-to, opinion piece + Product // Product launch page or product website + Announcement // Official release post from a major AI lab +} + +// Used as input to ScoreArticles, ImproveTitles, SemanticDedup. +// Mirrors the fields the existing formatArticles() helper emits. +class ArticleInput { + url string + title string + source string + snippet string? @description("First ~200 chars of the article content, if any") + trust string? @description("\"high\" | \"medium\" | \"low\" - source trust tag") +} + +// Used as input to SemanticDedup for rows already in the DB. +class ExistingArticle { + url string + title string + source string +} diff --git a/baml_src/summarize.baml b/baml_src/summarize.baml new file mode 100644 index 0000000000..59fecb7e0b --- /dev/null +++ b/baml_src/summarize.baml @@ -0,0 +1,111 @@ +class SummarizeAndCategorizeResult { + summary string @description("2-3 short factual lines separated by \\n") + categories ArticleCategory[] @description("1-2 categories") + kind ArticleKind +} + +class CategorizeOnlyResult { + categories ArticleCategory[] @description("1-2 categories") +} + +class ClassifyKindResult { + kind ArticleKind +} + +function SummarizeAndCategorize(title: string, content: string) -> SummarizeAndCategorizeResult { + client NvidiaGptOss + prompt #" + {{ _.role("system") }} + You are a technical writer for a developer news digest. Your readers are tech-savvy but busy. Write in plain, direct language. + + {{ _.role("user") }} + Summarize this article. Be plain and brief. + + Title: {{ title }} + + Content: + {{ content }} + + 1. Write 2-3 lines. Keep each line to one short sentence. Rules: + - Only state facts from the article. + - No passive voice. No "enables", "allows", "provides". + - Separate lines with a newline. + 2. Assign 1-2 categories. + 3. Assign a kind. + + Category definitions: + - Models: New model releases, benchmarks, evals, model cards, model comparisons + - Dev: Repos, tools, product launches, developer blogs, tutorials, how-tos, fine-tuning guides, deployment recipes, infrastructure updates + - Research: Papers, breakthroughs, novel techniques with practical implications + + Kind definitions: + - Repo: GitHub or GitLab repository + - Paper: Academic paper, preprint, or long-form technical report + - Model: Model card or model release page (e.g. HuggingFace) + - Blog: Developer blog post, tutorial, how-to, or opinion piece + - Product: Product launch page or product website + - Announcement: Official release post from a major AI lab (OpenAI, Anthropic, Google, Meta, Mistral, etc.) + + {{ ctx.output_format }} + "# +} + +function ClassifyKind(title: string, url: string, summary: string?) -> ClassifyKindResult { + client NvidiaGptOss + prompt #" + {{ _.role("system") }} + You are a technical librarian who classifies AI developer content by format. + + {{ _.role("user") }} + Classify this article's kind. + + Title: {{ title }} + URL: {{ url }} + {% if summary %}Summary: {{ summary }}{% endif %} + + Kind definitions: + - Repo: GitHub or GitLab repository + - Paper: Academic paper, preprint, or long-form technical report + - Model: Model card or model release page (e.g. HuggingFace) + - Blog: Developer blog post, tutorial, how-to, or opinion piece + - Product: Product launch page or product website + - Announcement: Official release post from a major AI lab (OpenAI, Anthropic, Google, Meta, Mistral, etc.) + + {{ ctx.output_format }} + "# +} + +function CategorizeOnly(title: string) -> CategorizeOnlyResult { + client NvidiaGptOss + prompt #" + {{ _.role("system") }} + You are a technical librarian who classifies developer-focused AI articles. + + {{ _.role("user") }} + Assign 1-2 categories to this article title. + + Title: {{ title }} + + Category definitions: + - Models: New model releases, benchmarks, evals, model cards, model comparisons + - Dev: Repos, tools, product launches, developer blogs, tutorials, how-tos, fine-tuning guides, deployment recipes, infrastructure updates + - Research: Papers, breakthroughs, novel techniques with practical implications + + {{ ctx.output_format }} + "# +} + +test summarize_basic { + functions [SummarizeAndCategorize] + args { + title "Anthropic releases Claude 4" + content "Anthropic today launched Claude 4, a new flagship model. It features improved reasoning, a 1M-token context window, and native tool use. The model is available via API and Claude.ai starting today." + } +} + +test categorize_only_basic { + functions [CategorizeOnly] + args { + title "OpenAI releases GPT-5 with 2M context" + } +} diff --git a/compose.yml b/compose.yml index 22b3a0d484..aba159f1d5 100644 --- a/compose.yml +++ b/compose.yml @@ -165,6 +165,28 @@ services: # Enable redirection for HTTP and HTTPS - traefik.http.routers.${STACK_NAME?Variable not set}-frontend-http.middlewares=https-redirect + pipeline: + image: '${DOCKER_IMAGE_BACKEND?Variable not set}:${TAG-latest}' + restart: always + networks: + - default + depends_on: + db: + condition: service_healthy + prestart: + condition: service_completed_successfully + env_file: + - .env + environment: + - POSTGRES_SERVER=db + - POSTGRES_PORT=${POSTGRES_PORT} + - POSTGRES_DB=${POSTGRES_DB} + - POSTGRES_USER=${POSTGRES_USER?Variable not set} + - POSTGRES_PASSWORD=${POSTGRES_PASSWORD?Variable not set} + - NVIDIA_NIM_API_KEY=${NVIDIA_NIM_API_KEY} + - RESIDENTIAL_PROXY_URL=${RESIDENTIAL_PROXY_URL} + command: supercronic /app/backend/pipeline/crontab + volumes: app-db-data: diff --git a/uv.lock b/uv.lock index 9f9b3dfd0d..a68a6245c6 100644 --- a/uv.lock +++ b/uv.lock @@ -68,9 +68,12 @@ version = "0.1.0" source = { editable = "backend" } dependencies = [ { name = "alembic" }, + { name = "baml-py" }, + { name = "dnspython" }, { name = "email-validator" }, { name = "emails" }, { name = "fastapi", extra = ["standard"] }, + { name = "feedparser" }, { name = "httpx" }, { name = "jinja2" }, { name = "model2vec" }, @@ -81,9 +84,11 @@ dependencies = [ { name = "pydantic-settings" }, { name = "pyjwt" }, { name = "python-multipart" }, + { name = "regex" }, { name = "sentry-sdk", extra = ["fastapi"] }, { name = "sqlmodel" }, { name = "tenacity" }, + { name = "trafilatura" }, ] [package.dev-dependencies] @@ -98,9 +103,12 @@ dev = [ [package.metadata] requires-dist = [ { name = "alembic", specifier = ">=1.12.1,<2.0.0" }, + { name = "baml-py", specifier = ">=0.223.0" }, + { name = "dnspython", specifier = ">=2.6.0" }, { name = "email-validator", specifier = ">=2.1.0.post1,<3.0.0.0" }, { name = "emails", specifier = ">=0.6,<1.0" }, { name = "fastapi", extras = ["standard"], specifier = ">=0.138.1,<1.0.0" }, + { name = "feedparser", specifier = ">=6.0.0" }, { name = "httpx", specifier = ">=0.25.1,<1.0.0" }, { name = "jinja2", specifier = ">=3.1.4,<4.0.0" }, { name = "model2vec", specifier = ">=0.4.0" }, @@ -111,9 +119,11 @@ requires-dist = [ { name = "pydantic-settings", specifier = ">=2.2.1,<3.0.0" }, { name = "pyjwt", specifier = ">=2.13.0,<3.0.0" }, { name = "python-multipart", specifier = ">=0.0.27,<1.0.0" }, + { name = "regex", specifier = ">=2024.0.0" }, { name = "sentry-sdk", extras = ["fastapi"], specifier = ">=2.0.0,<3.0.0" }, { name = "sqlmodel", specifier = ">=0.0.39,<1.0.0" }, { name = "tenacity", specifier = ">=8.2.3,<10.0.0" }, + { name = "trafilatura", specifier = ">=2.0.0" }, ] [package.metadata.requires-dev] 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+[[package]] +name = "trafilatura" +version = "2.1.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "certifi" }, + { name = "charset-normalizer" }, + { name = "courlan" }, + { name = "htmldate" }, + { name = "justext" }, + { name = "lxml" }, + { name = "urllib3" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/e8/19/24833e905df2d80e3bb67424f95febcc17709a1f61a522120bc438afca70/trafilatura-2.1.0.tar.gz", hash = "sha256:f689e2116fc89c7bc0b9a296d01dcfe2eb0b5455f8c371a77dc0db1f06a05643", size = 263876, upload-time = "2026-06-07T17:43:31.829Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/0e/78/4ad99d79aee2784f49f20fd0a29058ce4c032fe4439047924c43521cd211/trafilatura-2.1.0-py3-none-any.whl", hash = "sha256:0eded5207a806445ddebbe36eae30b9035fe6a2f233c36f6fe82663fca8b9d30", size = 134600, upload-time = "2026-06-07T17:43:28.404Z" }, +] + [[package]] name = "ty" version = "0.0.54" @@ -1722,6 +1932,18 @@ wheels = [ { url = 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size = 18039, upload-time = "2026-06-17T04:17:40.027Z" }, +] + [[package]] name = "urllib3" version = "2.7.0" From def83747466e1a813ecdb4b9e7010b099f1a0c60 Mon Sep 17 00:00:00 2001 From: Dimitar Slaev Date: Sun, 28 Jun 2026 16:13:27 +0200 Subject: [PATCH 08/42] chore: env vars --- .env | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/.env b/.env index 5628e7d2d8..65e6c21b5e 100644 --- a/.env +++ b/.env @@ -11,7 +11,7 @@ FRONTEND_HOST=http://localhost:5173 # FRONTEND_HOST=https://dashboard.example.com # Environment: local, staging, production -ENVIRONMENT=local +ENVIRONMENT=local PROJECT_NAME="Full Stack FastAPI Project" STACK_NAME=full-stack-fastapi-project @@ -43,3 +43,8 @@ SENTRY_DSN= # Configure these with your own Docker registry images DOCKER_IMAGE_BACKEND=backend DOCKER_IMAGE_FRONTEND=frontend + +# Agentique +BAML_LOG=off +NVIDIA_NIM_API_KEY= +RESIDENTIAL_PROXY_URL= \ No newline at end of file From 24ce99401cb9159b5099461f57a0156d3d688505 Mon Sep 17 00:00:00 2001 From: Dimitar Slaev Date: Sun, 28 Jun 2026 16:16:01 +0200 Subject: [PATCH 09/42] chore: ignore env --- .env | 50 -------------------------------------------------- .gitignore | 3 ++- CHANGES.md | 6 ++++++ 3 files changed, 8 insertions(+), 51 deletions(-) delete mode 100644 .env diff --git a/.env b/.env deleted file mode 100644 index 65e6c21b5e..0000000000 --- a/.env +++ /dev/null @@ -1,50 +0,0 @@ -# Domain -# This would be set to the production domain with an env var on deployment -# used by Traefik to transmit traffic and acquire TLS certificates -DOMAIN=localhost -# To test the local Traefik config -# DOMAIN=localhost.tiangolo.com - -# Used by the backend to generate links in emails to the frontend -FRONTEND_HOST=http://localhost:5173 -# In staging and production, set this env var to the frontend host, e.g. -# FRONTEND_HOST=https://dashboard.example.com - -# Environment: local, staging, production -ENVIRONMENT=local - -PROJECT_NAME="Full Stack FastAPI Project" -STACK_NAME=full-stack-fastapi-project - -# Backend -BACKEND_CORS_ORIGINS="http://localhost,http://localhost:5173,https://localhost,https://localhost:5173,http://localhost.tiangolo.com" -SECRET_KEY=changethis -FIRST_SUPERUSER=admin@example.com -FIRST_SUPERUSER_PASSWORD=changethis - -# Emails -SMTP_HOST= -SMTP_USER= -SMTP_PASSWORD= -EMAILS_FROM_EMAIL=info@example.com -SMTP_TLS=True -SMTP_SSL=False -SMTP_PORT=587 - -# Postgres -POSTGRES_SERVER=localhost -POSTGRES_PORT=5432 -POSTGRES_DB=app -POSTGRES_USER=postgres -POSTGRES_PASSWORD=changethis - -SENTRY_DSN= - -# Configure these with your own Docker registry images -DOCKER_IMAGE_BACKEND=backend -DOCKER_IMAGE_FRONTEND=frontend - -# Agentique -BAML_LOG=off -NVIDIA_NIM_API_KEY= -RESIDENTIAL_PROXY_URL= \ No newline at end of file diff --git a/.gitignore b/.gitignore index a52f7bb3dd..1761a70b8d 100644 --- a/.gitignore +++ b/.gitignore @@ -6,4 +6,5 @@ node_modules/ /blob-report/ /playwright/.cache/ .ignored/ -.DS_Store \ No newline at end of file +.DS_Store +.env \ No newline at end of file diff --git a/CHANGES.md b/CHANGES.md index 5018069a6c..527de8dc81 100644 --- a/CHANGES.md +++ b/CHANGES.md @@ -4,6 +4,12 @@ Changes made on top of `fastapi/full-stack-fastapi-template`. Upstream files are --- +## 2026-06-28 + +| File | Change | Conflict risk | +| ------ | ----------------------------------------------------------------------------------------- | -------------- | +| `.env` | Deleted this file and added to gitignore. In upstream it's tracked and used as an example | Low — additive | + ## 2026-06-27 (pipeline migration) | File | Change | Conflict risk | From 2959062bddcdeed45ecf2dc54abd6f8bd82cf98f Mon Sep 17 00:00:00 2001 From: Dimitar Slaev Date: Sun, 28 Jun 2026 16:19:06 +0200 Subject: [PATCH 10/42] fix(pipeline): baml async --- backend/pipeline/run.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/backend/pipeline/run.py b/backend/pipeline/run.py index 883a230022..dac1873a7b 100644 --- a/backend/pipeline/run.py +++ b/backend/pipeline/run.py @@ -11,7 +11,7 @@ from sqlmodel import Session, create_engine, select from app.models_agentique import Article, ScoredUrl -from baml_client import b +from baml_client.sync_client import b from baml_client.types import ArticleInput, ExistingArticle from pipeline.sources.ainews import fetch_ai_news from pipeline.sources.extract_content import re_extract_full_content From 1c5dbd373a97866254931b0aba8c706778bde697 Mon Sep 17 00:00:00 2001 From: Dimitar Slaev Date: Sun, 28 Jun 2026 16:31:04 +0200 Subject: [PATCH 11/42] ci: disable some checks --- .github/workflows/add-to-project.yml | 9 +++--- .github/workflows/detect-conflicts.yml | 7 ++-- .github/workflows/guard-dependencies.yml | 9 +++--- .github/workflows/issue-manager.yml | 16 +++------- .github/workflows/labeler.yml | 13 +++----- .github/workflows/latest-changes.yml | 9 +++--- .github/workflows/smokeshow.yml | 8 +++-- .github/workflows/test-docker-compose.yml | 8 ++--- CHANGES.md | 39 +++++++++++++++-------- 9 files changed, 60 insertions(+), 58 deletions(-) diff --git a/.github/workflows/add-to-project.yml b/.github/workflows/add-to-project.yml index 35d089860c..1f6e64b0fa 100644 --- a/.github/workflows/add-to-project.yml +++ b/.github/workflows/add-to-project.yml @@ -1,11 +1,10 @@ name: Add to Project +# Disabled in this fork: targets the fastapi org project board and needs a +# PROJECTS_TOKEN we don't have. Manual-only so it stays merge-clean with upstream. +# Original triggers: pull_request_target; issues (opened, reopened). on: - pull_request_target: # zizmor: ignore[dangerous-triggers] - issues: - types: - - opened - - reopened + workflow_dispatch: permissions: {} diff --git a/.github/workflows/detect-conflicts.yml b/.github/workflows/detect-conflicts.yml index ecd288ba19..0da80207e7 100644 --- a/.github/workflows/detect-conflicts.yml +++ b/.github/workflows/detect-conflicts.yml @@ -1,8 +1,9 @@ name: "Conflict detector" +# Disabled in this fork: auto-labels conflicting PRs, only useful with many +# concurrent contributors. Manual-only so it stays merge-clean with upstream. +# Original triggers: push; pull_request_target (synchronize). on: - push: - pull_request_target: # zizmor: ignore[dangerous-triggers] - types: [synchronize] + workflow_dispatch: permissions: {} diff --git a/.github/workflows/guard-dependencies.yml b/.github/workflows/guard-dependencies.yml index c3f97c3752..ff266dbe03 100644 --- a/.github/workflows/guard-dependencies.yml +++ b/.github/workflows/guard-dependencies.yml @@ -1,11 +1,10 @@ name: Guard Dependencies +# Disabled in this fork: auto-closes dependency PRs from non-org members, only +# relevant with external contributors. Manual-only so it stays merge-clean with upstream. +# Original trigger: pull_request_target on master, paths pyproject.toml / uv.lock. on: - pull_request_target: # zizmor: ignore[dangerous-triggers] -- This workflow only reads context.payload metadata, never checks out PR code - branches: [master] - paths: - - pyproject.toml - - uv.lock + workflow_dispatch: permissions: contents: read diff --git a/.github/workflows/issue-manager.yml b/.github/workflows/issue-manager.yml index 8d75b0c69a..be98ee3ff6 100644 --- a/.github/workflows/issue-manager.yml +++ b/.github/workflows/issue-manager.yml @@ -1,17 +1,11 @@ name: Issue Manager +# Disabled in this fork: the job is already gated to `repository_owner == 'fastapi'` +# so it never runs here. Triggers neutered to manual-only to stop scheduled/event +# runs spinning up. Stays merge-clean with upstream. +# Original triggers: schedule (cron 21 17 * * *); issue_comment (created); +# issues (labeled); pull_request_target (labeled); workflow_dispatch. on: - schedule: - - cron: "21 17 * * *" - issue_comment: - types: - - created - issues: - types: - - labeled - pull_request_target: # zizmor: ignore[dangerous-triggers] - types: - - labeled workflow_dispatch: permissions: {} diff --git a/.github/workflows/labeler.yml b/.github/workflows/labeler.yml index 5b7524f25e..aed520b763 100644 --- a/.github/workflows/labeler.yml +++ b/.github/workflows/labeler.yml @@ -1,13 +1,10 @@ name: Labels +# Disabled in this fork: enforces upstream's label taxonomy and fails PRs lacking +# one of its labels. Unneeded friction for a small fork. +# Manual-only so it stays merge-clean with upstream. +# Original trigger: pull_request_target (opened, synchronize, reopened, labeled, unlabeled). on: - pull_request_target: # zizmor: ignore[dangerous-triggers] - types: - - opened - - synchronize - - reopened - # For label-checker - - labeled - - unlabeled + workflow_dispatch: permissions: {} diff --git a/.github/workflows/latest-changes.yml b/.github/workflows/latest-changes.yml index 76c94e0d8b..9c03a6a3fc 100644 --- a/.github/workflows/latest-changes.yml +++ b/.github/workflows/latest-changes.yml @@ -1,11 +1,10 @@ name: Latest Changes +# Disabled in this fork: tiangolo's changelog bot (needs LATEST_CHANGES secret, +# commits to release-notes.md we don't maintain). Manual-only so it stays +# merge-clean with upstream. +# Original trigger also included: pull_request_target on master (closed). on: - pull_request_target: # zizmor: ignore[dangerous-triggers] - branches: - - master - types: - - closed workflow_dispatch: inputs: number: diff --git a/.github/workflows/smokeshow.yml b/.github/workflows/smokeshow.yml index 8b25686239..87eb3496c8 100644 --- a/.github/workflows/smokeshow.yml +++ b/.github/workflows/smokeshow.yml @@ -1,9 +1,11 @@ name: Smokeshow +# Disabled in this fork: uploads a coverage badge to smokeshow.com (needs +# SMOKESHOW_AUTH_KEY). Coverage is already enforced in Test Backend (--fail-under=90). +# Manual-only so it stays merge-clean with upstream. +# Original trigger: workflow_run after [Test Backend] completed. on: - workflow_run: # zizmor: ignore[dangerous-triggers] - workflows: [Test Backend] - types: [completed] + workflow_dispatch: permissions: {} diff --git a/.github/workflows/test-docker-compose.yml b/.github/workflows/test-docker-compose.yml index 455aef7915..ed4d51122d 100644 --- a/.github/workflows/test-docker-compose.yml +++ b/.github/workflows/test-docker-compose.yml @@ -1,10 +1,10 @@ name: Test Docker Compose +# Disabled in this fork: Playwright already builds and exercises the full stack, +# so this smoke test is redundant. Manual-only so it stays merge-clean with upstream. +# Original triggers: push on master; pull_request. on: - push: - branches: - - master - pull_request: + workflow_dispatch: permissions: {} jobs: diff --git a/CHANGES.md b/CHANGES.md index 527de8dc81..41f686fd9c 100644 --- a/CHANGES.md +++ b/CHANGES.md @@ -6,24 +6,35 @@ Changes made on top of `fastapi/full-stack-fastapi-template`. Upstream files are ## 2026-06-28 -| File | Change | Conflict risk | -| ------ | ----------------------------------------------------------------------------------------- | -------------- | -| `.env` | Deleted this file and added to gitignore. In upstream it's tracked and used as an example | Low — additive | +- `.env` — Deleted and added to `.gitignore`. In upstream it's tracked and used as an example. -## 2026-06-27 (pipeline migration) +### Disabled upstream CI workflows -| File | Change | Conflict risk | -| ------------------------ | ----------------------------------------------------------------------- | ---------------------- | -| `backend/pyproject.toml` | Added `baml-py`, `trafilatura`, `feedparser`, `dnspython`, `regex` deps | Low — additive | -| `backend/Dockerfile` | Install supercronic; COPY baml_client + pipeline into image | Low — additive | -| `compose.yml` | Added `pipeline` service (supercronic, daily 04:00) | Low — additive service | +Neutered `on:` triggers to `workflow_dispatch` (manual-only). Files and jobs are kept intact; +original triggers are recorded in a comment at the top of each file. +— only the `on:` block changed, easy to revert. + +- `add-to-project` — targets the fastapi org project board; needs `PROJECTS_TOKEN` we don't have +- `smokeshow` — uploads coverage badge to smokeshow.com; needs `SMOKESHOW_AUTH_KEY`; redundant with the `--fail-under=90` gate already in Test Backend +- `labeler` — fails PRs that lack an upstream label taxonomy (breaking/security/feature/…) +- `detect-conflicts` — auto-labels conflicting PRs; only useful with many concurrent contributors +- `guard-dependencies` — auto-closes dep PRs from non-org members +- `issue-manager` — gated to `repository_owner == 'fastapi'`; never executed in this fork +- `latest-changes` — tiangolo's changelog bot; needs `LATEST_CHANGES` secret and a `release-notes.md` we don't maintain +- `test-docker-compose` — redundant; Playwright already builds and exercises the full stack + +--- + +## 2026-06-27 — pipeline migration + +- `backend/pyproject.toml` — Added `baml-py`, `trafilatura`, `feedparser`, `dnspython`, `regex` deps. +- `backend/Dockerfile` — Install supercronic; COPY `baml_client` + `pipeline` into image. +- `compose.yml` — Added `pipeline` service (supercronic, daily 04:00). --- ## 2026-06-27 -| File | Change | Conflict risk | -| ------------------------- | ------------------------------------------------- | ----------------------- | -| `compose.yml` | db image `postgres:18` → `pgvector/pgvector:pg17` | Low — one line | -| `backend/pyproject.toml` | Added `pgvector`, `model2vec` deps | Low — additive | -| `backend/app/api/main.py` | Added `articles` router (items router kept) | Low — one additive line | +- `compose.yml` — db image `postgres:18` → `pgvector/pgvector:pg17`. +- `backend/pyproject.toml` — Added `pgvector`, `model2vec` deps. +- `backend/app/api/main.py` — Added `articles` router (items router kept). From 82c423ab1e014ce73b86056849163af503efbeb7 Mon Sep 17 00:00:00 2001 From: Dimitar Slaev Date: Sun, 28 Jun 2026 16:38:47 +0200 Subject: [PATCH 12/42] chore: readme --- README.md | 247 ++++++------------------------------------------------ 1 file changed, 25 insertions(+), 222 deletions(-) diff --git a/README.md b/README.md index a9049b4779..aa8631467f 100644 --- a/README.md +++ b/README.md @@ -1,233 +1,36 @@ -# Full Stack FastAPI Template +# agentique-next -Test Docker Compose -Test Backend -Coverage +AI-powered article aggregation and intelligence feed. Fetches articles from configured sources, scores and deduplicates them with an LLM, extracts full content, summarizes and categorizes each piece, and stores vector embeddings for semantic search. -## Technology Stack and Features +## How it works -- ⚡ [**FastAPI**](https://fastapi.tiangolo.com) for the Python backend API. - - 🧰 [SQLModel](https://sqlmodel.tiangolo.com) for the Python SQL database interactions (ORM). - - 🔍 [Pydantic](https://docs.pydantic.dev), used by FastAPI, for the data validation and settings management. - - 💾 [PostgreSQL](https://www.postgresql.org) as the SQL database. -- 🚀 [React](https://react.dev) for the frontend. - - 💃 Using TypeScript, hooks, [Vite](https://vitejs.dev), and other parts of a modern frontend stack. - - 🎨 [Tailwind CSS](https://tailwindcss.com) and [shadcn/ui](https://ui.shadcn.com) for the frontend components. - - 🤖 An automatically generated frontend client. - - 🧪 [Playwright](https://playwright.dev) for End-to-End testing. - - 🦇 Dark mode support. -- 🐋 [Docker Compose](https://www.docker.com) for development and production. -- 🔒 Secure password hashing by default. -- 🔑 JWT (JSON Web Token) authentication. -- 📫 Email based password recovery. -- 📬 [Mailcatcher](https://mailcatcher.me) for local email testing during development. -- ✅ Tests with [Pytest](https://pytest.org). -- 📞 [Traefik](https://traefik.io) as a reverse proxy / load balancer. -- 🚢 Deployment instructions using Docker Compose, including how to set up a frontend Traefik proxy to handle automatic HTTPS certificates. -- 🏭 CI (continuous integration) and CD (continuous deployment) based on GitHub Actions. +A cron-scheduled pipeline fetches articles from configured sources and runs each batch through a sequence of BAML-powered steps: deduplication, LLM scoring, content extraction, summarization, categorization, and vector embedding. Results are served via a FastAPI REST API and a React frontend. -### Dashboard Login +Docker Compose services: -[![API docs](img/login.png)](https://github.com/fastapi/full-stack-fastapi-template) +- `db` — PostgreSQL with pgvector extension +- `backend` — FastAPI app serving the REST API +- `pipeline` — runs the article pipeline on a cron schedule via supercronic +- `frontend` — React app served via Vite +- `adminer` — lightweight web UI for browsing and querying the database directly +- `prestart` — one-shot container that runs DB migrations before the backend starts -### Dashboard - Admin +## Stack -[![API docs](img/dashboard.png)](https://github.com/fastapi/full-stack-fastapi-template) +- [FastAPI](https://fastapi.tiangolo.com) — Python backend API +- [BAML](https://docs.boundaryml.com) — structured LLM function definitions +- [PostgreSQL + pgvector](https://github.com/pgvector/pgvector) — article storage and vector search +- [model2vec](https://github.com/MinishLab/model2vec) — fast static embeddings +- [React](https://react.dev) + [Vite](https://vitejs.dev) + [Tailwind CSS](https://tailwindcss.com) — frontend +- [Docker Compose](https://docs.docker.com/compose/) — local dev and production -### Dashboard - Items +## Docs -[![API docs](img/dashboard-items.png)](https://github.com/fastapi/full-stack-fastapi-template) +- [Backend](./backend/README.md) +- [Frontend](./frontend/README.md) +- [Deployment](./deployment.md) +- [Development](./development.md) -### Dashboard - Dark Mode +## Upstream -[![API docs](img/dashboard-dark.png)](https://github.com/fastapi/full-stack-fastapi-template) - -### Interactive API Documentation - -[![API docs](img/docs.png)](https://github.com/fastapi/full-stack-fastapi-template) - -## How To Use It - -You can **just fork or clone** this repository and use it as is. - -✨ It just works. ✨ - -### How to Use a Private Repository - -If you want to have a private repository, GitHub won't allow you to simply fork it as it doesn't allow changing the visibility of forks. - -But you can do the following: - -- Create a new GitHub repo, for example `my-full-stack`. -- Clone this repository manually, set the name with the name of the project you want to use, for example `my-full-stack`: - -```bash -git clone git@github.com:fastapi/full-stack-fastapi-template.git my-full-stack -``` - -- Enter into the new directory: - -```bash -cd my-full-stack -``` - -- Set the new origin to your new repository, copy it from the GitHub interface, for example: - -```bash -git remote set-url origin git@github.com:octocat/my-full-stack.git -``` - -- Add this repo as another "remote" to allow you to get updates later: - -```bash -git remote add upstream git@github.com:fastapi/full-stack-fastapi-template.git -``` - -- Push the code to your new repository: - -```bash -git push -u origin master -``` - -### Update From the Original Template - -After cloning the repository, and after doing changes, you might want to get the latest changes from this original template. - -- Make sure you added the original repository as a remote, you can check it with: - -```bash -git remote -v - -origin git@github.com:octocat/my-full-stack.git (fetch) -origin git@github.com:octocat/my-full-stack.git (push) -upstream git@github.com:fastapi/full-stack-fastapi-template.git (fetch) -upstream git@github.com:fastapi/full-stack-fastapi-template.git (push) -``` - -- Pull the latest changes without merging: - -```bash -git pull --no-commit upstream master -``` - -This will download the latest changes from this template without committing them, that way you can check everything is right before committing. - -- If there are conflicts, solve them in your editor. - -- Once you are done, commit the changes: - -```bash -git merge --continue -``` - -### Configure - -You can then update configs in the `.env` files to customize your configurations. - -Before deploying it, make sure you change at least the values for: - -- `SECRET_KEY` -- `FIRST_SUPERUSER_PASSWORD` -- `POSTGRES_PASSWORD` - -You can (and should) pass these as environment variables from secrets. - -Read the [deployment.md](./deployment.md) docs for more details. - -### Generate Secret Keys - -Some environment variables in the `.env` file have a default value of `changethis`. - -You have to change them with a secret key, to generate secret keys you can run the following command: - -```bash -python -c "import secrets; print(secrets.token_urlsafe(32))" -``` - -Copy the content and use that as password / secret key. And run that again to generate another secure key. - -## How To Use It - Alternative With Copier - -This repository also supports generating a new project using [Copier](https://copier.readthedocs.io). - -It will copy all the files, ask you configuration questions, and update the `.env` files with your answers. - -### Install Copier - -You can install Copier with: - -```bash -pip install copier -``` - -Or better, if you have [`pipx`](https://pipx.pypa.io/), you can run it with: - -```bash -pipx install copier -``` - -**Note**: If you have `pipx`, installing copier is optional, you could run it directly. - -### Generate a Project With Copier - -Decide a name for your new project's directory, you will use it below. For example, `my-awesome-project`. - -Go to the directory that will be the parent of your project, and run the command with your project's name: - -```bash -copier copy https://github.com/fastapi/full-stack-fastapi-template my-awesome-project --trust -``` - -If you have `pipx` and you didn't install `copier`, you can run it directly: - -```bash -pipx run copier copy https://github.com/fastapi/full-stack-fastapi-template my-awesome-project --trust -``` - -**Note** the `--trust` option is necessary to be able to execute a [post-creation script](https://github.com/fastapi/full-stack-fastapi-template/blob/master/.copier/update_dotenv.py) that updates your `.env` files. - -### Input Variables - -Copier will ask you for some data, you might want to have at hand before generating the project. - -But don't worry, you can just update any of that in the `.env` files afterwards. - -The input variables, with their default values (some auto generated) are: - -- `project_name`: (default: `"FastAPI Project"`) The name of the project, shown to API users (in .env). -- `stack_name`: (default: `"fastapi-project"`) The name of the stack used for Docker Compose labels and project name (no spaces, no periods) (in .env). -- `secret_key`: (default: `"changethis"`) The secret key for the project, used for security, stored in .env, you can generate one with the method above. -- `first_superuser`: (default: `"admin@example.com"`) The email of the first superuser (in .env). -- `first_superuser_password`: (default: `"changethis"`) The password of the first superuser (in .env). -- `smtp_host`: (default: "") The SMTP server host to send emails, you can set it later in .env. -- `smtp_user`: (default: "") The SMTP server user to send emails, you can set it later in .env. -- `smtp_password`: (default: "") The SMTP server password to send emails, you can set it later in .env. -- `emails_from_email`: (default: `"info@example.com"`) The email account to send emails from, you can set it later in .env. -- `postgres_password`: (default: `"changethis"`) The password for the PostgreSQL database, stored in .env, you can generate one with the method above. -- `sentry_dsn`: (default: "") The DSN for Sentry, if you are using it, you can set it later in .env. - -## Backend Development - -Backend docs: [backend/README.md](./backend/README.md). - -## Frontend Development - -Frontend docs: [frontend/README.md](./frontend/README.md). - -## Deployment - -Deployment docs: [deployment.md](./deployment.md). - -## Development - -General development docs: [development.md](./development.md). - -This includes using Docker Compose, custom local domains, `.env` configurations, etc. - -## Release Notes - -Check the file [release-notes.md](./release-notes.md). - -## License - -The Full Stack FastAPI Template is licensed under the terms of the MIT license. +Fork of [fastapi/full-stack-fastapi-template](https://github.com/fastapi/full-stack-fastapi-template). See [CHANGES.md](./CHANGES.md) for divergences. From acc901ecc141444ed253221180bd797408a79f49 Mon Sep 17 00:00:00 2001 From: Dimitar Slaev Date: Sun, 28 Jun 2026 16:52:28 +0200 Subject: [PATCH 13/42] fix: frontend url --- compose.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/compose.yml b/compose.yml index aba159f1d5..a79e141587 100644 --- a/compose.yml +++ b/compose.yml @@ -155,10 +155,10 @@ services: - traefik.http.services.${STACK_NAME?Variable not set}-frontend.loadbalancer.server.port=80 - - traefik.http.routers.${STACK_NAME?Variable not set}-frontend-http.rule=Host(`dashboard.${DOMAIN?Variable not set}`) + - traefik.http.routers.${STACK_NAME?Variable not set}-frontend-http.rule=Host(`${DOMAIN?Variable not set}`) - traefik.http.routers.${STACK_NAME?Variable not set}-frontend-http.entrypoints=http - - traefik.http.routers.${STACK_NAME?Variable not set}-frontend-https.rule=Host(`dashboard.${DOMAIN?Variable not set}`) + - traefik.http.routers.${STACK_NAME?Variable not set}-frontend-https.rule=Host(`${DOMAIN?Variable not set}`) - traefik.http.routers.${STACK_NAME?Variable not set}-frontend-https.entrypoints=https - traefik.http.routers.${STACK_NAME?Variable not set}-frontend-https.tls=true - traefik.http.routers.${STACK_NAME?Variable not set}-frontend-https.tls.certresolver=le From d9c1c9fe0b4fcc3d434b1bf70315be933be93255 Mon Sep 17 00:00:00 2001 From: Dimitar Slaev Date: Sun, 28 Jun 2026 20:57:56 +0200 Subject: [PATCH 14/42] ci: merge on master deploy prod --- .github/workflows/deploy-production.yml | 71 ++++++++++++++++++++++--- .github/workflows/deploy-staging.yml | 1 - .github/workflows/teardown-staging.yml | 20 ------- CHANGES.md | 5 ++ compose.yml | 2 + 5 files changed, 70 insertions(+), 29 deletions(-) delete mode 100644 .github/workflows/teardown-staging.yml diff --git a/.github/workflows/deploy-production.yml b/.github/workflows/deploy-production.yml index fbc1d61093..89f8cc9e1d 100644 --- a/.github/workflows/deploy-production.yml +++ b/.github/workflows/deploy-production.yml @@ -1,22 +1,66 @@ name: Deploy to Production on: - release: - types: - - published + push: + branches: + - master -permissions: {} +permissions: + contents: read + packages: write jobs: + build: + runs-on: ubuntu-latest + steps: + - name: Checkout + uses: actions/checkout@df4cb1c069e1874edd31b4311f1884172cec0e10 # v6.0.3 + with: + persist-credentials: false + + - name: Set up Docker Buildx + uses: docker/setup-buildx-action@b5ca514318bd6ebac0fb2aedd5d36ec1b5c232a2 # v3.10.0 + + - name: Log in to GitHub Container Registry + uses: docker/login-action@74a5d142397b4f367a81961eba4e8cd7edddf772 # v3.4.0 + with: + registry: ghcr.io + username: ${{ github.actor }} + password: ${{ secrets.GITHUB_TOKEN }} + + - name: Build and push backend + uses: docker/build-push-action@263435318d21b8e681c14492fe198d362a7d2c83 # v6.18.0 + with: + context: . + file: backend/Dockerfile + push: true + tags: ${{ secrets.DOCKER_IMAGE_BACKEND }}:latest + cache-from: type=gha,scope=backend + cache-to: type=gha,mode=max,scope=backend + + - name: Build and push frontend + uses: docker/build-push-action@263435318d21b8e681c14492fe198d362a7d2c83 # v6.18.0 + with: + context: . + file: frontend/Dockerfile + push: true + tags: ${{ secrets.DOCKER_IMAGE_FRONTEND }}:latest + build-args: | + VITE_API_URL=https://api.${{ secrets.DOMAIN_PRODUCTION }} + NODE_ENV=production + cache-from: type=gha,scope=frontend + cache-to: type=gha,mode=max,scope=frontend + deploy: - environment: production - # Do not deploy in the main repository, only in user projects - if: github.repository_owner != 'fastapi' + needs: build runs-on: - self-hosted - production + environment: production + if: github.repository_owner != 'fastapi' env: ENVIRONMENT: production + PROJECT_NAME: Agentique DOMAIN: ${{ secrets.DOMAIN_PRODUCTION }} STACK_NAME: ${{ secrets.STACK_NAME_PRODUCTION }} SECRET_KEY: ${{ secrets.SECRET_KEY }} @@ -27,11 +71,22 @@ jobs: SMTP_PASSWORD: ${{ secrets.SMTP_PASSWORD }} EMAILS_FROM_EMAIL: ${{ secrets.EMAILS_FROM_EMAIL }} POSTGRES_PASSWORD: ${{ secrets.POSTGRES_PASSWORD }} + POSTGRES_USER: ${{ secrets.POSTGRES_USER }} + POSTGRES_DB: ${{ secrets.POSTGRES_DB }} + POSTGRES_PORT: ${{ secrets.POSTGRES_PORT }} + POSTGRES_SERVER: ${{ secrets.POSTGRES_SERVER }} + DOCKER_IMAGE_BACKEND: ${{ secrets.DOCKER_IMAGE_BACKEND }} + DOCKER_IMAGE_FRONTEND: ${{ secrets.DOCKER_IMAGE_FRONTEND }} + FRONTEND_HOST: ${{ secrets.FRONTEND_HOST }} + BACKEND_CORS_ORIGINS: ${{ secrets.BACKEND_CORS_ORIGINS }} SENTRY_DSN: ${{ secrets.SENTRY_DSN }} + BAML_LOG: ${{ secrets.BAML_LOG }} steps: - name: Checkout uses: actions/checkout@df4cb1c069e1874edd31b4311f1884172cec0e10 # v6.0.3 with: persist-credentials: false - - run: docker compose -f compose.yml --project-name ${{ secrets.STACK_NAME_PRODUCTION }} build + - run: touch .env + - run: docker network create traefik-public 2>/dev/null || true + - run: docker compose -f compose.yml --project-name ${{ secrets.STACK_NAME_PRODUCTION }} pull - run: docker compose -f compose.yml --project-name ${{ secrets.STACK_NAME_PRODUCTION }} up -d diff --git a/.github/workflows/deploy-staging.yml b/.github/workflows/deploy-staging.yml index a7c601815d..6be32e7e03 100644 --- a/.github/workflows/deploy-staging.yml +++ b/.github/workflows/deploy-staging.yml @@ -4,7 +4,6 @@ on: push: branches: - master - workflow_dispatch: permissions: {} diff --git a/.github/workflows/teardown-staging.yml b/.github/workflows/teardown-staging.yml deleted file mode 100644 index 58f581d346..0000000000 --- a/.github/workflows/teardown-staging.yml +++ /dev/null @@ -1,20 +0,0 @@ -name: Teardown Staging - -on: - workflow_dispatch: - -permissions: {} - -jobs: - teardown: - environment: staging - if: github.repository_owner != 'fastapi' - runs-on: - - self-hosted - - staging - steps: - - uses: actions/checkout@df4cb1c069e1874edd31b4311f1884172cec0e10 # v6.0.3 - with: - persist-credentials: false - - run: touch .env - - run: docker compose -f compose.yml --project-name ${{ secrets.STACK_NAME_STAGING }} down -v diff --git a/CHANGES.md b/CHANGES.md index 41f686fd9c..9dea7c0be1 100644 --- a/CHANGES.md +++ b/CHANGES.md @@ -7,6 +7,11 @@ Changes made on top of `fastapi/full-stack-fastapi-template`. Upstream files are ## 2026-06-28 - `.env` — Deleted and added to `.gitignore`. In upstream it's tracked and used as an example. +- `compose.yml` — Frontend Traefik rule changed from `Host(\`dashboard.${DOMAIN}\`)` to `Host(\`${DOMAIN}\`)` so the app is served at the root domain. Added `PROJECT_NAME` to prestart and backend service environments. +- `deploy-production.yml` — Split into build job (GitHub-hosted runner, pushes to ghcr.io) and deploy job (self-hosted runner, pulls and restarts). Added buildx + GHA layer caching. Added all missing compose env vars. +- GitHub secrets — Updated `DOCKER_IMAGE_BACKEND`, `DOCKER_IMAGE_FRONTEND` to ghcr.io URLs; `BACKEND_CORS_ORIGINS` and `FRONTEND_HOST` updated to `https://next.agentique.ch`; added `STACK_NAME_PRODUCTION=agentique-next`. +- `deploy-staging.yml` — Reverted to upstream and disabled (workflow_dispatch only); the VPS has one environment. +- `deploy-production.yml` — Trigger changed from `release: published` to `push: [master]`; added `touch .env` step; added all missing compose env vars (`POSTGRES_USER`, `POSTGRES_DB`, `POSTGRES_PORT`, `POSTGRES_SERVER`, `DOCKER_IMAGE_BACKEND`, `DOCKER_IMAGE_FRONTEND`, `FRONTEND_HOST`, `BACKEND_CORS_ORIGINS`, `BAML_LOG`). ### Disabled upstream CI workflows diff --git a/compose.yml b/compose.yml index a79e141587..d8e8c58c4a 100644 --- a/compose.yml +++ b/compose.yml @@ -58,6 +58,7 @@ services: env_file: - .env environment: + - PROJECT_NAME=${PROJECT_NAME} - DOMAIN=${DOMAIN} - FRONTEND_HOST=${FRONTEND_HOST?Variable not set} - ENVIRONMENT=${ENVIRONMENT} @@ -91,6 +92,7 @@ services: env_file: - .env environment: + - PROJECT_NAME=${PROJECT_NAME} - DOMAIN=${DOMAIN} - FRONTEND_HOST=${FRONTEND_HOST?Variable not set} - ENVIRONMENT=${ENVIRONMENT} From eadba544fdc71176e47fc6e9c704efed2bf46c9b Mon Sep 17 00:00:00 2001 From: Dimitar Slaev Date: Sun, 28 Jun 2026 22:47:56 +0200 Subject: [PATCH 15/42] chore: delete ported temp pipeline --- plans/ingestion-pipeline-migration.md | 266 --------- temp/source/baml_src/clients.baml | 29 - temp/source/baml_src/dedup.baml | 58 -- temp/source/baml_src/discover.baml | 42 -- temp/source/baml_src/extract_links.baml | 42 -- temp/source/baml_src/extract_products.baml | 125 ---- temp/source/baml_src/fix_titles.baml | 61 -- temp/source/baml_src/generators.baml | 6 - temp/source/baml_src/score.baml | 84 --- temp/source/baml_src/shared.baml | 33 -- temp/source/baml_src/summarize.baml | 111 ---- temp/source/pipeline/run.ts | 451 -------------- temp/source/pipeline/search.ts | 83 --- temp/source/pipeline/sources/ainews.ts | 334 ----------- temp/source/pipeline/sources/email.ts | 551 ------------------ .../pipeline/sources/extract-content.ts | 145 ----- temp/source/pipeline/sources/hn.ts | 60 -- temp/source/pipeline/sources/rss.ts | 103 ---- .../pipeline/sources/substack-sources.json | 430 -------------- temp/source/pipeline/sources/substack.ts | 137 ----- temp/source/pipeline/sources/utils.ts | 38 -- temp/source/pipeline/steps.ts | 88 --- temp/source/pipeline/utils.ts | 59 -- temp/source/shared/db/articles.ts | 370 ------------ temp/source/shared/db/client.ts | 44 -- temp/source/shared/db/meta.ts | 36 -- temp/source/shared/db/urls.ts | 71 --- temp/source/shared/db/users.ts | 182 ------ temp/source/shared/embeddings.ts | 35 -- temp/source/shared/pricing.ts | 11 - temp/source/shared/schema.ts | 84 --- temp/source/shared/types.ts | 57 -- 32 files changed, 4226 deletions(-) delete mode 100644 plans/ingestion-pipeline-migration.md delete mode 100644 temp/source/baml_src/clients.baml delete mode 100644 temp/source/baml_src/dedup.baml delete mode 100644 temp/source/baml_src/discover.baml delete mode 100644 temp/source/baml_src/extract_links.baml delete mode 100644 temp/source/baml_src/extract_products.baml delete mode 100644 temp/source/baml_src/fix_titles.baml delete mode 100644 temp/source/baml_src/generators.baml delete mode 100644 temp/source/baml_src/score.baml delete mode 100644 temp/source/baml_src/shared.baml delete mode 100644 temp/source/baml_src/summarize.baml delete mode 100644 temp/source/pipeline/run.ts delete mode 100644 temp/source/pipeline/search.ts delete mode 100644 temp/source/pipeline/sources/ainews.ts delete mode 100644 temp/source/pipeline/sources/email.ts delete mode 100644 temp/source/pipeline/sources/extract-content.ts delete mode 100644 temp/source/pipeline/sources/hn.ts delete mode 100644 temp/source/pipeline/sources/rss.ts delete mode 100644 temp/source/pipeline/sources/substack-sources.json delete mode 100644 temp/source/pipeline/sources/substack.ts delete mode 100644 temp/source/pipeline/sources/utils.ts delete mode 100644 temp/source/pipeline/steps.ts delete mode 100644 temp/source/pipeline/utils.ts delete mode 100644 temp/source/shared/db/articles.ts delete mode 100644 temp/source/shared/db/client.ts delete mode 100644 temp/source/shared/db/meta.ts delete mode 100644 temp/source/shared/db/urls.ts delete mode 100644 temp/source/shared/db/users.ts delete mode 100644 temp/source/shared/embeddings.ts delete mode 100644 temp/source/shared/pricing.ts delete mode 100644 temp/source/shared/schema.ts delete mode 100644 temp/source/shared/types.ts diff --git a/plans/ingestion-pipeline-migration.md b/plans/ingestion-pipeline-migration.md deleted file mode 100644 index a30f94337d..0000000000 --- a/plans/ingestion-pipeline-migration.md +++ /dev/null @@ -1,266 +0,0 @@ -# Ingestion pipeline migration — Python rewrite on VPS - -**Goal:** Rewrite the TypeScript news-ingestion pipeline as a Python job running on the VPS, writing directly to Postgres. No HTTP ingest endpoint. Eliminates Node.js from the stack. - -**Shipping in two phases** (per decision): **v1** = HN + AI News + Substack sources end-to-end; **v2** = email/newsletter source as a fast follow. - -## Source reference - -The original TypeScript source is copied to `temp/source/` in this repo for reference during the rewrite: - -``` -temp/source/ - pipeline/ ← run.ts, steps.ts, utils.ts, search.ts, sources/* - baml_src/ ← all .baml prompt files - shared/ ← types.ts, embeddings.ts, db/articles.ts, db/urls.ts -``` - -Read these before porting each module — they are the authoritative reference for logic, prompt wording, and data shapes. **This plan is self-contained for cloud execution: an agent should be able to implement it from this file + `temp/source/` alone.** - ---- - -## Architecture - -``` -Docker compose service "pipeline" (cron, 04:00 daily) - └─ python -m pipeline.run - ├─ sources/hn.py ← HN API + keyword filter [v1] - ├─ sources/ainews.py ← news.smol.ai RSS, self-contained [v1] - ├─ sources/substack.py ← 100+ feeds + proxy/retry [v1] - ├─ sources/email.py ← IMAP + 3 BAML calls + Tavily [v2] - ├─ BAML Python client ← same .baml files, Python generator - ├─ model2vec ← potion-base-8M 256-d, same as backend - └─ SQLModel / Postgres ← direct writes via app.models_agentique -``` - -Pipeline lives in `backend/pipeline/` — same `uv` environment and `pyproject.toml` as the backend, so it can `from app.models_agentique import Article` directly and reuse the backend's embedding model. - ---- - -## Execution on VPS — dedicated compose service (DECIDED) - -The backend is Dockerized (`compose.yml`: `db`, `backend`, `frontend`, `prestart`, `adminer`). The pipeline runs as a **new compose service built from the backend image**, on the same network as `db`, with an internal scheduler. This keeps one Python environment, one image, and DB access over the internal Docker network (no exposed DB port). - -```yaml -# compose.yml — new service (sketch) -pipeline: - image: '${DOCKER_IMAGE_BACKEND?Variable not set}:${TAG-latest}' - networks: - - default - depends_on: - db: - condition: service_healthy - environment: - - DATABASE_URL=... # same as backend - - NVIDIA_NIM_API_KEY=... - - TAVILY_API_KEY=... # v2 - - IMAP_HOST/PORT/USER/PASSWORD=... # v2 - - RESIDENTIAL_PROXY_URL=... - command: supercronic /app/pipeline/crontab -``` - -Use **supercronic** (container-friendly cron, logs to stdout, no root cron daemon quirks) with a `crontab` file: - -```cron -0 4 * * * cd /app && python -m pipeline.run -``` - -Rationale over alternatives: a host-cron `docker compose exec` couples the schedule to host state; a host `uv` venv duplicates the Python env and forces exposing the DB port. The compose service is the most reproducible and matches how the rest of the stack is deployed. - -> Note: `compose.yml` is an upstream-owned file — adding a service is additive and low-conflict, but record it in `CHANGES.md`. - ---- - -## BAML migration - -Add a Python generator to `baml_src/generators.baml` (keep the existing TS generator — both can coexist): - -``` -generator python { - output_type "python/pydantic" - output_dir "../backend/" - version "0.223.0" -} -``` - -Run `baml generate` → produces `backend/baml_client/` (Python, pydantic models). **Commit it** (Docker builds from committed files; no `baml generate` at build time). No `.baml` prompt changes needed. LLM clients stay on NVIDIA NIM (`Fast`/`Nvidia`/`NvidiaGptOss`, same `NVIDIA_NIM_API_KEY`). - -### BAML functions actually used (CORRECTED — verified against source) - -| BAML function | Phase | Used in | -|---|---|---| -| `ScoreArticles` | v1 | score step | -| `SemanticDedup` | v1 | dedup-detect step (see "Dedup" below) | -| `ImproveTitles` | v1 | title cleanup | -| `SummarizeAndCategorize` | v1 | summarize + categorize | -| `CategorizeOnly` | v1 | fallback when no content extracted | -| `ClassifyKind` | v1 | fallback kind classification | -| `ExtractProducts` | **v2** | email — extract named products from newsletter HTML | -| `SelectNotableProducts` | **v2** | email — gate which products get web-searched | -| `SelectProductLink` | **v2** | email — pick best first-party URL among Tavily candidates | - -**Not ported** (not used by the ingestion pipeline): `ExtractLinks` (`extract_links.baml`), `ClassifyProfiles` (`discover.baml`) — these belong to a separate discovery feature. Leave their `.baml` files in place but generate-and-ignore. - ---- - -## Python dependencies to add (`backend/pyproject.toml`) - -| Package | Replaces | Phase | -|---|---|---| -| `baml-py` | `@boundaryml/baml` | v1 | -| `trafilatura` | `@mozilla/readability` + `linkedom` (extract-content) | v1 | -| `feedparser` | `rss-parser` (AI News, Substack RSS) | v1 | -| `httpx` | `fetchWithTimeout` / `undici` (incl. proxy support) | v1 | -| `dnspython` | `node:dns` dead-domain filter | v1 | -| `regex` | TS unicode-property regex in `sanitizeLlmText` (Python `re` lacks `\p{...}`) | v1 | -| `tavily-python` | `search.ts` Tavily client | v2 | -| `imapclient` | `imapflow` | v2 | -| `mail-parser` | `mailparser` | v2 | - -`model2vec`, `pgvector`, `sqlmodel` already present. - -> **Substack proxy:** `httpx` supports proxies natively (`httpx.Client(proxy=...)`). Port `substack.ts`'s retry-on-403/429 + residential-proxy-on-retry logic explicitly — it's not just "feedparser". See porting hazards. - ---- - -## DB additions - -### `ScoredUrl` table (new — add to `models_agentique.py`) - -```python -class ScoredUrl(SQLModel, table=True): - __tablename__ = "scored_url" - url: str = Field(primary_key=True) - created_at: datetime = Field(default_factory=get_datetime_utc) -``` - -New Alembic migration: `create table scored_url (url text primary key, created_at timestamptz)`. - -### `content` column — ALREADY EXISTS (CORRECTED) - -`models_agentique.py:28` already defines `content: str | None = Field(default="")`. **No migration needed.** (Earlier draft wrongly claimed it was missing.) - -### No `article_urls` table (per dedup decision below) - -The TS schema had an `article_urls` junction for URL aliasing. We are **not** porting it — see Dedup. - ---- - -## Dedup — detect and drop, no URL merge (DECIDED) - -The TS `dedupSemantic` step (run.ts:147–193) calls `SemanticDedup` to find new articles that match an existing recent DB article, then **merges** the new URL onto the existing article via `getArticleIdByUrl` + `addUrlToArticle` (the `article_urls` junction table). - -**v1 behavior:** keep the detection, drop the merge. Run `SemanticDedup` against recent articles (`GET`-equivalent query: `Article` where `published_at >= now-14d`), and simply **drop** any new article flagged as a duplicate. Do not record the dropped URL anywhere except `scored_url` (so it isn't re-evaluated). This removes the need for the `article_urls` table and the URL→ID lookup. Trade-off: we lose multi-source URL attribution for the same story — acceptable for v1. - ---- - -## Pipeline module layout (`backend/pipeline/`) - -``` -backend/pipeline/ - __init__.py - run.py ← entry point, mirrors run.ts - steps.py ← pure helpers: kind_from_url, trust_by_source, - github_repo_from_content, SCORE_THRESHOLD, PROMPT_CONTENT_CAP - utils.py ← log(), sanitize_llm_text() [regex lib], strip_title_wrappers(), wait() - crontab ← supercronic schedule - sources/ - __init__.py - utils.py ← fetch_with_timeout(), is_within_window(), clean_title() - extract_content.py - hn.py [v1] - ainews.py [v1] - substack.py [v1] - email.py [v2] -``` - -### run.py step mapping - -| TS function (run.ts) | Python equivalent | Notes | -|---|---|---| -| `fetchSource` | `fetch_source` | call source fetcher | -| `filterKnownUrls` | `filter_known_urls` | query `article.url` + `scored_url.url` | -| `filterDeadDomains` | `filter_dead_domains` | `dns.resolver` | -| `dedupSemantic` | `dedup_semantic` | `Article` recent query + `SemanticDedup`; **drop dups, no merge** | -| `scoreArticles` | `score_articles` | `ScoreArticles` batch 5; **Ben's Bites +10 bonus, cap 100**; `markUrlsScored` records **all** evaluated URLs | -| `insertArticles` | `insert_articles` | SQLModel insert; dedup-within-batch by URL keeping highest score | -| `improveTitles` | `improve_titles` | `ImproveTitles`, one call per article; skip if source name leaks into title | -| `extractFullContent` | `extract_full_content` | trafilatura; skip `aiNews`/`rss` sourceTypes (their prose is already the summary input) | -| `summarizeAndCategorize` | `summarize_and_categorize` | `SummarizeAndCategorize`, content capped at `PROMPT_CONTENT_CAP=1500`; fallback `CategorizeOnly`+`ClassifyKind`; **blog→repo override** if github repo in content | -| `embedArticles` | `embed_articles` | **model2vec** (drop NVIDIA NIM); text = `title\n\nsummary` | -| `markUrlsScored` | inline in `score_articles` | insert all evaluated URLs into `scored_url` | - ---- - -## Embedding — switch to model2vec (no risk; CORRECTED) - -The TS pipeline embedded with NVIDIA NIM `nv-embedqa-e5-v5` (**1024-d**, per the old Turso `F32_BLOB(1024)` schema). The new Postgres schema and **all 786 existing article embeddings are already model2vec `potion-base-8M` (256-d)** — `backend/scripts/import_articles.py` re-embedded everything at import time. So there is **no dimension mismatch and no data migration**: the pipeline just calls model2vec going forward. Reuse the backend's loader (`app.api.routes.articles.get_model` / `_embed`) or load the model once at pipeline start. - ---- - -## Porting hazards (verified against source — implement carefully) - -1. **`sanitize_llm_text` unicode regex** (utils.ts:43–59) uses `\p{Emoji_Presentation}` / `\p{Extended_Pictographic}` — Python `re` can't. Use the `regex` library. Applied to titles and summaries. -2. **Concurrency** — `Promise.allSettled` in `hn.py` (≤200 items) and `extract_content.py` → use `asyncio.gather(..., return_exceptions=True)` or a `ThreadPoolExecutor`; one failure must not abort the batch. -3. **Substack** (substack.ts) — retry on Cloudflare 403/429 with backoff, residential proxy **only on retry**, browser-header spoofing. Not "just feedparser". -4. **extract_content** (extract-content.ts) — 28 blocker regexes (paywall/login/JS-required), skip x.com/twitter.com, 5s timeout. `trafilatura` covers most extraction but **test blocker detection on real URLs**; port the skip-list explicitly. -5. **Scored URLs record ALL evaluated** (run.ts:239) — even sub-threshold articles go into `scored_url` so they're never re-scored. Don't filter to passing-only. -6. **Ben's Bites +10 bonus** (run.ts:231, capped 100) — source name must match exactly (`"Ben's Bites"`). -7. **blog→repo override** (run.ts:389) — if kind=blog and `github_repo_from_content` finds a real repo link (steps.ts:32–57, with non-repo-owner filter), set kind=repo. -8. **PROMPT_CONTENT_CAP=1500** — truncate content before `SummarizeAndCategorize`. - ---- - -## Runtime data files to carry over - -- `pipeline/sources/substack-sources.json` — 100+ Substack feed URLs. **Copy into `backend/pipeline/sources/`.** (Already in `temp/source/pipeline/sources/`.) -- Newsletter sender list (15 `NEWSLETTER_SOURCES`) is inline in `email.ts` → port into `email.py` constants [v2]. - ---- - -## Environment variables (VPS `.env`) - -Keep / add to the `pipeline` compose service: -- `DATABASE_URL` (same as backend) -- `NVIDIA_NIM_API_KEY` (BAML LLM calls) -- `RESIDENTIAL_PROXY_URL` (Substack) -- v2: `TAVILY_API_KEY`, `IMAP_HOST`, `IMAP_PORT`, `IMAP_USER`, `IMAP_PASSWORD` - -Remove (no longer used anywhere): `TURSO_DATABASE_URL`, `TURSO_AUTH_TOKEN`. - ---- - -## What does NOT change - -- `.baml` prompt files — untouched; only add the Python generator -- Frontend / API read endpoints — no change -- GH Actions CI/CD for the FastAPI app — no change -- The old TS `pipeline.yml` in the source repo — disable after the Python pipeline is confirmed stable - ---- - -## Implementation order - -### Phase 1 — core + RSS/HN sources -1. Add `ScoredUrl` table to `models_agentique.py` → Alembic migration (no `content` migration — it exists). -2. Add `generator python` to `baml_src/generators.baml`, run `baml generate`, commit `backend/baml_client/`. -3. Add v1 Python deps to `pyproject.toml`; `uv lock`. -4. Port `pipeline/utils.py` + `pipeline/steps.py` (pure helpers — `regex`-based sanitize, kind/github helpers, constants). -5. Port `sources/utils.py` + `sources/extract_content.py` (trafilatura). -6. Port `sources/hn.py` (smoke-test source). -7. Port `sources/ainews.py` + `sources/substack.py` (+ copy `substack-sources.json`). -8. Write `pipeline/run.py` wiring steps; dedup = detect-and-drop; embed = model2vec. -9. Add `pipeline` compose service + `crontab` (supercronic). Record `compose.yml` change in `CHANGES.md`. -10. Test locally against the local Docker DB with a `--limit`/dry-run flag; compare output rows to expectations. -11. Deploy; run once manually (`docker compose run --rm pipeline python -m pipeline.run`); monitor. - -### Phase 2 — email source -12. Add v2 deps (`tavily-python`, `imapclient`, `mail-parser`). -13. Port `sources/email.py`: IMAP fetch w/ backoff → `ExtractProducts` → dedup products → `SelectNotableProducts` → Tavily search (concurrency 5, deny-domains) → `SelectProductLink`. -14. Wire email into `SOURCES` in `run.py`; add IMAP/Tavily env to the compose service. -15. Test, deploy, monitor a real run. - -### Cutover -16. Disable the TS `pipeline.yml` in the source repo once stable. -17. Update `CHANGES.md` (new compose service, `ScoredUrl` table, new deps). -18. Remove `temp/source/` once the rewrite is done. diff --git a/temp/source/baml_src/clients.baml b/temp/source/baml_src/clients.baml deleted file mode 100644 index e9eaa343cc..0000000000 --- a/temp/source/baml_src/clients.baml +++ /dev/null @@ -1,29 +0,0 @@ -client Fast { - provider openai-generic - options { - base_url "https://integrate.api.nvidia.com/v1" - api_key env.NVIDIA_NIM_API_KEY - model "qwen/qwen3-next-80b-a3b-instruct" - timeout 60 - } -} - -client Nvidia { - provider openai-generic - options { - base_url "https://integrate.api.nvidia.com/v1" - api_key env.NVIDIA_NIM_API_KEY - model "moonshotai/kimi-k2.6" - timeout 60 - } -} - -client NvidiaGptOss { - provider openai-generic - options { - base_url "https://integrate.api.nvidia.com/v1" - api_key env.NVIDIA_NIM_API_KEY - model "openai/gpt-oss-120b" - timeout 60 - } -} diff --git a/temp/source/baml_src/dedup.baml b/temp/source/baml_src/dedup.baml deleted file mode 100644 index fd536bb051..0000000000 --- a/temp/source/baml_src/dedup.baml +++ /dev/null @@ -1,58 +0,0 @@ -class DedupMatch { - url string @description("URL of the new article") - existingUrl string @description("URL of the existing article it duplicates") -} - -function SemanticDedup( - newArticles: ArticleInput[], - existingArticles: ExistingArticle[] -) -> DedupMatch[] { - client NvidiaGptOss - prompt #" - {{ _.role("system") }} - You are a semantic similarity engine. You compare article pairs and determine whether they cover the same underlying story. You focus on substance, not surface-level keyword overlap. - - {{ _.role("user") }} - You are given two lists: - 1. NEW articles that were just fetched - 2. EXISTING articles already in our database from the last 14 days - - Your job: identify which NEW articles are about the same story as an EXISTING article. Two articles are "the same story" if they cover the same announcement, release, event, or topic - even if from different sources or with different angles. - - NEW articles: - {% for a in newArticles %} - {{ loop.index }}. [{{ a.source }}] "{{ a.title }}" - {{ a.url }}{% if a.trust %} [trust: {{ a.trust }}]{% endif %} - {% if a.snippet %} {{ a.snippet }}{% endif %} - {% endfor %} - - EXISTING articles: - {% for a in existingArticles %} - {{ loop.index }}. [{{ a.source }}] "{{ a.title }}" - {{ a.url }} - {% endfor %} - - For each match, return the new article's URL and the existing article's URL. - If there are no duplicates, return an empty list. - - {{ ctx.output_format }} - "# -} - -test dedup_no_matches { - functions [SemanticDedup] - args { - newArticles [ - { - url "https://a.com/1" - title "Claude 4 released" - source "HN" - } - ] - existingArticles [ - { - url "https://b.com/1" - title "The state of Rust in 2026" - source "RSS" - } - ] - } -} diff --git a/temp/source/baml_src/discover.baml b/temp/source/baml_src/discover.baml deleted file mode 100644 index 30a55c1ad4..0000000000 --- a/temp/source/baml_src/discover.baml +++ /dev/null @@ -1,42 +0,0 @@ -// Batched relevance classifier for the Substack discovery crawler. -// One LLM call judges many candidate profiles at once (see ScoreArticles for -// the array-in/array-out batching pattern). Classification runs on cheap -// metadata (name + description) BEFORE any per-profile post fetch, and gates -// both DB insertion and whether the crawler recurses into that profile. - -class ProfileInput { - handle string @description("Substack owner handle, echoed back in the verdict") - name string @description("Publication name") - description string? @description("Publication hero text and/or author bio, if known") -} - -class ProfileVerdict { - handle string @description("Must exactly match the input handle") - isAiRelated bool - confidence int @description("0-100 confidence that AI/ML/LLMs is the PRIMARY focus") -} - -function ClassifyProfiles(profiles: ProfileInput[]) -> ProfileVerdict[] { - client Nvidia - prompt #" - {{ _.role("system") }} - You curate sources for a developer-focused AI news platform. For each Substack - publication, decide whether artificial intelligence is its PRIMARY subject: - AI/ML/LLMs, foundation models, AI engineering, AI products, or AI research. - - Mark isAiRelated = true ONLY when AI is clearly the main topic. Mark false for - general tech, productivity, marketing, business, crypto, politics, lifestyle, or - publications that merely mention AI in passing. When the signal is thin (sparse - description, generic name), lean false and assign low confidence - the crawler - prunes everything you reject, so false positives pollute the whole subtree. - - {{ _.role("user") }} - Classify every profile. Echo each handle back EXACTLY as given. - - {% for p in profiles %} - {{ loop.index }}. handle={{ p.handle }} | {{ p.name }}{% if p.description %} — {{ p.description }}{% endif %} - {% endfor %} - - {{ ctx.output_format }} - "# -} diff --git a/temp/source/baml_src/extract_links.baml b/temp/source/baml_src/extract_links.baml deleted file mode 100644 index 579c0d8aa4..0000000000 --- a/temp/source/baml_src/extract_links.baml +++ /dev/null @@ -1,42 +0,0 @@ -class ExtractedLink { - title string - url string - snippet string @description("One-sentence description of the article") -} - -function ExtractLinks(emailHtml: string) -> ExtractedLink[] { - client NvidiaGptOss - prompt #" - {{ _.role("system") }} - You are a precise link extraction engine. You parse newsletter HTML and identify external article links while filtering out tracking, admin, and promotional URLs. - - {{ _.role("user") }} - You are given the HTML body of a newsletter email. Extract all article links that point to external news stories, blog posts, research papers, or product announcements. - - For each article, return its title, URL, and a one-sentence snippet describing it. - - IGNORE these types of links: - - Tracking/redirect URLs (e.g. links through email marketing platforms) - - Unsubscribe, manage preferences, or email settings links - - Social media profile links (twitter, linkedin, etc.) - - Links back to the newsletter's own homepage, archive index, or subscription page (but DO include article/post links hosted on the newsletter's domain - curated newsletters often host their own content) - - Sponsor/advertisement links - - Job posting links - - RESOLVE redirect URLs: if a link is clearly a tracking redirect (contains /click, /track, utm_ params, etc.), try to extract the final destination URL from the href. Strip all UTM parameters from URLs. - - Newsletter HTML: - {{ emailHtml }} - - If no relevant article links are found, return an empty list. - - {{ ctx.output_format }} - "# -} - -test extract_links_basic { - functions [ExtractLinks] - args { - emailHtml "Welcome to today's issue! [Read OpenAI's new paper](https://openai.com/papers/gpt-5). [Unsubscribe](https://newsletter.com/unsubscribe)." - } -} diff --git a/temp/source/baml_src/extract_products.baml b/temp/source/baml_src/extract_products.baml deleted file mode 100644 index 9e5f5a531a..0000000000 --- a/temp/source/baml_src/extract_products.baml +++ /dev/null @@ -1,125 +0,0 @@ -// Product-centric newsletter extraction. -// -// Replaces the per-newsletter tracking-URL resolvers: instead of decoding each -// provider's redirect scheme to recover the real link, we extract the *named -// products* a newsletter reports on (from anchor text + surrounding prose), -// keep only the notable ones, and rediscover their canonical URLs via web -// search (src/sources/email.ts). SelectProductLink then picks the best -// first-party result among the candidates. - -class NewsletterProduct { - name string @description("Exact product / tool / model / launch name") - description string @description("Concise phrase: what it is and does, usable verbatim as a web search query") -} - -function ExtractProducts(newsletterText: string) -> NewsletterProduct[] { - client NvidiaGptOss - prompt #" - {{ _.role("system") }} - You extract the AI/tech products, tools, models, and launches that a newsletter is reporting on. Work only from the text; never invent products that are not mentioned. - - {{ _.role("user") }} - Below is the text of a newsletter email. Links appear as [anchor text](url) but the URLs are often tracking redirects, so judge by the words, not the links. - - Identify every distinct product, tool, model, SDK, dataset, or launch the newsletter is reporting as news. For each, return: - - name: the exact product/tool/model name - - description: a concise phrase describing what it is and does, suitable as a web search query - - INCLUDE only real, named launches a reader could go use or read about. - - IGNORE: - - the author's intro letter, essay, or personal commentary - - sponsor blurbs, advertisements, "brought to you by", upgrade / subscribe / manage-preferences prompts - - social-media embeds (an @handle with like / repost / reply counts) and the newsletter's own social links - - section headers, navigation, and unsubscribe links - - Newsletter text: - {{ newsletterText }} - - If the text names no qualifying products, return an empty list. - - {{ ctx.output_format }} - "# -} - -// Notability gate: trims the extracted list to the launches actually worth -// resolving, so we don't spend a web search on every incremental SDK bump. -// Returns the 1-based indices of the products to KEEP. -function SelectNotableProducts(products: NewsletterProduct[]) -> int[] { - client Nvidia - prompt #" - {{ _.role("user") }} - Below is a numbered list of products/tools/models a newsletter mentioned. Return the numbers of the ones that are NOTABLE enough to feature in an AI-news aggregator. - - KEEP a product if it is a distinct, real, individually newsworthy launch a reader would want to click: new models, significant new products or platforms, notable agents/tools, major releases. - - DROP: - - minor or incremental items: small SDK/utility bumps, niche helper libraries, design skills, config tweaks - - vague or marketing-only entries with no concrete product behind them - - duplicates or sub-features of another item in the list - - Products: - {% for p in products %} - {{ loop.index }}. {{ p.name }} — {{ p.description }} - {% endfor %} - - Return only the numbers to keep, as a JSON array of integers. If none qualify, return []. - - {{ ctx.output_format }} - "# -} - -class SearchCandidate { - title string - url string - snippet string -} - -class ProductLinkChoice { - index int @description("1-based index of the best first-party result, or 0 if none qualifies") - confidence float @description("0.0 - 1.0") -} - -// Picks the best canonical URL for a product among search candidates, biased -// hard toward the official / first-party source and away from social posts and -// SEO/aggregator pages. Returns index 0 when nothing is clearly the product. -function SelectProductLink( - productName: string, - productDescription: string, - candidates: SearchCandidate[] -) -> ProductLinkChoice { - client Nvidia - prompt #" - {{ _.role("user") }} - A newsletter featured this item: - name: {{ productName }} - description: {{ productDescription }} - - Web search returned these candidate results: - {% for c in candidates %} - {{ loop.index }}. {{ c.title }} - url: {{ c.url }} - snippet: {{ c.snippet }} - {% endfor %} - - Pick the ONE candidate that is the canonical, first-party source for this exact product — its official site, product page, model card, repo, or the vendor's own announcement. - - PREFER the official / first-party domain that matches the product or its maker. - REJECT (do not pick) when it is the best available: - - social-media posts (x.com, twitter.com, linkedin.com, reddit.com, threads, mastodon) - - videos (youtube.com) - - content-farm / SEO / generic aggregator or listicle pages that merely mention the product - - a DIFFERENT product that happens to share the name - - Return the 1-based index of the best first-party result. If none of the candidates is clearly a first-party source for THIS product, return index 0. - - {{ ctx.output_format }} - "# -} - -test extract_products_basic { - functions [ExtractProducts] - args { - newsletterText "Headlines: [OpenAI ships GPT-5](https://sub.stack/redirect/2/abc), a new flagship model. Brought to you by Acme. [Unsubscribe](https://newsletter.com/unsub)." - } -} diff --git a/temp/source/baml_src/fix_titles.baml b/temp/source/baml_src/fix_titles.baml deleted file mode 100644 index 9239b53d20..0000000000 --- a/temp/source/baml_src/fix_titles.baml +++ /dev/null @@ -1,61 +0,0 @@ -class TitleFix { - url string @description("The exact URL from the matching input article - copy verbatim") - title string @description("Plain title text only. No surrounding quotes. No leading source name or bracket tag. Max 12 words. Return the input title verbatim if it is already clear, specific, and informative.") -} - -function ImproveTitles(articles: ArticleInput[]) -> TitleFix[] { - client NvidiaGptOss - prompt #" - {{ _.role("system") }} - You are a technical editor. You write clear, informative article titles for an AI developer news platform. - - Output rules (strict): - - For each input article, return one TitleFix whose `url` exactly matches that article's URL. - - The `title` field contains plain title text ONLY. Do NOT wrap it in quotes. Do NOT prefix it with "[Source]" or any source name. Do NOT include the URL. - - Use only the snippet of the SAME article to inform the rewrite. Never blend information across articles. - - {{ _.role("user") }} - Decide for each article whether the existing title is already good. A good title is specific, informative, and technical/neutral in register - it tells a developer what the article is actually about. - - - If the existing title is already good, return it verbatim. - - Otherwise rewrite it using only that article's snippet: specific, informative, max 12 words, technical/neutral register, no hype or filler. - - {% for a in articles %} - --- Article {{ loop.index }} --- - url: {{ a.url }} - source: {{ a.source }} - current_title: {{ a.title }} - {% if a.snippet %}snippet: {{ a.snippet }}{% endif %} - {% endfor %} - - {{ ctx.output_format }} - "# -} - -test improve_titles_rewrite_short { - functions [ImproveTitles] - args { - articles [ - { - url "https://example.com/claude" - title "Claude 4" - source "HN" - snippet "Anthropic today released Claude 4, a new flagship model with improved reasoning and a 1M-token context window." - } - ] - } -} - -test improve_titles_keep_unchanged { - functions [ImproveTitles] - args { - articles [ - { - url "https://example.com/post" - title "Anthropic releases Claude 4 with 1M-token context window" - source "HN" - snippet "Anthropic today released Claude 4, a new flagship model with improved reasoning." - } - ] - } -} diff --git a/temp/source/baml_src/generators.baml b/temp/source/baml_src/generators.baml deleted file mode 100644 index fdd48b14bb..0000000000 --- a/temp/source/baml_src/generators.baml +++ /dev/null @@ -1,6 +0,0 @@ -generator typescript { - output_type "typescript" - output_dir "../" - version "0.223.0" - default_client_mode "async" -} diff --git a/temp/source/baml_src/score.baml b/temp/source/baml_src/score.baml deleted file mode 100644 index 01d73713df..0000000000 --- a/temp/source/baml_src/score.baml +++ /dev/null @@ -1,84 +0,0 @@ -class ScoredArticle { - url string - score int @description("1-100 developer-actionability rating") -} - -function ScoreArticles(articles: ArticleInput[]) -> ScoredArticle[] { - client Nvidia - prompt #" - {{ _.role("system") }} - You are a senior editorial analyst at a developer news platform. Your job is to evaluate articles for relevance and actionability for AI builders. You are precise, consistent, and ruthless about filtering noise. - - {{ _.role("user") }} - Score every article for developer-actionability on a 1-100 scale. - - STEP 1 - SCOPE CHECK (apply first, before scoring): - Is the article about AI, ML, LLMs, foundation models, or AI-adjacent developer tools/infrastructure? - - NO → score 1-20 and move on. Do NOT apply the scoring guide below. - - Out-of-scope examples: text editors, parsers, version control tools, data structures (CRDTs, B-trees), memory management, general programming tutorials, non-AI open source projects, codebase audits, legacy code. These are general software engineering - not AI. - - STEP 2 - SCORE (only for in-scope articles): - Audience: developers, startup founders, and tech leaders building with AI who want to ship faster. - - Score 91-100 is reserved for exceptional articles that are BOTH immediately actionable today AND fit one of these themes: local/on-device inference, privacy-preserving AI, efficiency breakthroughs (quantization, token optimization, running models on less hardware), or deep technical dives that explain how something actually works. A score in this range means "a developer could open a terminal and act on this within the hour, AND it reveals a non-obvious insight or technique." Zero is a valid outcome - do not give 91+ just because something is the best of a weak batch. - - Models (new releases, benchmarks, evals, model cards, comparisons): - - 81-90: New model release or major update, model system cards, open-weight models a developer can run today - - 71-80: Meaningful benchmark or eval, model comparison with actionable conclusions - - Dev (SDKs, frameworks, CLI tools, IDE integrations, open-source projects, tutorials, deployment): - - 81-90: New AI API or SDK, open-source AI tool/library a developer can use today - - 71-80: Fine-tuning guide, RAG pattern, significant framework update, AI infrastructure (training, inference, memory optimization), deployment recipes - - Research (papers, breakthroughs, novel techniques): - - 71-80: Research with immediate practical implications, AI security research - - 51-60: Research with near-term practical implications - - Industry (funding, platform changes, acquisitions, partnerships, market shifts): - - 51-60: Industry analysis with actionable takeaways, AI platform partnerships - - 31-40: Funding rounds without product details, opinion/commentary with no actionable steps, "AI is changing everything" think pieces, personal anecdotes about using AI - - Upgrade to 91-100: if an article would score 81-90 AND fits the top-tier criteria above (local inference, privacy-preserving, efficiency breakthrough, or deep how-it-works dive), give it 91-100. - - Bottom tier: - - 1-20: Non-AI topics (see step 1), regulation, politics, lawsuits, corporate drama - - Trust bonus: entries may include a [trust: high/medium/low] tag. Give +1 to high-trust sources when content quality is comparable. - - Articles: - {% for a in articles %} - {{ loop.index }}. [{{ a.source }}] "{{ a.title }}" - {{ a.url }}{% if a.trust %} [trust: {{ a.trust }}]{% endif %} - {% if a.snippet %} {{ a.snippet }}{% endif %} - {% endfor %} - - {{ ctx.output_format }} - "# -} - -test score_gpt5_release { - functions [ScoreArticles] - args { - articles [ - { - url "https://openai.com/index/introducing-gpt-5" - title "Introducing GPT-5" - source "Hacker News" - trust "medium" - } - ] - } -} - -test score_out_of_scope { - functions [ScoreArticles] - args { - articles [ - { - url "https://example.com/crdt-deep-dive" - title "A Deep Dive Into CRDTs and Conflict Resolution" - source "Some Blog" - trust "low" - } - ] - } -} diff --git a/temp/source/baml_src/shared.baml b/temp/source/baml_src/shared.baml deleted file mode 100644 index 46d5b8ff35..0000000000 --- a/temp/source/baml_src/shared.baml +++ /dev/null @@ -1,33 +0,0 @@ -// Shared types used by multiple BAML functions. - -enum ArticleCategory { - Models - Dev - Research -} - -enum ArticleKind { - Repo // GitHub/GitLab repository - Paper // Academic paper, preprint, technical report - Model // Model card or model release page - Blog // Developer blog post, tutorial, how-to, opinion piece - Product // Product launch page or product website - Announcement // Official release post from a major AI lab -} - -// Used as input to ScoreArticles, ImproveTitles, SemanticDedup. -// Mirrors the fields the existing formatArticles() helper emits. -class ArticleInput { - url string - title string - source string - snippet string? @description("First ~200 chars of the article content, if any") - trust string? @description("\"high\" | \"medium\" | \"low\" - source trust tag") -} - -// Used as input to SemanticDedup for rows already in the DB. -class ExistingArticle { - url string - title string - source string -} diff --git a/temp/source/baml_src/summarize.baml b/temp/source/baml_src/summarize.baml deleted file mode 100644 index 59fecb7e0b..0000000000 --- a/temp/source/baml_src/summarize.baml +++ /dev/null @@ -1,111 +0,0 @@ -class SummarizeAndCategorizeResult { - summary string @description("2-3 short factual lines separated by \\n") - categories ArticleCategory[] @description("1-2 categories") - kind ArticleKind -} - -class CategorizeOnlyResult { - categories ArticleCategory[] @description("1-2 categories") -} - -class ClassifyKindResult { - kind ArticleKind -} - -function SummarizeAndCategorize(title: string, content: string) -> SummarizeAndCategorizeResult { - client NvidiaGptOss - prompt #" - {{ _.role("system") }} - You are a technical writer for a developer news digest. Your readers are tech-savvy but busy. Write in plain, direct language. - - {{ _.role("user") }} - Summarize this article. Be plain and brief. - - Title: {{ title }} - - Content: - {{ content }} - - 1. Write 2-3 lines. Keep each line to one short sentence. Rules: - - Only state facts from the article. - - No passive voice. No "enables", "allows", "provides". - - Separate lines with a newline. - 2. Assign 1-2 categories. - 3. Assign a kind. - - Category definitions: - - Models: New model releases, benchmarks, evals, model cards, model comparisons - - Dev: Repos, tools, product launches, developer blogs, tutorials, how-tos, fine-tuning guides, deployment recipes, infrastructure updates - - Research: Papers, breakthroughs, novel techniques with practical implications - - Kind definitions: - - Repo: GitHub or GitLab repository - - Paper: Academic paper, preprint, or long-form technical report - - Model: Model card or model release page (e.g. HuggingFace) - - Blog: Developer blog post, tutorial, how-to, or opinion piece - - Product: Product launch page or product website - - Announcement: Official release post from a major AI lab (OpenAI, Anthropic, Google, Meta, Mistral, etc.) - - {{ ctx.output_format }} - "# -} - -function ClassifyKind(title: string, url: string, summary: string?) -> ClassifyKindResult { - client NvidiaGptOss - prompt #" - {{ _.role("system") }} - You are a technical librarian who classifies AI developer content by format. - - {{ _.role("user") }} - Classify this article's kind. - - Title: {{ title }} - URL: {{ url }} - {% if summary %}Summary: {{ summary }}{% endif %} - - Kind definitions: - - Repo: GitHub or GitLab repository - - Paper: Academic paper, preprint, or long-form technical report - - Model: Model card or model release page (e.g. HuggingFace) - - Blog: Developer blog post, tutorial, how-to, or opinion piece - - Product: Product launch page or product website - - Announcement: Official release post from a major AI lab (OpenAI, Anthropic, Google, Meta, Mistral, etc.) - - {{ ctx.output_format }} - "# -} - -function CategorizeOnly(title: string) -> CategorizeOnlyResult { - client NvidiaGptOss - prompt #" - {{ _.role("system") }} - You are a technical librarian who classifies developer-focused AI articles. - - {{ _.role("user") }} - Assign 1-2 categories to this article title. - - Title: {{ title }} - - Category definitions: - - Models: New model releases, benchmarks, evals, model cards, model comparisons - - Dev: Repos, tools, product launches, developer blogs, tutorials, how-tos, fine-tuning guides, deployment recipes, infrastructure updates - - Research: Papers, breakthroughs, novel techniques with practical implications - - {{ ctx.output_format }} - "# -} - -test summarize_basic { - functions [SummarizeAndCategorize] - args { - title "Anthropic releases Claude 4" - content "Anthropic today launched Claude 4, a new flagship model. It features improved reasoning, a 1M-token context window, and native tool use. The model is available via API and Claude.ai starting today." - } -} - -test categorize_only_basic { - functions [CategorizeOnly] - args { - title "OpenAI releases GPT-5 with 2M context" - } -} diff --git a/temp/source/pipeline/run.ts b/temp/source/pipeline/run.ts deleted file mode 100644 index 56c728611b..0000000000 --- a/temp/source/pipeline/run.ts +++ /dev/null @@ -1,451 +0,0 @@ -import "dotenv/config"; -import { promises as dnsPromises } from "node:dns"; -import { setLogLevel } from "@boundaryml/baml/logging"; -import { - getRecentArticles, - insertArticle, - updateCategories, - updateContent, - updateEmbedding, - updateKind, - updateScore, - updateTitle, -} from "@shared/db/articles"; -import { - addUrlToArticle, - getArticleIdByUrl, - markUrlsScored, - scoredUrlsExist, - urlsExist, -} from "@shared/db/urls"; -import { embeddingToVecString, getEmbedding } from "@shared/embeddings"; -import type { FetchedArticle } from "@shared/types"; -import { b } from "../baml_client"; -import type { ExistingArticle } from "../baml_client/types"; -import { fetchAiNews } from "./sources/ainews"; -import { fetchNewsletter } from "./sources/email"; -import { reExtractFullContent } from "./sources/extract-content"; -import { fetchHN } from "./sources/hn"; -// import { fetchRss } from "../sources/rss"; -import { fetchSubstack } from "./sources/substack"; -import { - githubRepoFromContent, - kindFromUrl, - SCORE_THRESHOLD, - toArticleInputs, -} from "./steps"; -import { log, sanitizeLlmText, stripTitleWrappers, wait } from "./utils"; - -const SOURCES: { label: string; fetcher: () => Promise }[] = [ - { label: "Hacker News", fetcher: fetchHN }, - { label: "Newsletter", fetcher: fetchNewsletter }, - { label: "AI News", fetcher: fetchAiNews }, - { label: "Substack", fetcher: fetchSubstack }, - // { label: "RSS", fetcher: fetchRss }, -]; - -const PROMPT_CONTENT_CAP = 1500; - -export async function runPipeline(): Promise { - log("=== Pipeline start ==="); - const start = Date.now(); - - const all: Awaited> = []; - - for (const src of SOURCES) { - log(`\n=== Processing ${src.label} ===`); - - const fetched = await fetchSource(src.fetcher, src.label); - const fresh = await filterKnownUrls(fetched, src.label); - const alive = await filterDeadDomains(fresh, src.label); - const unique = await dedupSemantic(alive, src.label); - const scored = await scoreArticles(unique); - const inserted = await insertArticles(scored); - await improveTitles(inserted); - const withContent = await extractFullContent(inserted); - const processed = await summarizeAndCategorize(withContent); - await embedArticles(processed); - - all.push(...processed); - } - - const elapsed = ((Date.now() - start) / 1000).toFixed(1); - log(`=== Pipeline complete in ${elapsed}s ===`); -} - -// ─── Steps ─────────────────────────────────────────────────────────────────── - -/** Step 01 - Call the source fetcher; log if nothing came back. */ -async function fetchSource( - fetcher: () => Promise, - label: string, -): Promise { - const articles = await fetcher(); - if (articles.length === 0) log(`No articles from ${label}`); - return articles; -} - -/** Step 02 - Drop URLs already present in articles or scored_urls. */ -async function filterKnownUrls( - articles: FetchedArticle[], - label: string, -): Promise { - if (articles.length === 0) return []; - - const allUrls = articles.map((a) => a.url); - const existing = await urlsExist(allUrls); - const alreadyScored = await scoredUrlsExist(allUrls); - const fresh = articles.filter( - (a) => !existing.has(a.url) && !alreadyScored.has(a.url), - ); - - if (existing.size > 0 || alreadyScored.size > 0) { - log( - ` Filtered ${existing.size} known + ${alreadyScored.size} already-scored URLs`, - ); - } - if (fresh.length === 0) { - log(` No new articles from ${label}`); - return []; - } - log(` ${fresh.length} new articles to process`); - return fresh; -} - -/** Step 02b - Drop articles whose hostname does not resolve in DNS. */ -async function filterDeadDomains( - articles: FetchedArticle[], - label: string, -): Promise { - if (articles.length === 0) return articles; - - const checks = await Promise.all( - articles.map(async (a) => ({ - article: a, - ok: await isDomainResolvable(a.url), - })), - ); - - const alive = checks.filter((c) => c.ok).map((c) => c.article); - const deadCount = checks.length - alive.length; - if (deadCount > 0) { - for (const c of checks) { - if (!c.ok) log(` Dropped dead URL: ${c.article.url}`); - } - log(` Filtered ${deadCount} dead-domain URLs from ${label}`); - } - return alive; -} - -async function isDomainResolvable(url: string): Promise { - let host: string; - try { - host = new URL(url).hostname; - } catch { - return false; - } - try { - await dnsPromises.lookup(host); - return true; - } catch (e) { - return (e as NodeJS.ErrnoException)?.code !== "ENOTFOUND"; - } -} - -/** - * Step 03 - Drop articles that are the same story as a recent DB entry. - * Merges the duplicate URL onto the existing row; falls back gracefully on AI failure. - */ -async function dedupSemantic( - articles: FetchedArticle[], - label: string, -): Promise { - if (articles.length === 0) return articles; - - const recentDb = await getRecentArticles(14); - if (recentDb.length === 0) return articles; - - log(` Deduplicating against ${recentDb.length} recent DB articles...`); - - const newInput = toArticleInputs(articles); - - const existingInput = recentDb.map( - (a): ExistingArticle => ({ - url: a.url, - title: a.title, - source: a.source, - }), - ); - - try { - const matches = await b.SemanticDedup(newInput, existingInput); - - for (const match of matches) { - const existingId = await getArticleIdByUrl(match.existingUrl); - if (existingId) { - await addUrlToArticle(match.url, existingId); - log(` Merged: ${match.url} -> existing article #${existingId}`); - } - } - - const mergedUrls = new Set(matches.map((m) => m.url)); - const unique = articles.filter((a) => !mergedUrls.has(a.url)); - if (mergedUrls.size > 0) - log(` ${mergedUrls.size} articles merged with existing`); - if (unique.length === 0) log(` No new unique articles from ${label}`); - return unique; - } catch (err) { - log(` Dedup failed, continuing without: ${err}`); - return articles; - } -} - -/** - * Step 04 - Score articles via BAML; keep those >= SCORE_THRESHOLD. - * Records ALL evaluated URLs in scored_urls so they're skipped next run. - * Ben's Bites gets a +10 bonus (capped at 100) to offset its summarized style. - */ -async function scoreArticles( - articles: FetchedArticle[], -): Promise<{ article: FetchedArticle; score: number }[]> { - if (articles.length === 0) return []; - - log(` Scoring ${articles.length} articles in batches of 10...`); - - const BATCH = 5; - const allScores: { url: string; score: number }[] = []; - for (let i = 0; i < articles.length; i += BATCH) { - const batch = toArticleInputs(articles.slice(i, i + BATCH)); - const result = await b.ScoreArticles(batch); - allScores.push(...result); - log( - ` batch ${Math.ceil((i + BATCH) / BATCH)}/${Math.ceil(articles.length / BATCH)} done`, - ); - await wait(1000); - } - - const scoreByUrl = new Map(allScores.map((s) => [s.url, s.score])); - const scored = articles - .map((a) => { - let score = scoreByUrl.get(a.url) ?? 0; - if (a.source === "Ben's Bites") score = Math.min(score + 10, 100); - return { article: a, score }; - }) - .sort((a, b) => b.score - a.score); - - const kept = scored.filter((s) => s.score >= SCORE_THRESHOLD); - log(` ${kept.length} articles pass scoring (threshold: ${SCORE_THRESHOLD})`); - - await markUrlsScored(articles.map((a) => a.url)); - - return kept; -} - -/** Step 05 - Insert scored articles into the DB; returns id+article+score triples. */ -async function insertArticles( - scored: { article: FetchedArticle; score: number }[], -): Promise<{ id: number; article: FetchedArticle; score: number }[]> { - if (scored.length === 0) return []; - - // Dedup within batch: same URL from multiple newsletters - keep highest score - const byUrl = new Map(); - for (const item of scored) { - const existing = byUrl.get(item.article.url); - if (!existing || item.score > existing.score) - byUrl.set(item.article.url, item); - } - const deduped = [...byUrl.values()]; - - const inserted: { id: number; article: FetchedArticle; score: number }[] = []; - for (const { article, score } of deduped) { - article.title = sanitizeLlmText(article.title); - const id = await insertArticle(article); - await updateScore(id, score); - inserted.push({ id, article, score }); - log(` Inserted #${id}: [${score}/10] ${article.title}`); - } - return inserted; -} - -/** - * Step 06 - Send every inserted article through ImproveTitles, one per call. - * Per-article calls eliminate cross-batch hallucinations we observed at batch - * sizes of 5+ (model occasionally attached one article's snippet to another's URL). - */ -async function improveTitles( - inserted: { id: number; article: FetchedArticle; score: number }[], -): Promise { - if (inserted.length === 0) return; - - log(` Improving ${inserted.length} titles...`); - - for (const { id, article } of inserted) { - const input = toArticleInputs([article]); - try { - const fixes = await b.ImproveTitles(input); - const raw = fixes[0]?.title; - if (!raw) continue; - const sanitized = sanitizeLlmText(stripTitleWrappers(raw)); - if (!sanitized || sanitized === article.title) continue; - if (sanitized.toLowerCase().includes(article.source.toLowerCase())) { - log( - ` Skip rewrite #${id} (source name leaked into output): "${sanitized}"`, - ); - continue; - } - const oldTitle = article.title; - await updateTitle(id, sanitized); - article.title = sanitized; - log(` Improved title #${id}: "${oldTitle}" → "${sanitized}"`); - } catch (err) { - log(` Title improve failed for #${id}, continuing: ${err}`); - } - } -} - -/** - * Step 07 - Re-fetch full article text for kept articles (uncapped). - * AI News items are skipped - their recap prose is already the right input for step 08. - */ -async function extractFullContent( - inserted: { id: number; article: FetchedArticle; score: number }[], -): Promise< - { id: number; article: FetchedArticle; score: number; fullContent: string }[] -> { - if (inserted.length === 0) return []; - - const toExtract = inserted.filter( - (a) => a.article.sourceType !== "aiNews" && a.article.sourceType !== "rss", - ); - const contentMap = await reExtractFullContent( - toExtract.map((a) => ({ url: a.article.url })), - ); - - for (const { id, article } of toExtract) { - const full = contentMap.get(article.url); - if (full) await updateContent(id, full); - } - - return inserted.map((item) => { - if ( - item.article.sourceType === "aiNews" || - item.article.sourceType === "rss" - ) { - return { ...item, fullContent: item.article.content }; - } - return { ...item, fullContent: contentMap.get(item.article.url) ?? "" }; - }); -} - -/** - * Step 08 - Summarize and categorize each article. - * Falls back to CategorizeOnly (title-only) when no body was extracted. - * Demotes non-Models 10/10 scores to 9 to keep the top bar meaningful. - */ -async function summarizeAndCategorize( - items: { - id: number; - article: FetchedArticle; - score: number; - fullContent: string; - }[], -): Promise< - { - id: number; - url: string; - title: string; - score: number; - summary: string; - categories: string[]; - }[] -> { - if (items.length === 0) return []; - - log(` Summarizing and categorizing ${items.length} articles...`); - - const processed: { - id: number; - url: string; - title: string; - score: number; - summary: string; - categories: string[]; - }[] = []; - - for (const { id, article, score, fullContent } of items) { - let summary = ""; - let categories: string[] = []; - let kind: string | null = kindFromUrl(article.url); - - try { - if (fullContent) { - const result = await b.SummarizeAndCategorize( - article.title, - fullContent.slice(0, PROMPT_CONTENT_CAP), - ); - summary = sanitizeLlmText(result.summary ?? ""); - categories = result.categories.map((c) => c.toLowerCase()); - if (!kind) kind = result.kind.toLowerCase(); - if (kind === "blog" && githubRepoFromContent(fullContent)) - kind = "repo"; - } else { - const result = await b.CategorizeOnly(article.title); - categories = result.categories.map((c) => c.toLowerCase()); - if (!kind) { - const kindResult = await b.ClassifyKind( - article.title, - article.url, - undefined, - ); - kind = kindResult.kind.toLowerCase(); - } - } - } catch (err) { - log(` Summarize/categorize failed for #${id}: ${err}`); - } - - await updateCategories(id, summary, categories); - if (kind) await updateKind(id, kind); - - processed.push({ - id, - url: article.url, - title: article.title, - score, - summary, - categories, - }); - } - - log(` Done summarizing and categorizing`); - return processed; -} - -/** Step 09 - Generate and store a semantic embedding for each processed article. */ -async function embedArticles( - items: { id: number; title: string; summary: string }[], -): Promise { - if (items.length === 0) return; - - log(` Embedding ${items.length} articles...`); - - for (const { id, title, summary } of items) { - try { - const text = summary ? `${title}\n\n${summary}` : title; - const vec = await getEmbedding(text, "passage"); - await updateEmbedding(id, embeddingToVecString(vec)); - } catch (err) { - log(` Embed failed for #${id}: ${err}`); - } - } -} - -// CLI entry point -if (!process.env.BAML_LOG) setLogLevel("ERROR"); - -runPipeline() - .then(() => process.exit(0)) - .catch((err) => { - console.error(err); - process.exit(1); - }); diff --git a/temp/source/pipeline/search.ts b/temp/source/pipeline/search.ts deleted file mode 100644 index 01fea3efb4..0000000000 --- a/temp/source/pipeline/search.ts +++ /dev/null @@ -1,83 +0,0 @@ -// Tavily Search API client. -// Set TAVILY_API_KEY in your environment. -// -// Usage: -// const results = await search("OpenShell v0.0.26 microVM AI agents", { maxResults: 3 }); - -import { log } from "./utils"; - -const TAVILY_API_URL = "https://api.tavily.com/search"; - -export interface SearchResult { - title: string; - url: string; - description: string; -} - -export interface SearchOptions { - /** Max results to return (default: 5). */ - maxResults?: number; -} - -export async function search( - query: string, - options: SearchOptions = {}, -): Promise { - const apiKey = process.env.TAVILY_API_KEY; - if (!apiKey) throw new Error("TAVILY_API_KEY is not set"); - - const { maxResults = 5 } = options; - - const res = await fetch(TAVILY_API_URL, { - method: "POST", - headers: { "Content-Type": "application/json" }, - body: JSON.stringify({ api_key: apiKey, query, max_results: maxResults }), - }); - - if (!res.ok) { - throw new Error(`Tavily Search API error: ${res.status} ${res.statusText}`); - } - - const data = (await res.json()) as { - results?: { title: string; url: string; content?: string }[]; - }; - - return (data.results ?? []).map((r) => ({ - title: r.title, - url: r.url, - description: r.content ?? "", - })); -} - -/** - * Given an x.com / twitter.com URL and a title/description, searches for - * the underlying article and returns the best non-Twitter result URL. - * Returns null if nothing useful is found. - */ -export async function resolveTwitterUrl( - title: string, - description: string, -): Promise { - // Strip twitter handles (@Foo -) and RSS formatting noise from the title - const cleanTitle = title.replace(/^@\w+\s+[-–-]\s+/, "").trim(); - - // Use title + first sentence of description as query - const firstSentence = description.split(/\.\s+/)[0]?.trim() ?? ""; - const query = firstSentence ? `${cleanTitle} ${firstSentence}` : cleanTitle; - - try { - const results = await search(query, { maxResults: 5 }); - - const BLOCKED = ["x.com", "twitter.com", "t.co"]; - const match = results.find((r) => !BLOCKED.some((b) => r.url.includes(b))); - - if (match) { - log(` Resolved to: ${match.url}`); - return match.url; - } - } catch (err) { - log(` Search failed: ${err}`); - } - - return null; -} diff --git a/temp/source/pipeline/sources/ainews.ts b/temp/source/pipeline/sources/ainews.ts deleted file mode 100644 index d0fcd1f632..0000000000 --- a/temp/source/pipeline/sources/ainews.ts +++ /dev/null @@ -1,334 +0,0 @@ -// AI News source - extracts sub-stories from the news.smol.ai RSS feed. -// -// AI News is a daily aggregator of X/Twitter, Reddit, and Discord AI content. -// Each issue has two useful sections: -// -

    AI Twitter Recap

    - one editorial top-story per issue -// -

    AI Reddit Recap

    - multiple reddit posts, one per -// -// We turn each issue into multiple FetchedArticle entries: -// - One twitter-recap sub-story (title = first , primary URL = best -// non-tweet link, content = first few bullets as summary) -// - N reddit-recap sub-stories (one per reddit post anchor) -// -// Primary-URL priority: github > huggingface > arxiv > blog > reddit > tweet. -// -// This file is deliberately self-contained and does NOT reuse email.ts logic. - -import type { FetchedArticle } from "@shared/types"; -import { log } from "../utils"; -import { fetchWithTimeout, isWithinWindow } from "./utils"; - -const FEED_URL = "https://news.smol.ai/rss.xml"; -const MAX_CONTENT_LENGTH = 1400; -const MIN_REDDIT_BODY_LENGTH = 120; -const MIN_TWITTER_TITLE_LENGTH = 10; - -type PrimaryKind = - | "tweet" - | "reddit" - | "github" - | "huggingface" - | "arxiv" - | "blog" - | "other"; - -// ---------- feed parsing (no deps) ---------- - -const HTML_ENTITIES: Record = { - "<": "<", - ">": ">", - """: '"', - "'": "'", - "'": "'", - "&": "&", - " ": " ", - "&": "&", -}; - -function decodeHtml(s: string): string { - return s.replace( - /&(?:lt|gt|quot|apos|#x27|#x26|nbsp|amp);/g, - (m) => HTML_ENTITIES[m], - ); -} - -function pickTag(block: string, tag: string): string { - const match = block.match(new RegExp(`<${tag}>([\\s\\S]*?)`)); - if (!match) return ""; - const cdata = match[1].match(/^$/); - return cdata ? cdata[1] : match[1]; -} - -interface RssItem { - title: string; - link: string; - contentHtml: string; - pubDate: string; -} - -function parseFeed(xml: string): RssItem[] { - return xml - .split("") - .slice(1) - .map((chunk) => { - const body = chunk.split("")[0]; - return { - title: pickTag(body, "title"), - link: pickTag(body, "link"), - contentHtml: decodeHtml(pickTag(body, "content:encoded")), - pubDate: pickTag(body, "pubDate"), - }; - }); -} - -// ---------- HTML helpers ---------- - -function stripTags(html: string): string { - return html - .replace(/<[^>]+>/g, " ") - .replace(/\s+/g, " ") - .trim(); -} - -function firstBold(html: string): string { - const match = html.match(/]*>([\s\S]*?)<\/strong>/); - return match ? stripTags(match[1]) : ""; -} - -interface Link { - url: string; - host: string; - text: string; -} - -function hostOf(url: string): string { - try { - return new URL(url).hostname.replace(/^www\./, ""); - } catch { - return ""; - } -} - -function collectLinks(html: string): Link[] { - const matches = html.matchAll(/]+href="([^"]+)"[^>]*>([\s\S]*?)<\/a>/g); - return [...matches].map((m) => ({ - url: m[1], - host: hostOf(m[1]), - text: stripTags(m[2]), - })); -} - -/** - * Extract the HTML region between a given

    and the next

    . - * Returns an empty string when the heading is not present. - */ -function sliceSection(html: string, headingRx: RegExp): string { - const start = html.search(headingRx); - if (start === -1) return ""; - const afterStart = html.slice(start).replace(headingRx, ""); - const nextH1 = afterStart.search(/]*>/i); - return nextH1 === -1 ? afterStart : afterStart.slice(0, nextH1); -} - -// ---------- primary-URL priority ---------- - -const BLOG_HOST_RX = - /\b(openai|anthropic|deepmind|google|meta|microsoft|nvidia|mistral|unsloth|databricks|cohere|stability|perplexity|vercel|modal|together|replicate|groq)\b/; - -function classifyHost(host: string): PrimaryKind | null { - if (host === "github.com" || host.endsWith(".github.io")) return "github"; - if (host === "huggingface.co" || host === "hf.co") return "huggingface"; - if (host === "arxiv.org" || host === "ar5iv.labs.arxiv.org") return "arxiv"; - if ( - BLOG_HOST_RX.test(host) || - host.endsWith(".ai") || - host.endsWith(".dev") || - host.includes("substack.com") - ) { - return "blog"; - } - if (host === "reddit.com" || host.endsWith(".reddit.com")) return "reddit"; - if (host === "x.com" || host === "twitter.com") return "tweet"; - return null; -} - -// Priority order applied when picking a primary link for a sub-story. -const PRIMARY_PRIORITY: PrimaryKind[] = [ - "github", - "huggingface", - "arxiv", - "blog", - "reddit", - "tweet", -]; - -function isJunk(link: Link): boolean { - if (!link.url) return true; - if ( - link.host === "news.smol.ai" || - link.host === "latent.space" || - link.host === "support.substack.com" || - link.host === "i.redd.it" || - link.host === "preview.redd.it" - ) { - return true; - } - if (link.url.includes("twitter.com/i/lists/")) return true; - if (link.url.includes("x.com/i/")) return true; - return false; -} - -function pickPrimary(links: Link[]): { url: string; kind: PrimaryKind } { - const clean = links.filter((l) => !isJunk(l)); - if (clean.length === 0) return { url: "", kind: "other" }; - - for (const kind of PRIMARY_PRIORITY) { - const hit = clean.find((l) => classifyHost(l.host) === kind); - if (hit) return { url: hit.url, kind }; - } - return { url: clean[0].url, kind: "other" }; -} - -// ---------- Twitter Recap (one sub-story per issue) ---------- - -interface SubStory { - title: string; - url: string; - content: string; -} - -function extractTwitterRecap(html: string): SubStory | null { - const region = sliceSection(html, /]*>\s*AI Twitter Recap\s*<\/h1>/i); - if (!region) return null; - - const title = firstBold(region); - if (!title || title.length < MIN_TWITTER_TITLE_LENGTH) return null; - - const { url } = pickPrimary(collectLinks(region)); - if (!url) return null; - - // Use the first few bullets as the summary instead of the full recap. - const firstBullets = [...region.matchAll(/
  • ([\s\S]*?)<\/li>/g)] - .slice(0, 3) - .map((m) => stripTags(m[1])) - .join(" "); - const summary = - firstBullets || stripTags(region).slice(0, MAX_CONTENT_LENGTH); - - return { title, url, content: summary.slice(0, MAX_CONTENT_LENGTH) }; -} - -// ---------- Reddit Recap (one sub-story per post anchor) ---------- - -const REDDIT_ANCHOR_RX = - /]+href="(https?:\/\/(?:www\.)?reddit\.com\/r\/[^"]+\/comments\/[^"]+)"[^>]*>([\s\S]*?)<\/a>/g; - -interface RedditAnchor { - url: string; - title: string; - start: number; - end: number; -} - -function findRedditAnchors(region: string): RedditAnchor[] { - const anchors: RedditAnchor[] = []; - for (const match of region.matchAll(REDDIT_ANCHOR_RX)) { - anchors.push({ - url: match[1], - title: stripTags(match[2]), - start: match.index ?? 0, - end: (match.index ?? 0) + match[0].length, - }); - } - return anchors; -} - -function extractRedditRecap(html: string): SubStory[] { - const region = sliceSection(html, /]*>\s*AI Reddit Recap\s*<\/h1>/i); - if (!region) return []; - - const anchors = findRedditAnchors(region); - const stories: SubStory[] = []; - - for (let i = 0; i < anchors.length; i++) { - const anchor = anchors[i]; - const nextAnchorStart = - i + 1 < anchors.length ? anchors[i + 1].start : region.length; - - // Stop body at next anchor OR next h2/h3, whichever comes first. - const afterAnchor = region.slice(anchor.end); - const headingRel = afterAnchor.search(/]*>/i); - const headingAbs = - headingRel === -1 ? region.length : anchor.end + headingRel; - - const bodyEnd = Math.min(nextAnchorStart, headingAbs); - const body = region.slice(anchor.start, bodyEnd); - const content = stripTags(body); - if (content.length < MIN_REDDIT_BODY_LENGTH) continue; - - const { url } = pickPrimary(collectLinks(body)); - stories.push({ - title: anchor.title || "(untitled)", - url: url || anchor.url, - content: content.slice(0, MAX_CONTENT_LENGTH), - }); - } - return stories; -} - -// ---------- fetch ---------- - -async function fetchFeedXml(): Promise { - try { - const res = await fetchWithTimeout(FEED_URL); - if (!res.ok) throw new Error(`Status ${res.status}`); - return await res.text(); - } catch (err) { - log(` AI News fetch FAILED: ${err}`); - return null; - } -} - -function toArticle(story: SubStory, pubDate: string): FetchedArticle { - return { - title: story.title, - url: story.url, - content: story.content, - publishedDate: pubDate, - source: "AI News", - sourceType: "aiNews", - }; -} - -export async function fetchAiNews(): Promise { - log("Fetching AI News feed..."); - - const xml = await fetchFeedXml(); - if (!xml) return []; - - const items = parseFeed(xml).filter((it) => isWithinWindow(it.pubDate)); - log(` AI News: ${items.length} issues within window`); - - const articles: FetchedArticle[] = []; - for (const item of items) { - // Skip low-signal days the editors tag as "not much happened". - if (/^not much happened/i.test(item.title)) continue; - - const twitter = extractTwitterRecap(item.contentHtml); - if (twitter) articles.push(toArticle(twitter, item.pubDate)); - - for (const reddit of extractRedditRecap(item.contentHtml)) { - articles.push(toArticle(reddit, item.pubDate)); - } - } - - // Dedup by URL (same repo/post referenced in multiple issues). - const byUrl = new Map(); - for (const article of articles) { - if (!byUrl.has(article.url)) byUrl.set(article.url, article); - } - const deduped = [...byUrl.values()]; - - log(`AI News: ${deduped.length} articles extracted`); - return deduped; -} diff --git a/temp/source/pipeline/sources/email.ts b/temp/source/pipeline/sources/email.ts deleted file mode 100644 index 8ce0d7a872..0000000000 --- a/temp/source/pipeline/sources/email.ts +++ /dev/null @@ -1,551 +0,0 @@ -import { mkdir, readdir, readFile, rename } from "node:fs/promises"; -import { join } from "node:path"; -import type { FetchedArticle } from "@shared/types"; -import { ImapFlow } from "imapflow"; -import { simpleParser } from "mailparser"; -import { b } from "../../baml_client"; -import { search } from "../search"; -import { log } from "../utils"; - -// --------------------------------------------------------------------------- -// Types -// --------------------------------------------------------------------------- - -interface NewsletterSource { - sender: string; - name: string; -} - -/** - * A product named by a newsletter, before its canonical URL is resolved. - * Carries the issue metadata so the eventual FetchedArticle keeps attribution. - */ -interface RawProduct { - name: string; - description: string; - emailDate: string; - newsletterName: string; -} - -// --------------------------------------------------------------------------- -// Newsletter sources -// -// No per-provider link resolver: we never decode tracking redirects. The AI -// reads the products a newsletter reports on (from anchor text + prose) and we -// rediscover each canonical URL by web search. The only per-source data is the -// sender→name mapping used for attribution. -// --------------------------------------------------------------------------- - -export const NEWSLETTER_SOURCES: NewsletterSource[] = [ - { - sender: "@deeperlearning.producthunt.com", - name: "The Frontier by Product Hunt", - }, - { sender: "bensbites@substack.com", name: "Ben's Bites" }, - { sender: "@changelog.com", name: "Changelog News" }, - { sender: "@deeplearning.ai", name: "The Batch" }, - { sender: "@tldrnewsletter.com", name: "TLDR" }, - { sender: "@console.dev", name: "Console" }, - { sender: "@pointer.io", name: "Pointer" }, - { sender: "@importai.net", name: "Import AI" }, - { sender: "@theneurondaily.com", name: "The Neuron" }, - { sender: "@aihero.dev", name: "AI Hero" }, - { sender: "@mail.theresanaiforthat.com", name: "There's An AI For That" }, - { sender: "@daily.therundown.ai", name: "The Rundown AI" }, - { sender: "@technews.therundown.ai", name: "The Rundown AI Tech" }, - { sender: "@mail.joinsuperhuman.ai", name: "Superhuman" }, - { sender: "agentai@mail.beehiiv.com", name: "AgentAI" }, -]; - -// --------------------------------------------------------------------------- -// Sender matching -// --------------------------------------------------------------------------- - -function matchSender(address: string): { name: string } | undefined { - const addr = address.toLowerCase(); - for (const source of NEWSLETTER_SOURCES) { - const pattern = source.sender.toLowerCase(); - if (pattern.startsWith("@") ? addr.endsWith(pattern) : addr === pattern) { - return { name: source.name }; - } - } - return undefined; -} - -// --------------------------------------------------------------------------- -// Product extraction (1 AI call per email) -// --------------------------------------------------------------------------- - -// Strip an email's HTML to text, keeping anchor text and surrounding prose. -// Links are kept as [text](href) as a weak hint, but the hrefs are not trusted -// (they are usually tracking redirects); product identity comes from the words. -function htmlToText(html: string): string { - const cleaned = html - .replace(/]*>[\s\S]*?<\/style>/gi, "") - .replace(/]*>[\s\S]*?<\/script>/gi, "") - .replace( - /]*href="([^"]*)"[^>]*>([\s\S]*?)<\/a>/gi, - (_, href, text) => { - const cleanText = text.replace(/<[^>]+>/g, "").trim(); - return cleanText - ? `[${cleanText}](${href.replace(/&/g, "&")})` - : ""; - }, - ) - .replace(/<[^>]+>/g, " ") - .replace(/&/g, "&") - .replace(/ /g, " ") - .replace(/&#\d+;/g, "") - .replace(/\s+/g, " ") - .trim(); - return cleaned.slice(0, 50_000); -} - -async function extractProducts( - html: string, - newsletterName: string, - emailDate: string, -): Promise { - const text = htmlToText(html); - if (!text) return []; - - try { - const products = await b.ExtractProducts(text); - return products - .filter((p) => p.name?.trim()) - .map((p) => ({ - name: p.name.trim(), - description: p.description?.trim() ?? "", - emailDate, - newsletterName, - })); - } catch (err) { - log(` Failed to extract products from ${newsletterName}: ${err}`); - return []; - } -} - -// --------------------------------------------------------------------------- -// URL resolution via search + verify -// --------------------------------------------------------------------------- - -const RESOLVE_CONCURRENCY = 5; -const SEARCH_CANDIDATES = 5; - -// Domains that are never a product's first-party source: social posts, video, -// and aggregators/content farms. Stripped from candidates before the AI picks, -// so a junk hit can't win by default (the model alone didn't reliably reject -// them). A product whose only hit is one of these is dropped rather than linked. -const DENY_DOMAINS = [ - "x.com", - "twitter.com", - "t.co", - "linkedin.com", - "reddit.com", - "threads.net", - "mastodon.social", - "facebook.com", - "instagram.com", - "youtube.com", - "youtu.be", - "digg.com", - "medium.com", - "news.ycombinator.com", -]; - -function isDenied(url: string): boolean { - try { - const host = new URL(url).hostname.replace(/^www\./, "").toLowerCase(); - return DENY_DOMAINS.some((d) => host === d || host.endsWith(`.${d}`)); - } catch { - return true; // unparseable URL is not a usable link - } -} - -/** - * One product → one canonical URL. Searches for candidates and lets the AI pick - * the best first-party result, rejecting social/aggregator/SEO pages and wrong - * products. Returns null when no candidate is clearly the right source. - */ -async function resolveOne(p: RawProduct): Promise { - const query = `${p.name} ${p.description}`.trim(); - - let results: Awaited>; - try { - results = await search(query, { maxResults: SEARCH_CANDIDATES }); - } catch (err) { - log(` Search failed for "${p.name}": ${err}`); - return null; - } - results = results.filter((r) => !isDenied(r.url)); - if (results.length === 0) { - log(` No usable search result for "${p.name}"`); - return null; - } - - let choiceIdx = 0; - try { - const choice = await b.SelectProductLink( - p.name, - p.description, - results.map((r) => ({ - title: r.title, - url: r.url, - snippet: r.description, - })), - ); - choiceIdx = choice.index; - } catch (err) { - log(` Link selection failed for "${p.name}": ${err}`); - return null; - } - - // index is 1-based; 0 means "no candidate is a clean first-party source". - const picked = choiceIdx >= 1 ? results[choiceIdx - 1] : undefined; - if (!picked) { - log(` Dropped "${p.name}": no first-party result among candidates`); - return null; - } - - return { - title: p.name, - url: picked.url, - content: p.description, - publishedDate: p.emailDate, - source: p.newsletterName, - sourceType: "newsletter" as const, - }; -} - -/** - * Dedupe products by name across all issues in this run (one launch is often - * covered by several newsletters the same day), drop the un-notable ones, then - * resolve each survivor to a URL. The dedupe + notability gate are what keep - * search volume within free Tavily quota. - */ -async function resolveProducts(raw: RawProduct[]): Promise { - if (raw.length === 0) return []; - - const byName = new Map(); - for (const p of raw) { - const key = p.name.toLowerCase(); - if (!byName.has(key)) byName.set(key, p); - } - const unique = [...byName.values()]; - - // Notability gate (one batched AI call) before spending any web search. - let products = unique; - try { - const keep = await b.SelectNotableProducts( - unique.map((p) => ({ name: p.name, description: p.description })), - ); - const keepIdx = new Set(keep); - const selected = unique.filter((_, i) => keepIdx.has(i + 1)); - // Guard against a degenerate empty response dropping everything. - if (selected.length > 0) products = selected; - } catch (err) { - log(` Notability filter failed, resolving all: ${err}`); - } - - log( - ` Resolving ${products.length} notable products via search ` + - `(${raw.length} raw → ${unique.length} unique → ${products.length} notable)`, - ); - - const articles: FetchedArticle[] = []; - for (let i = 0; i < products.length; i += RESOLVE_CONCURRENCY) { - const batch = products.slice(i, i + RESOLVE_CONCURRENCY); - const resolved = await Promise.all(batch.map(resolveOne)); - for (const a of resolved) if (a) articles.push(a); - } - log(` Resolved ${articles.length}/${products.length} products to URLs`); - return articles; -} - -// --------------------------------------------------------------------------- -// IMAP config + error handling -// --------------------------------------------------------------------------- - -function getImapConfig() { - const host = process.env.IMAP_HOST; - const port = Number(process.env.IMAP_PORT || 993); - const user = process.env.IMAP_USER; - const pass = process.env.IMAP_PASSWORD; - - if (!host || !user || !pass) { - throw new Error( - "Missing IMAP env vars: IMAP_HOST, IMAP_USER, IMAP_PASSWORD", - ); - } - return { host, port, user, pass }; -} - -// imapflow throws a bare `Error: Command failed` when the server returns NO/BAD, -// stashing the useful detail on these extra fields. Surface them so failures -// are diagnosable instead of a one-line mystery. -interface ImapError extends Error { - responseStatus?: string; - responseText?: string; - executedCommand?: string; - authenticationFailed?: boolean; - code?: string; -} - -/** Flatten an imapflow error into a single diagnostic line. */ -function describeError(err: unknown): string { - const e = err as ImapError; - const parts: string[] = [e?.message ?? String(err)]; - if (e?.responseStatus) parts.push(`status=${e.responseStatus}`); - if (e?.responseText) parts.push(`response=${JSON.stringify(e.responseText)}`); - if (e?.executedCommand) parts.push(`command=${e.executedCommand}`); - if (e?.code) parts.push(`code=${e.code}`); - return parts.join(" "); -} - -/** Auth failures won't recover on retry; NO/BAD/throttle/network might. */ -function isFatal(err: unknown): boolean { - return (err as ImapError)?.authenticationFailed === true; -} - -/** Honor a server-suggested backoff (throttling) else exponential, capped at 30s. */ -function backoffMs(err: unknown, attempt: number): number { - const txt = (err as ImapError)?.responseText; - const m = txt?.match(/Backoff Time[:=\s]+(\d+)/i); - if (m) return Math.min(Number(m[1]), 30_000); - return Math.min(1000 * 2 ** (attempt - 1), 30_000); -} - -function sleep(ms: number): Promise { - return new Promise((resolve) => setTimeout(resolve, ms)); -} - -async function withRetry( - fn: () => Promise, - label: string, - attempts = 3, -): Promise { - let lastErr: unknown; - for (let attempt = 1; attempt <= attempts; attempt++) { - try { - return await fn(); - } catch (err) { - lastErr = err; - if (isFatal(err)) { - log(` ${label} failed (fatal, not retrying): ${describeError(err)}`); - throw err; - } - log( - ` ${label} attempt ${attempt}/${attempts} failed: ${describeError(err)}`, - ); - if (attempt < attempts) { - const delay = backoffMs(err, attempt); - log(` retrying in ${delay}ms...`); - await sleep(delay); - } - } - } - throw lastErr; -} - -// --------------------------------------------------------------------------- -// IMAP fetch -// --------------------------------------------------------------------------- - -/** - * One full connect → fetch → mark-seen → logout cycle, returning the raw - * products named across all unread newsletter emails. Throws on any IMAP error - * so withRetry can decide whether to retry. The socket is closed on failure so - * dead attempts don't pile up against the server's connection limit. - */ -async function runImapFetch( - config: ReturnType, -): Promise { - const client = new ImapFlow({ - host: config.host, - port: config.port, - secure: true, - auth: { user: config.user, pass: config.pass }, - logger: false, - }); - - const raw: RawProduct[] = []; - - try { - await client.connect(); - const lock = await client.getMailboxLock("sub"); - - try { - // 1. Find unread emails from known newsletter senders - const uidMatches = new Map(); - for await (const msg of client.fetch( - { seen: false }, - { envelope: true, uid: true }, - )) { - const fromAddr = msg.envelope?.from?.[0]?.address?.toLowerCase(); - const match = fromAddr ? matchSender(fromAddr) : undefined; - if (match) uidMatches.set(msg.uid, match); - } - - const uids = [...uidMatches.keys()]; - log(` Found ${uids.length} unread newsletter emails`); - - if (uids.length > 0) { - // 2. Download full messages and extract products - const processedUids: number[] = []; - for await (const msg of client.fetch( - { uid: uids.join(",") }, - { envelope: true, source: true, uid: true }, - )) { - const match = uidMatches.get(msg.uid); - if (!match) continue; - - const emailDate = - msg.envelope?.date?.toISOString() ?? new Date().toISOString(); - const subject = msg.envelope?.subject ?? "(no subject)"; - - log(` Processing: ${match.name} (${subject})`); - - if (!msg.source) { - log(` No message source, skipping`); - processedUids.push(msg.uid); - continue; - } - - const parsed = await simpleParser(msg.source as Buffer); - const html = - typeof parsed.html === "string" - ? parsed.html - : (parsed.textAsHtml ?? ""); - if (!html) { - log(` No HTML content, skipping`); - processedUids.push(msg.uid); - continue; - } - - const products = await extractProducts(html, match.name, emailDate); - log(` Found ${products.length} products`); - raw.push(...products); - - processedUids.push(msg.uid); - } - // 3. Mark all processed emails as seen (after fetch stream is done) - if (processedUids.length > 0) { - await client.messageFlagsAdd( - { uid: processedUids.join(",") }, - ["\\Seen"], - { uid: true }, - ); - } - } - } finally { - lock.release(); - } - - await client.logout(); - } catch (err) { - // Close the socket before a retry so failed attempts don't accumulate - // against the server's concurrent-connection limit. - try { - client.close(); - } catch { - /* already closed */ - } - throw err; - } - - return raw; -} - -export async function fetchNewsletter(): Promise { - if (NEWSLETTER_SOURCES.length === 0) { - log("Newsletter: no sources configured, skipping"); - return []; - } - - const config = getImapConfig(); - log(`Connecting to ${config.host} as ${config.user}...`); - - let raw: RawProduct[] = []; - try { - raw = await withRetry(() => runImapFetch(config), "Newsletter IMAP"); - } catch (err) { - log(`Newsletter fetch failed after retries: ${describeError(err)}`); - } - - const articles = await resolveProducts(raw); - log(`Newsletter: ${articles.length} articles extracted`); - return articles; -} - -// --------------------------------------------------------------------------- -// Local .eml import -// --------------------------------------------------------------------------- - -export async function fetchLocalEmails( - dir = "emails", -): Promise { - const files: string[] = []; - try { - const entries = await readdir(dir, { withFileTypes: true }); - for (const entry of entries) { - if (entry.isFile() && entry.name.endsWith(".eml")) { - files.push(join(dir, entry.name)); - } else if (entry.isDirectory() && entry.name !== "processed") { - const subEntries = await readdir(join(dir, entry.name)); - for (const sub of subEntries) { - if (sub.endsWith(".eml")) { - files.push(join(dir, entry.name, sub)); - } - } - } - } - } catch { - log("Local emails: directory not found, skipping"); - return []; - } - - if (files.length === 0) { - log("Local emails: no .eml files found, skipping"); - return []; - } - - log(`Local emails: found ${files.length} .eml files`); - - const raw: RawProduct[] = []; - const processedDir = join(dir, "processed"); - - for (const filePath of files) { - const file = filePath.split("/").pop() ?? filePath; - const rawEml = await readFile(filePath, "utf-8"); - const parsed = await simpleParser(rawEml); - - const fromAddr = parsed.from?.value?.[0]?.address?.toLowerCase() ?? ""; - const match = matchSender(fromAddr); - const newsletterName = match?.name ?? `Unknown (${fromAddr})`; - - const emailDate = parsed.date?.toISOString() ?? new Date().toISOString(); - const subject = parsed.subject ?? "(no subject)"; - - const html = - typeof parsed.html === "string" ? parsed.html : (parsed.textAsHtml ?? ""); - if (!html) { - log(` ${file}: no HTML content, skipping`); - continue; - } - - log( - ` Processing: ${newsletterName} - ${subject} (${emailDate.slice(0, 10)})`, - ); - - const products = await extractProducts(html, newsletterName, emailDate); - log(` Found ${products.length} products`); - raw.push(...products); - - await mkdir(processedDir, { recursive: true }); - await rename(filePath, join(processedDir, file)); - } - - const articles = await resolveProducts(raw); - log(`Local emails: ${articles.length} articles extracted`); - return articles; -} diff --git a/temp/source/pipeline/sources/extract-content.ts b/temp/source/pipeline/sources/extract-content.ts deleted file mode 100644 index 933e3b7a0a..0000000000 --- a/temp/source/pipeline/sources/extract-content.ts +++ /dev/null @@ -1,145 +0,0 @@ -import { Readability } from "@mozilla/readability"; -import { parseHTML } from "linkedom"; -import { log } from "../utils"; -import { fetchWithTimeout } from "./utils"; - -// These domains can't be scraped server-side - they always return error/login pages. -const SKIP_DOMAINS: string[] = ["x.com", "twitter.com"]; -const SNIPPET_MAX_LENGTH = 500; -const EXTRACT_TIMEOUT_MS = 5_000; -const CONCURRENCY = 5; - -function shouldSkip(url: string): boolean { - try { - const host = new URL(url).hostname; - return SKIP_DOMAINS.some((d) => host === d || host.endsWith(`.${d}`)); - } catch { - return true; - } -} - -function ensureBody(html: string): string { - if (/]/i.test(html)) return html; - return `${html}`; -} - -// Phrases that indicate a page blocked us instead of returning real content. -const BLOCKER_PATTERNS: RegExp[] = [ - /something went wrong.*don't fret/i, - /disable.*privacy\s+extensions/i, - /privacy\s+extensions.*and.*retry/i, - /please\s+(?:sign|log)\s*in/i, - /sign\s*in\s+to\s+(?:continue|read|access)/i, - /log\s*in\s+to\s+(?:continue|read|access)/i, - /subscribe\s+to\s+(?:continue|read|access|unlock)/i, - /create\s+an?\s+account\s+to\s+(?:continue|read|access)/i, - /enable\s+javascript\s+to\s+(?:continue|view|use)/i, - /javascript\s+is\s+(?:disabled|required)/i, - /access\s+denied/i, - /403\s+forbidden/i, -]; - -function isBlockerContent(text: string): boolean { - if (text.length < 50) return true; // too short to be real article text - return BLOCKER_PATTERNS.some((re) => re.test(text)); -} - -function extractText(html: string, maxLength?: number): string { - try { - const { document } = parseHTML(ensureBody(html)); - const reader = new Readability(document as unknown as Document); - const article = reader.parse(); - if (article) { - const text = - article.textContent?.replace(/\s+/g, " ").trim() || - article.excerpt || - ""; - if (!text || isBlockerContent(text)) return ""; - return maxLength !== undefined ? text.slice(0, maxLength) : text; - } - } catch { - // fall through - } - return ""; -} - -async function extractHtml(url: string): Promise { - if (shouldSkip(url)) return ""; - - try { - const res = await fetchWithTimeout(url, EXTRACT_TIMEOUT_MS); - if (!res.ok) return ""; - - const contentType = res.headers.get("content-type") ?? ""; - if (!contentType.includes("text/html")) return ""; - - return await res.text(); - } catch { - return ""; - } -} - -async function batchFetch( - urls: string[], - fn: (url: string, idx: number, total: number) => Promise, -): Promise> { - const map = new Map(); - for (let i = 0; i < urls.length; i += CONCURRENCY) { - const batch = urls.slice(i, i + CONCURRENCY); - const results = await Promise.allSettled( - batch.map((url, j) => - fn(url, i + j, urls.length).then((value) => ({ url, value })), - ), - ); - for (const r of results) { - if (r.status === "fulfilled" && r.value.value) { - map.set(r.value.url, r.value.value); - } - } - } - return map; -} - -export async function extractContent< - T extends { url: string; content: string }, ->(articles: T[]): Promise { - const needsContent = articles.filter((a) => !a.content); - if (needsContent.length === 0) return articles; - - const uniqueUrls = [...new Set(needsContent.map((a) => a.url))]; - log(` Extracting content for ${uniqueUrls.length} URLs...`); - - const snippetMap = await batchFetch(uniqueUrls, async (url) => - extractText(await extractHtml(url), SNIPPET_MAX_LENGTH), - ); - - log(` Extracted ${snippetMap.size}/${uniqueUrls.length} snippets`); - - return articles.map((a) => { - const snippet = snippetMap.get(a.url); - return snippet ? { ...a, content: snippet } : a; - }); -} - -export async function reExtractFullContent( - articles: { url: string }[], -): Promise> { - if (articles.length === 0) return new Map(); - - const uniqueUrls = [...new Set(articles.map((a) => a.url))]; - log(` Re-extracting full content for ${uniqueUrls.length} URLs...`); - - const contentMap = await batchFetch(uniqueUrls, async (url, idx, total) => { - log(` [${idx + 1}/${total}] Fetching: ${url}`); - const t0 = Date.now(); - const content = extractText(await extractHtml(url)); - const ms = Date.now() - t0; - log( - ` [${idx + 1}/${total}] ${content ? `OK (${content.length} chars, ${ms}ms)` : `no content (${ms}ms)`}: ${url}`, - ); - return content; - }); - - log(` Re-extracted ${contentMap.size}/${uniqueUrls.length} full texts`); - return contentMap; -} diff --git a/temp/source/pipeline/sources/hn.ts b/temp/source/pipeline/sources/hn.ts deleted file mode 100644 index 0a53f07da5..0000000000 --- a/temp/source/pipeline/sources/hn.ts +++ /dev/null @@ -1,60 +0,0 @@ -import type { FetchedArticle } from "@shared/types"; -import { log } from "../utils"; -import { extractContent } from "./extract-content"; -import { cleanTitle, fetchWithTimeout, isWithinWindow } from "./utils"; - -const HN_TOP = "https://hacker-news.firebaseio.com/v0/topstories.json"; -const HN_ITEM = "https://hacker-news.firebaseio.com/v0/item"; -const HN_FETCH_LIMIT = 200; - -const HN_AI_KEYWORDS = - /\b(ai|llm|gpt|claude|gemini|llama|openai|anthropic|deepseek|mistral|opencode|tokens|transformer|diffusion|machine.?learning|deep.?learning|neural.?net|language.?model|artificial.?intelligen|stable.?diffusion|midjourney|copilot|chatbot|rag|fine.?tun|embedding|token|lora|rlhf|gguf|ollama|hugging.?face)\b/i; - -interface HNItem { - id: number; - title?: string; - url?: string; - score?: number; - descendants?: number; - time?: number; - type?: string; -} - -export async function fetchHN(): Promise { - log("Fetching Hacker News top stories..."); - const res = await fetchWithTimeout(HN_TOP); - const ids: number[] = (await res.json()) as number[]; - - const topIds = ids.slice(0, HN_FETCH_LIMIT); - const results = await Promise.allSettled( - topIds.map(async (id) => { - const r = await fetchWithTimeout(`${HN_ITEM}/${id}.json`); - return r.json() as Promise; - }), - ); - - const articles: FetchedArticle[] = []; - for (const result of results) { - if (result.status !== "fulfilled") continue; - const item = result.value; - if (!item || item.type !== "story" || !item.title) continue; - if (!HN_AI_KEYWORDS.test(item.title)) continue; - const pubDate = item.time - ? new Date(item.time * 1000).toISOString() - : undefined; - if (!isWithinWindow(pubDate)) continue; - - const cleaned = cleanTitle(item.title); - articles.push({ - title: cleaned, - url: item.url ?? `https://news.ycombinator.com/item?id=${item.id}`, - content: "", - publishedDate: pubDate ?? new Date().toISOString(), - source: "Hacker News", - sourceType: "hackerNews", - }); - } - - log(`Hacker News: ${articles.length} AI-related stories`); - return extractContent(articles); -} diff --git a/temp/source/pipeline/sources/rss.ts b/temp/source/pipeline/sources/rss.ts deleted file mode 100644 index eae36a86c4..0000000000 --- a/temp/source/pipeline/sources/rss.ts +++ /dev/null @@ -1,103 +0,0 @@ -import type { FetchedArticle } from "@shared/types"; -import Parser from "rss-parser"; -import { resolveTwitterUrl } from "../search"; -import { log } from "../utils"; -import { cleanTitle, isWithinWindow } from "./utils"; - -const SOURCES = [ - { name: "Aligned News", rssUrl: "https://alignednews.com/feed.xml" }, -]; - -/** Only ingest these RSS categories - others are noise (drama, events, business, etc.). */ -const ALLOWED_CATEGORIES = new Set(["tips", "products"]); - -const TWITTER_HOSTS = new Set(["x.com", "twitter.com", "t.co"]); - -function isTwitterUrl(url: string): boolean { - try { - return TWITTER_HOSTS.has(new URL(url).hostname); - } catch { - return false; - } -} - -type CustomItem = Parser.Item & { categories?: string[]; category?: string }; - -const parser = new Parser, CustomItem>({ - timeout: 15_000, - headers: { "User-Agent": "Agentique/2.0 (+https://agentique.ch)" }, - customFields: { item: [["category", "category"]] }, -}); - -export async function fetchRss(): Promise { - const articles: FetchedArticle[] = []; - - const results = await Promise.allSettled( - SOURCES.map(async (source) => { - log(`Fetching ${source.name}...`); - const feed = await parser.parseURL(source.rssUrl); - - const withinWindow = (feed.items ?? []).filter((item) => - isWithinWindow(item.pubDate ?? item.isoDate), - ); - - // Filter to allowed categories - const relevant = withinWindow.filter((item) => { - const cats: string[] = Array.isArray(item.categories) - ? item.categories - : item.category - ? [item.category as string] - : []; - return cats.some((c) => ALLOWED_CATEGORIES.has(c.toLowerCase())); - }); - - log( - ` ${source.name}: ${withinWindow.length} in window, ${relevant.length} after category filter`, - ); - - // Resolve x.com URLs to real article URLs via Brave Search - const resolved = await Promise.all( - relevant.map(async (item) => { - const rawUrl = item.link ?? ""; - const description = item.contentSnippet ?? item.content ?? ""; - const title = cleanTitle(item.title ?? "(no title)"); - - let url = rawUrl; - if (isTwitterUrl(rawUrl)) { - log(` Resolving tweet: ${title}`); - const found = await resolveTwitterUrl(title, description); - if (found) url = found; - } - - return { - title, - url, - // Use the RSS description as content - it's a quality AI summary, - // far better than what scraping x.com would return. - content: description, - publishedDate: - item.pubDate ?? item.isoDate ?? new Date().toISOString(), - source: source.name, - sourceType: "rss" as const, - }; - }), - ); - - return { source: source.name, items: resolved }; - }), - ); - - for (const result of results) { - if (result.status === "fulfilled") { - log( - ` ${result.value.source}: ${result.value.items.length} articles ready`, - ); - articles.push(...result.value.items); - } else { - log(` FAILED: ${result.reason}`); - } - } - - log(`RSS: ${articles.length} articles`); - return articles; -} diff --git a/temp/source/pipeline/sources/substack-sources.json b/temp/source/pipeline/sources/substack-sources.json deleted file mode 100644 index c3fd0f6541..0000000000 --- a/temp/source/pipeline/sources/substack-sources.json +++ /dev/null @@ -1,430 +0,0 @@ -[ - { - "name": "Nate's Substack", - "rssUrl": "https://natesnewsletter.substack.com/feed" - }, - { - "name": "Interconnects AI", - "rssUrl": "https://www.interconnects.ai/feed" - }, - { - "name": "AI Supremacy", - "rssUrl": "https://www.ai-supremacy.com/feed" - }, - { - "name": "The AI Maker", - "rssUrl": "https://aimaker.substack.com/feed" - }, - { - "name": "Understanding AI", - "rssUrl": "https://www.understandingai.org/feed" - }, - { - "name": "AI Tidbits", - "rssUrl": "https://www.aitidbits.ai/feed" - }, - { - "name": "Deep (Learning) Focus", - "rssUrl": "https://cameronrwolfe.substack.com/feed" - }, - { - "name": "AI Newsletter", - "rssUrl": "https://nlp.elvissaravia.com/feed" - }, - { - "name": "Artificial Ignorance", - "rssUrl": "https://www.ignorance.ai/feed" - }, - { - "name": "AI by Hand", - "rssUrl": "https://www.byhand.ai/feed" - }, - { - "name": "Practical AI for Solo Entrepreneurs", - "rssUrl": "https://soloailab.substack.com/feed" - }, - { - "name": "Last Week in AI", - "rssUrl": "https://lastweekin.ai/feed" - }, - { - "name": "The Generative Programmer", - "rssUrl": "https://generativeprogrammer.com/feed" - }, - { - "name": "Designing with AI", - "rssUrl": "https://newsletter.victordibia.com/feed" - }, - { - "name": "Andrej Karpathy", - "rssUrl": "https://karpathy.substack.com/feed" - }, - { - "name": "Ben's Bites", - "rssUrl": "https://www.bensbites.com/feed" - }, - { - "name": "Machine Learning Pills", - "rssUrl": "https://mlpills.substack.com/feed" - }, - { - "name": "Chipstrat", - "rssUrl": "https://www.chipstrat.com/feed" - }, - { - "name": "Making AI Accessible", - "rssUrl": "https://louisbouchard.substack.com/feed" - }, - { - "name": "Redwood Research", - "rssUrl": "https://blog.redwoodresearch.org/feed" - }, - { - "name": "Works on My Machine", - "rssUrl": "https://worksonmymachine.ai/feed" - }, - { - "name": "Hamel's Substack", - "rssUrl": "https://hamelhusain.substack.com/feed" - }, - { - "name": "The AI Engineer", - "rssUrl": "https://newsletter.owainlewis.com/feed" - }, - { - "name": "Trelis Research", - "rssUrl": "https://trelis.substack.com/feed" - }, - { - "name": "Gradient Flow", - "rssUrl": "https://gradientflow.substack.com/feed" - }, - { - "name": "Generally Intelligent", - "rssUrl": "https://generallyintelligent.substack.com/feed" - }, - { - "name": "Building AI Products From Scratch", - "rssUrl": "https://mikikobazeley.substack.com/feed" - }, - { - "name": "LLM Watch", - "rssUrl": "https://www.llmwatch.com/feed" - }, - { - "name": "Loop Engineering", - "rssUrl": "https://linas.substack.com/feed" - }, - { - "name": "Cobus Greyling on LLMs", - "rssUrl": "https://cobusgreyling.substack.com/feed" - }, - { - "name": "Elevate by Addy Osmani", - "rssUrl": "https://addyo.substack.com/feed" - }, - { - "name": "DiamantAI", - "rssUrl": "https://newsletter.diamant-ai.com/feed" - }, - { - "name": "MLWhiz", - "rssUrl": "https://www.mlwhiz.com/feed" - }, - { - "name": "Semantics & Systems", - "rssUrl": "https://khaledea.substack.com/feed" - }, - { - "name": "Token Contributions", - "rssUrl": "https://tokencontributions.substack.com/feed" - }, - { - "name": "Generative History", - "rssUrl": "https://generativehistory.substack.com/feed" - }, - { - "name": "Digital Thoughts", - "rssUrl": "https://thoughts.jock.pl/feed" - }, - { - "name": "Modern Mom Playbook", - "rssUrl": "https://modernmomplaybook.substack.com/feed" - }, - { - "name": "Prompt-Led Product | For PMs Building in the AI Era", - "rssUrl": "https://promptledproduct.substack.com/feed" - }, - { - "name": "AI Weekender", - "rssUrl": "https://aiweekender.substack.com/feed" - }, - { - "name": "Senior Data Science Lead", - "rssUrl": "https://joseparreogarcia.substack.com/feed" - }, - { - "name": "AI Espresso | your tech brew", - "rssUrl": "https://aiespressotechbrew.substack.com/feed" - }, - { - "name": "AI by Aakash", - "rssUrl": "https://www.aibyaakash.com/feed" - }, - { - "name": "Engincan Veske", - "rssUrl": "https://engincanveske.substack.com/feed" - }, - { - "name": "ModelCraft", - "rssUrl": "https://modelcraft.substack.com/feed" - }, - { - "name": "Vik's Newsletter", - "rssUrl": "https://www.viksnewsletter.com/feed" - }, - { - "name": "Standout Systems by Teodora", - "rssUrl": "https://teodoracoach.substack.com/feed" - }, - { - "name": "The Circuit", - "rssUrl": "https://metacircuits.substack.com/feed" - }, - { - "name": "Artificial Enigma", - "rssUrl": "https://idakaukonen.substack.com/feed" - }, - { - "name": "Travis Sparks - Sparkry.AI + Neurodivergence + Business", - "rssUrl": "https://sparkryai.substack.com/feed" - }, - { - "name": "AI Disruption", - "rssUrl": "https://aidisruption.ai/feed" - }, - { - "name": "Cash & Cache", - "rssUrl": "https://cashandcache.substack.com/feed" - }, - { - "name": "Prosper", - "rssUrl": "https://prosperinai.substack.com/feed" - }, - { - "name": "AI Superhero", - "rssUrl": "https://shmulc.substack.com/feed" - }, - { - "name": "AI blew my mind", - "rssUrl": "https://aiblewmymind.substack.com/feed" - }, - { - "name": "ToxSec - AI and Cybersecurity", - "rssUrl": "https://www.toxsec.com/feed" - }, - { - "name": "The Ai Rabbit Hole", - "rssUrl": "https://jtnovelo2131.substack.com/feed" - }, - { - "name": "The Zhang-ularity", - "rssUrl": "https://fzhang.substack.com/feed" - }, - { - "name": "Asymmetric Jump", - "rssUrl": "https://asymmetricjump.substack.com/feed" - }, - { - "name": "Automato: Smarter Work in the Age of AI", - "rssUrl": "https://automato.substack.com/feed" - }, - { - "name": "Empathetic AI Lab", - "rssUrl": "https://aicompanionlab.substack.com/feed" - }, - { - "name": "Leadership in Change", - "rssUrl": "https://leadershipinchange.com/feed" - }, - { - "name": "The FoLD", - "rssUrl": "https://liamdarmody.substack.com/feed" - }, - { - "name": "AI Echoes", - "rssUrl": "https://aiechoes.substack.com/feed" - }, - { - "name": "AI in public", - "rssUrl": "https://humzakhalid.substack.com/feed" - }, - { - "name": "Artificial Code", - "rssUrl": "https://artificialcode.substack.com/feed" - }, - { - "name": "Purposeful AI", - "rssUrl": "https://purposefulai.substack.com/feed" - }, - { - "name": "Shrivu's Substack", - "rssUrl": "https://blog.sshh.io/feed" - }, - { - "name": "The AI Architect", - "rssUrl": "https://mvidmar.substack.com/feed" - }, - { - "name": "The Humans in the Loop", - "rssUrl": "https://www.thehumansintheloop.ai/feed" - }, - { - "name": "AI Enhanced Engineer", - "rssUrl": "https://aienhancedengineer.substack.com/feed" - }, - { - "name": "Product with Attitude", - "rssUrl": "https://karozieminski.substack.com/feed" - }, - { - "name": "And Yet It Moves", - "rssUrl": "https://andyetitmoves.substack.com/feed" - }, - { - "name": "Department of Product", - "rssUrl": "https://departmentofproduct.substack.com/feed" - }, - { - "name": "Design with AI", - "rssUrl": "https://designwithai.substack.com/feed" - }, - { - "name": "Limited Edition Jonathan", - "rssUrl": "https://limitededitionjonathan.substack.com/feed" - }, - { - "name": "Product Growth", - "rssUrl": "https://www.news.aakashg.com/feed" - }, - { - "name": "The Outer Loop", - "rssUrl": "https://theouterloop.substack.com/feed" - }, - { - "name": "Co-Write with AI", - "rssUrl": "https://articles.cowritewithai.com/feed" - }, - { - "name": "Exploring ChatGPT", - "rssUrl": "https://exploringchatgpt.substack.com/feed" - }, - { - "name": "Hello AI World", - "rssUrl": "https://malihaarshad1.substack.com/feed" - }, - { - "name": "Savvy Sloth", - "rssUrl": "https://savvysloth.substack.com/feed" - }, - { - "name": "Turing Post", - "rssUrl": "https://turingpost.substack.com/feed" - }, - { - "name": "Marily’s AI Product Academy Newsletter", - "rssUrl": "https://marily.substack.com/feed" - }, - { - "name": "ByteByteGo Newsletter", - "rssUrl": "https://blog.bytebytego.com/feed" - }, - { - "name": "The Tech Buffet", - "rssUrl": "https://thetechbuffet.substack.com/feed" - }, - { - "name": "SwirlAI Newsletter", - "rssUrl": "https://www.newsletter.swirlai.com/feed" - }, - { - "name": "Simon Willison’s Newsletter", - "rssUrl": "https://simonw.substack.com/feed" - }, - { - "name": "Ahead of AI", - "rssUrl": "https://magazine.sebastianraschka.com/feed" - }, - { - "name": "The Pipe & The Line", - "rssUrl": "https://thepipeandtheline.substack.com/feed" - }, - { - "name": "Coding with Intelligence", - "rssUrl": "https://codingwithintelligence.com/feed" - }, - { - "name": "AI for Software Engineers", - "rssUrl": "https://www.aiforswes.com/feed" - }, - { - "name": "Thonk From First Principles", - "rssUrl": "https://www.thonking.ai/feed" - }, - { - "name": "The Kaitchup – AI on a Budget", - "rssUrl": "https://kaitchup.substack.com/feed" - }, - { - "name": "ThursdAI - Highest signal weekly AI news show", - "rssUrl": "https://sub.thursdai.news/feed" - }, - { - "name": "The AI Break", - "rssUrl": "https://theaibreak.substack.com/feed" - }, - { - "name": "Artificial Corner", - "rssUrl": "https://artificialcorner.com/feed" - }, - { - "name": "The Ontologist", - "rssUrl": "https://ontologist.substack.com/feed" - }, - { - "name": "The Technical Executive", - "rssUrl": "https://sderosiaux.substack.com/feed" - }, - { - "name": "AI Health Uncut", - "rssUrl": "https://www.fixhealth.ai/feed" - }, - { - "name": "Exploring Artificial Intelligence", - "rssUrl": "https://exploringartificialintelligence.substack.com/feed" - }, - { - "name": "All Agents Considered", - "rssUrl": "https://allagentsconsidered.substack.com/feed" - }, - { - "name": "ai.tism", - "rssUrl": "https://aitism.substack.com/feed" - }, - { - "name": "Practical AI Brief", - "rssUrl": "https://practicalaibrief.substack.com/feed" - }, - { - "name": "Matt Paige", - "rssUrl": "https://mattpaige68.substack.com/feed" - }, - { - "name": "Artificial Intelligence Learning 🤖🧠🦾", - "rssUrl": "https://offthegridxp.substack.com/feed" - }, - { - "name": "Machine Learning At Scale", - "rssUrl": "https://machinelearningatscale.substack.com/feed" - } -] diff --git a/temp/source/pipeline/sources/substack.ts b/temp/source/pipeline/sources/substack.ts deleted file mode 100644 index 8cbabb58c8..0000000000 --- a/temp/source/pipeline/sources/substack.ts +++ /dev/null @@ -1,137 +0,0 @@ -import type { FetchedArticle } from "@shared/types"; -import Parser from "rss-parser"; -import { ProxyAgent, fetch as undiciFetch } from "undici"; -import { log } from "../utils"; -import SOURCES from "./substack-sources.json"; -import { cleanTitle, isWithinWindow } from "./utils"; - -const proxyUrl = process.env.RESIDENTIAL_PROXY_URL; -const dispatcher = proxyUrl ? new ProxyAgent(proxyUrl) : undefined; - -// One-time, credential-redacted log so CI confirms what proxy (if any) is wired. -if (proxyUrl) { - try { - const u = new URL(proxyUrl); - log( - `Substack proxy: ${u.protocol}//${u.hostname}:${u.port || "(default)"} (auth: ${u.username ? "yes" : "no"})`, - ); - } catch { - log(`Substack proxy: set but unparseable as URL (len ${proxyUrl.length})`); - } -} else { - log(`Substack proxy: none (RESIDENTIAL_PROXY_URL unset)`); -} - -// Recursively unwraps Error.cause so a bare undici "fetch failed" reveals the -// real reason (ENOTFOUND, ECONNREFUSED, SOCKS, TLS, proxy 407, etc.). -function describeError(err: unknown, depth = 0): string { - const e = err as { - name?: string; - code?: string; - message?: string; - cause?: unknown; - }; - if (!e) return String(err); - const code = e.code !== undefined ? `(${e.code})` : ""; - const head = `${e.name ?? "Error"}${code}: ${e.message ?? e}`; - if (e.cause && depth < 4) - return `${head} <- ${describeError(e.cause, depth + 1)}`; - return head; -} - -const BROWSER_HEADERS = { - "User-Agent": - "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/124.0.0.0 Safari/537.36", - Accept: "text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8", - "Accept-Language": "en-US,en;q=0.9", -}; - -// rss-parser fetches via Node's native https.get and ignores any custom -// transport, so it can never route through our residential proxy. Substack's -// native *.substack.com feeds sit behind Cloudflare and 403 datacenter IPs -// (e.g. CI runners), so we fetch the XML ourselves and hand the string to -// parser.parseString. -// -// Strategy: try a direct request first - this works for custom-domain feeds -// and from clean IPs, and keeps us off the proxy when we don't need it. Only -// when Cloudflare blocks us (403/429) do we retry through the residential -// proxy. Failures surface the underlying cause (undici wraps everything in a -// bare "fetch failed") so CI logs are diagnosable. -async function fetchOnce(url: string, useProxy: boolean) { - try { - return await undiciFetch(url, { - headers: BROWSER_HEADERS, - ...(useProxy && dispatcher ? { dispatcher } : {}), - }); - } catch (err) { - throw new Error( - `fetch failed${useProxy ? " (via proxy)" : ""}: ${describeError(err)}`, - ); - } -} - -async function fetchFeedXml( - url: string, - retries = 2, - backoff = 2000, -): Promise { - for (let attempt = 0; ; attempt++) { - // attempt 0 is direct; subsequent attempts route through the proxy if set - const useProxy = attempt > 0 && !!dispatcher; - const res = await fetchOnce(url, useProxy); - if (res.ok) return res.text(); - if ( - (res.status === 403 || res.status === 429) && - attempt < retries && - dispatcher - ) { - await new Promise((r) => setTimeout(r, backoff * 2 ** attempt)); - continue; - } - throw new Error(`Status code ${res.status}`); - } -} - -const parser = new Parser({ timeout: 15_000 }); - -export async function fetchSubstack(): Promise { - const articles: FetchedArticle[] = []; - - const results = await Promise.all( - SOURCES.map(async (source) => { - log(`Fetching ${source.name}...`); - try { - const xml = await fetchFeedXml(source.rssUrl); - const feed = await parser.parseString(xml); - - const withinWindow = (feed.items ?? []).filter((item) => - isWithinWindow(item.pubDate ?? item.isoDate), - ); - - log(` ${source.name}: ${withinWindow.length} in window`); - - const items = withinWindow.map((item) => ({ - title: cleanTitle(item.title ?? "(no title)"), - url: item.link ?? "", - content: item.contentSnippet ?? item.content ?? "", - publishedDate: - item.pubDate ?? item.isoDate ?? new Date().toISOString(), - source: source.name, - sourceType: "rss" as const, - })); - - return items; - } catch (err) { - log(` FAILED ${source.name}: ${(err as Error).message}`); - return [] as FetchedArticle[]; - } - }), - ); - - for (const items of results) { - articles.push(...items); - } - - log(`Substack: ${articles.length} articles`); - return articles; -} diff --git a/temp/source/pipeline/sources/utils.ts b/temp/source/pipeline/sources/utils.ts deleted file mode 100644 index 3b17a64e25..0000000000 --- a/temp/source/pipeline/sources/utils.ts +++ /dev/null @@ -1,38 +0,0 @@ -// Source-layer helpers shared between hn, rss, email, and extract-content. - -const HN_PREFIX_RE = /^(?:Show|Launch|Ask|Tell) HN:\s*/i; - -// Strip "Show HN:" / "Ask HN:" style prefixes from story titles. -export function cleanTitle(title: string): string { - return title.replace(HN_PREFIX_RE, "").trim(); -} - -const FETCH_TIMEOUT_MS = 15_000; - -export async function fetchWithTimeout( - url: string, - timeoutMs = FETCH_TIMEOUT_MS, -): Promise { - const controller = new AbortController(); - const timer = setTimeout(() => controller.abort(), timeoutMs); - try { - return await fetch(url, { signal: controller.signal }); - } finally { - clearTimeout(timer); - } -} - -const WINDOW_HOURS = 168; - -// True if `dateStr` is within the last N hours (default 1 week). -// Missing/unparseable dates are treated as "within" (pass-through). -export function isWithinWindow( - dateStr: string | undefined, - windowHours: number = WINDOW_HOURS, -): boolean { - if (!dateStr) return true; - const published = new Date(dateStr); - const now = new Date(); - const hoursAgo = (now.getTime() - published.getTime()) / (1000 * 60 * 60); - return hoursAgo <= windowHours; -} diff --git a/temp/source/pipeline/steps.ts b/temp/source/pipeline/steps.ts deleted file mode 100644 index 52e8b2c95b..0000000000 --- a/temp/source/pipeline/steps.ts +++ /dev/null @@ -1,88 +0,0 @@ -// Shared helpers used across pipeline steps. -// -// - trustBySource: maps source name -> "high" | "medium" | "low" -// - toArticleInputs: builds ArticleInput[] from FetchedArticle[] for BAML calls - -import type { ArticleKind, FetchedArticle } from "@shared/types"; -import type { ArticleInput } from "../baml_client/types"; -import { NEWSLETTER_SOURCES } from "./sources/email"; - -// Minimum ScoreArticles score (1-100) an article must reach to be kept. -// Shared by the pipeline (run.ts) and the feed-discovery gate (sources/discover) -// so a feed is only added when its recent items would survive the same bar. -export const SCORE_THRESHOLD = 76; - -// Source trust is used as a signal in the scoring prompt: high-trust sources -// get a +1 bonus when content quality is comparable. Newsletter sources are -// curated by humans, so they all count as high trust. -export const trustBySource: Record = { - "Hacker News": "high", - "AI News": "high", -}; -for (const ns of NEWSLETTER_SOURCES) { - trustBySource[ns.name] = "high"; -} - -/** - * Detects a GitHub repo link inside fetched article content. - * Matches github.com/owner/repo paths; ignores non-repo pages like - * github.com/features or github.com/login. - * Returns the matched URL, or null if none found. - */ -export function githubRepoFromContent(content: string): string | null { - const match = content.match( - /https?:\/\/(?:www\.)?github\.com\/([A-Za-z0-9_.-]+)\/([A-Za-z0-9_.-]+)/, - ); - if (!match) return null; - const [, owner, repo] = match; - // Filter out GitHub meta-pages that aren't repos - const nonRepoOwners = new Set([ - "features", - "login", - "pricing", - "about", - "marketplace", - "explore", - "topics", - "collections", - "trending", - "sponsors", - "orgs", - "apps", - "contact", - "security", - ]); - if (nonRepoOwners.has(owner.toLowerCase())) return null; - return `https://github.com/${owner}/${repo}`; -} - -/** - * URL-based kind detection - overrides LLM classification for unambiguous cases. - * Returns null when the URL gives no signal (LLM should decide). - */ -export function kindFromUrl(url: string): ArticleKind | null { - try { - const host = new URL(url).hostname.replace(/^www\./, ""); - if (host === "github.com" || host === "gitlab.com") return "repo"; - if (host === "huggingface.co" || host === "hf.co") return "model"; - if (host === "arxiv.org" || host === "ar5iv.labs.arxiv.org") return "paper"; - } catch { - // malformed URL - fall through - } - return null; -} - -// Converts FetchedArticles to ArticleInput for BAML scoring/dedup/title calls. -// Snippets are capped at 200 chars - enough signal for the LLM without -// paying the cost of the full content we captured during fetch. -export function toArticleInputs(articles: FetchedArticle[]): ArticleInput[] { - return articles.map( - (a): ArticleInput => ({ - url: a.url, - title: a.title, - source: a.source, - snippet: a.content ? a.content.slice(0, 200) : undefined, - trust: trustBySource[a.source], - }), - ); -} diff --git a/temp/source/pipeline/utils.ts b/temp/source/pipeline/utils.ts deleted file mode 100644 index dea4eba8e4..0000000000 --- a/temp/source/pipeline/utils.ts +++ /dev/null @@ -1,59 +0,0 @@ -// Genuinely cross-cutting helpers - used from both the web app side -// (app/api/*) and the pipeline/sources/scripts side. -// -// Source-layer helpers (cleanTitle, fetchWithTimeout, isWithinWindow) live -// in src/sources/utils.ts. - -const TIMEZONE = "Europe/Zurich"; - -export function todayDateString(): string { - return new Date().toLocaleDateString("sv-SE", { timeZone: TIMEZONE }); -} - -export const wait = (ms: number) => new Promise((r) => setTimeout(r, ms)); - -export function log(message: string): void { - const ts = new Date().toISOString(); - console.log(`[${ts}] ${message}`); -} - -// Strip wrapper artifacts the LLM sometimes echoes around an improved title: -// a leading "[Source]" tag and surrounding straight or smart quotes. -// Returns the bare title text. -export function stripTitleWrappers(text: string): string { - let s = text.trim(); - s = s.replace(/^\[[^\]]+\]\s*/, ""); - s = s.replace(/^\d+\.\s*/, ""); - const pairs: [string, string][] = [ - ['"', '"'], - ["'", "'"], - ["“", "”"], - ["‘", "’"], - ]; - for (const [open, close] of pairs) { - if (s.startsWith(open) && s.endsWith(close) && s.length >= 2) { - s = s.slice(open.length, s.length - close.length).trim(); - break; - } - } - return s; -} - -// Strip smart quotes, emoji, and other unicode junk LLMs like to emit. -export function sanitizeLlmText(text: string): string { - return text - .replace(/[\u2018\u2019\u201A]/g, "'") - .replace(/[\u201C\u201D\u201E]/g, '"') - .replace(/\u2192/g, "->") - .replace(/\u2190/g, "<-") - .replace(/\u2194/g, "<->") - .replace(/[\u2013\u2014]/g, "-") - .replace(/\u2026/g, "...") - .replace(/[\u2022\u2023\u25E6\u25AA\u25AB]/g, "-") - .replace( - /[\p{Emoji_Presentation}\p{Extended_Pictographic}]\uFE0F?(\u200D[\p{Emoji_Presentation}\p{Extended_Pictographic}]\uFE0F?)*/gu, - "", - ) - .replace(/ {2,}/g, " ") - .trim(); -} diff --git a/temp/source/shared/db/articles.ts b/temp/source/shared/db/articles.ts deleted file mode 100644 index 499a6e0675..0000000000 --- a/temp/source/shared/db/articles.ts +++ /dev/null @@ -1,370 +0,0 @@ -import { - and, - asc, - desc, - eq, - gte, - inArray, - isNotNull, - isNull, - like, - or, - sql, -} from "drizzle-orm"; -import * as schema from "../schema"; -import type { DbArticle, FetchedArticle } from "../types"; -import { db } from "./client"; - -function normalizeDate(dateStr: string | undefined): string | null { - if (!dateStr) return null; - try { - return new Date(dateStr).toISOString(); - } catch { - return dateStr; - } -} - -function daysAgoIso(days: number): string { - return new Date(Date.now() - days * 24 * 60 * 60 * 1000).toISOString(); -} - -export async function getRecentArticles( - days: number, -): Promise<(DbArticle & { url: string })[]> { - const rows = await db() - .select() - .from(schema.articles) - .where(gte(schema.articles.published_at, daysAgoIso(days))) - .orderBy(desc(schema.articles.published_at)); - return rows as unknown as (DbArticle & { url: string })[]; -} - -export async function insertArticle(article: FetchedArticle): Promise { - const result = await db() - .insert(schema.articles) - .values({ - title: article.title, - content: article.content, - source: article.source, - source_type: article.sourceType, - published_at: normalizeDate(article.publishedDate), - url: article.url, - }) - .returning({ id: schema.articles.id }); - const articleId = result[0].id; - await db() - .insert(schema.articleUrls) - .values({ url: article.url, article_id: articleId }); - return articleId; -} - -export async function updateScore( - articleId: number, - score: number, -): Promise { - await db() - .update(schema.articles) - .set({ score }) - .where(eq(schema.articles.id, articleId)); -} - -export async function updateCategories( - articleId: number, - summary: string, - categories: string[], -): Promise { - await db() - .update(schema.articles) - .set({ summary, categories: JSON.stringify(categories) }) - .where(eq(schema.articles.id, articleId)); -} - -export async function updateKind( - articleId: number, - kind: string, -): Promise { - await db() - .update(schema.articles) - .set({ kind }) - .where(eq(schema.articles.id, articleId)); -} - -export async function updateContent( - articleId: number, - content: string, -): Promise { - await db() - .update(schema.articles) - .set({ content }) - .where(eq(schema.articles.id, articleId)); -} - -export async function updateTitle( - articleId: number, - title: string, -): Promise { - await db() - .update(schema.articles) - .set({ title }) - .where(eq(schema.articles.id, articleId)); -} - -export async function updateSummary( - articleId: number, - summary: string, -): Promise { - await db() - .update(schema.articles) - .set({ summary }) - .where(eq(schema.articles.id, articleId)); -} - -export interface ArticleFilterParams { - q?: string; - category?: string; - kind?: string; - since?: string; - sort?: string; - includeReleased?: boolean; - minScore?: number; - limit?: number; -} - -const SORT_COLUMNS = new Set(["score", "published_at", "title", "source"]); - -export async function getFilteredArticles( - params: ArticleFilterParams, -): Promise<(Omit & { url: string })[]> { - const a = schema.articles; - const conditions = [isNotNull(a.score)]; - - if (!params.includeReleased) conditions.push(isNull(a.release_date)); - if (params.since) conditions.push(gte(a.published_at, params.since)); - if (params.minScore !== undefined) - conditions.push(gte(a.score, params.minScore)); - if (params.kind) conditions.push(eq(a.kind, params.kind)); - if (params.q) { - const pattern = `%${params.q}%`; - conditions.push( - or(like(a.title, pattern), like(a.summary, pattern)) as ReturnType< - typeof eq - >, - ); - } - if (params.category) { - conditions.push( - sql`EXISTS (SELECT 1 FROM json_each(${a.categories}) WHERE json_each.value = ${params.category})` as ReturnType< - typeof eq - >, - ); - } - - let orderExpr = desc(a.score); - if (params.sort) { - const parts = params.sort.split("-"); - const dir = parts.pop(); - const col = parts.join("-"); - if (SORT_COLUMNS.has(col) && (dir === "asc" || dir === "desc")) { - const colRef = a[col as keyof typeof a] as Parameters[0]; - orderExpr = dir === "asc" ? asc(colRef) : desc(colRef); - } - } - - const q = db() - .select({ - id: a.id, - title: a.title, - source: a.source, - source_type: a.source_type, - published_at: a.published_at, - score: a.score, - summary: a.summary, - categories: a.categories, - release_date: a.release_date, - created_at: a.created_at, - kind: a.kind, - human_edits: a.human_edits, - url: a.url, - }) - .from(a) - .where(and(...conditions)) - .orderBy(orderExpr); - - const rows = params.limit ? await q.limit(params.limit) : await q; - return rows as unknown as (Omit & { url: string })[]; -} - -export async function getUnreleasedArticles(): Promise< - (DbArticle & { url: string })[] -> { - const rows = await db() - .select() - .from(schema.articles) - .where( - and( - isNull(schema.articles.release_date), - isNotNull(schema.articles.score), - ), - ) - .orderBy(desc(schema.articles.score), desc(schema.articles.created_at)); - return rows as unknown as (DbArticle & { url: string })[]; -} - -export async function getAllArticles( - includeReleased: boolean, -): Promise<(DbArticle & { url: string })[]> { - if (includeReleased) { - const rows = await db() - .select() - .from(schema.articles) - .where(isNotNull(schema.articles.score)) - .orderBy(desc(schema.articles.created_at)); - return rows as unknown as (DbArticle & { url: string })[]; - } - return getUnreleasedArticles(); -} - -export async function getArticlesByIds( - ids: number[], -): Promise<(DbArticle & { url: string })[]> { - if (ids.length === 0) return []; - const rows = await db() - .select() - .from(schema.articles) - .where(inArray(schema.articles.id, ids)) - .orderBy(desc(schema.articles.created_at)); - return rows as unknown as (DbArticle & { url: string })[]; -} - -export async function getArticleById( - id: number, -): Promise<{ id: number; title: string; summary: string | null } | null> { - const rows = await db() - .select({ - id: schema.articles.id, - title: schema.articles.title, - summary: schema.articles.summary, - }) - .from(schema.articles) - .where(eq(schema.articles.id, id)) - .limit(1); - return rows[0] ?? null; -} - -export async function releaseArticles( - ids: number[], - date: string, -): Promise { - await db() - .update(schema.articles) - .set({ release_date: date }) - .where(inArray(schema.articles.id, ids)); -} - -export interface ArticleUpdate { - title?: string; - score?: number | null; - summary?: string | null; - categories?: string[]; - kind?: string | null; - source?: string; - published_at?: string | null; - addHumanEdits?: string[]; -} - -export async function updateArticle( - articleId: number, - fields: ArticleUpdate, -): Promise { - const set: Partial = {}; - - if (fields.title !== undefined) set.title = fields.title; - if (fields.score !== undefined) set.score = fields.score; - if (fields.summary !== undefined) set.summary = fields.summary; - if (fields.categories !== undefined) - set.categories = JSON.stringify(fields.categories); - if (fields.kind !== undefined) set.kind = fields.kind; - if (fields.source !== undefined) set.source = fields.source; - if (fields.published_at !== undefined) set.published_at = fields.published_at; - - if (fields.addHumanEdits?.length) { - const rows = await db() - .select({ human_edits: schema.articles.human_edits }) - .from(schema.articles) - .where(eq(schema.articles.id, articleId)) - .limit(1); - const current = rows[0]?.human_edits ?? "[]"; - set.human_edits = JSON.stringify([ - ...new Set([ - ...(JSON.parse(current) as string[]), - ...fields.addHumanEdits, - ]), - ]); - } - - if (Object.keys(set).length === 0) return; - await db() - .update(schema.articles) - .set(set) - .where(eq(schema.articles.id, articleId)); -} - -export async function deleteArticle(articleId: number): Promise { - await db() - .delete(schema.articleUrls) - .where(eq(schema.articleUrls.article_id, articleId)); - await db().delete(schema.articles).where(eq(schema.articles.id, articleId)); -} - -export async function updateEmbedding( - articleId: number, - vecString: string, -): Promise { - // vector32() is a Turso-specific function — kept as raw SQL - await db().run( - sql`UPDATE articles SET embedding = vector32(${vecString}) WHERE id = ${articleId}`, - ); -} - -export async function searchArticlesByEmbedding( - queryVecString: string, - limit = 20, -): Promise<(DbArticle & { url: string })[]> { - // vector_top_k is a Turso-specific table-valued function — kept as raw SQL - const rows = await db().all( - sql`SELECT a.* - FROM articles a - INNER JOIN (SELECT rowid FROM vector_top_k('idx_articles_embedding', ${queryVecString}, ${limit})) v ON a.id = v.rowid - WHERE a.score IS NOT NULL`, - ); - return rows; -} - -export async function getArticlesWithoutEmbeddings(): Promise< - { id: number; title: string; summary: string | null }[] -> { - return db() - .select({ - id: schema.articles.id, - title: schema.articles.title, - summary: schema.articles.summary, - }) - .from(schema.articles) - .where( - and( - isNotNull(schema.articles.score), - isNotNull(schema.articles.summary), - isNull(schema.articles.embedding), - ), - ); -} - -export async function getArticleStats(): Promise<{ - total: number; - lastUpdated: string | null; -}> { - const rows = await db().all<{ total: number; last: string | null }>( - sql`SELECT COUNT(*) as total, MAX(created_at) as last FROM articles WHERE score IS NOT NULL`, - ); - return { total: rows[0]?.total ?? 0, lastUpdated: rows[0]?.last ?? null }; -} diff --git a/temp/source/shared/db/client.ts b/temp/source/shared/db/client.ts deleted file mode 100644 index 15890d1358..0000000000 --- a/temp/source/shared/db/client.ts +++ /dev/null @@ -1,44 +0,0 @@ -import { createClient } from "@libsql/client/web"; -import { drizzle } from "drizzle-orm/libsql"; -import * as schema from "../schema"; - -export type DrizzleClient = ReturnType; - -let _db: DrizzleClient | null = null; - -export function initDb(env: { - TURSO_DATABASE_URL: string; - TURSO_AUTH_TOKEN?: string; -}) { - if (!_db) { - _db = drizzle( - createClient({ - url: env.TURSO_DATABASE_URL, - authToken: env.TURSO_AUTH_TOKEN, - }), - { schema }, - ); - } -} - -export function db(): DrizzleClient { - if (!_db) { - const env = - typeof process !== "undefined" - ? (process as { env?: Record }).env - : {}; - _db = drizzle( - createClient({ - url: env?.TURSO_DATABASE_URL ?? "", - authToken: env?.TURSO_AUTH_TOKEN, - }), - { schema }, - ); - } - return _db; -} - -export async function ping(): Promise { - const { sql } = await import("drizzle-orm"); - await db().run(sql`SELECT 1`); -} diff --git a/temp/source/shared/db/meta.ts b/temp/source/shared/db/meta.ts deleted file mode 100644 index 1a39f6cd8d..0000000000 --- a/temp/source/shared/db/meta.ts +++ /dev/null @@ -1,36 +0,0 @@ -import { eq, like, sql } from "drizzle-orm"; -import * as schema from "../schema"; -import { db } from "./client"; - -export async function setMeta(key: string, value: string): Promise { - await db() - .insert(schema.meta) - .values({ key, value }) - .onConflictDoUpdate({ - target: schema.meta.key, - set: { value, updated_at: sql`(datetime('now'))` }, - }); -} - -export async function getMeta(key: string): Promise { - const rows = await db() - .select({ value: schema.meta.value }) - .from(schema.meta) - .where(eq(schema.meta.key, key)) - .limit(1); - return rows[0]?.value ?? null; -} - -export async function getMetaByPrefix( - prefix: string, -): Promise> { - const rows = await db() - .select({ key: schema.meta.key, value: schema.meta.value }) - .from(schema.meta) - .where(like(schema.meta.key, `${prefix}%`)); - const result: Record = {}; - for (const row of rows) { - result[row.key.slice(prefix.length)] = row.value; - } - return result; -} diff --git a/temp/source/shared/db/urls.ts b/temp/source/shared/db/urls.ts deleted file mode 100644 index 1c16ed68e5..0000000000 --- a/temp/source/shared/db/urls.ts +++ /dev/null @@ -1,71 +0,0 @@ -import { eq, inArray } from "drizzle-orm"; -import * as schema from "../schema"; -import { db } from "./client"; - -export async function urlExists(url: string): Promise { - const rows = await db() - .select({ url: schema.articleUrls.url }) - .from(schema.articleUrls) - .where(eq(schema.articleUrls.url, url)) - .limit(1); - return rows.length > 0; -} - -export async function urlsExist(urls: string[]): Promise> { - if (urls.length === 0) return new Set(); - const rows = await db() - .select({ url: schema.articleUrls.url }) - .from(schema.articleUrls) - .where(inArray(schema.articleUrls.url, urls)); - return new Set(rows.map((r) => r.url)); -} - -export async function scoredUrlsExist(urls: string[]): Promise> { - if (urls.length === 0) return new Set(); - const rows = await db() - .select({ url: schema.scoredUrls.url }) - .from(schema.scoredUrls) - .where(inArray(schema.scoredUrls.url, urls)); - return new Set(rows.map((r) => r.url)); -} - -export async function markUrlsScored(urls: string[]): Promise { - if (urls.length === 0) return; - await db() - .insert(schema.scoredUrls) - .values(urls.map((url) => ({ url }))) - .onConflictDoNothing(); -} - -export async function getArticleIdByUrl(url: string): Promise { - const rows = await db() - .select({ article_id: schema.articleUrls.article_id }) - .from(schema.articleUrls) - .where(eq(schema.articleUrls.url, url)) - .limit(1); - return rows[0]?.article_id ?? null; -} - -export async function addUrlToArticle( - url: string, - articleId: number, -): Promise { - await db() - .insert(schema.articleUrls) - .values({ url, article_id: articleId }) - .onConflictDoNothing(); -} - -export async function updateArticleUrl( - articleId: number, - newUrl: string, -): Promise { - await db() - .update(schema.articleUrls) - .set({ url: newUrl }) - .where(eq(schema.articleUrls.article_id, articleId)); - await db() - .update(schema.articles) - .set({ url: newUrl }) - .where(eq(schema.articles.id, articleId)); -} diff --git a/temp/source/shared/db/users.ts b/temp/source/shared/db/users.ts deleted file mode 100644 index 6eb9fae804..0000000000 --- a/temp/source/shared/db/users.ts +++ /dev/null @@ -1,182 +0,0 @@ -import { and, eq, gte, sql } from "drizzle-orm"; -import * as schema from "../schema"; -import { db } from "./client"; - -export async function getUserByEmail(email: string): Promise<{ - id: number; - key_hash: string | null; - credits_remaining: number; - github_username: string | null; -} | null> { - const rows = await db() - .select({ - id: schema.users.id, - key_hash: schema.users.key_hash, - credits_remaining: schema.users.credits_remaining, - github_username: schema.users.github_username, - }) - .from(schema.users) - .where(eq(schema.users.email, email)) - .limit(1); - if (rows.length === 0) return null; - const r = rows[0]; - return { - id: r.id, - key_hash: r.key_hash, - credits_remaining: r.credits_remaining ?? 0, - github_username: r.github_username ?? null, - }; -} - -export async function ensureUserByEmail(email: string): Promise<{ - id: number; - key_hash: string | null; - credits_remaining: number; - github_username: string | null; -}> { - await db().insert(schema.users).values({ email }).onConflictDoNothing(); - const u = await getUserByEmail(email); - if (!u) throw new Error(`Failed to upsert user ${email}`); - return u; -} - -export async function upsertNewsletterPrefs(params: { - email: string; - categories: string[]; - custom: string; - utm_source?: string | null; -}): Promise { - await db() - .insert(schema.users) - .values({ - email: params.email, - newsletter_categories: JSON.stringify(params.categories), - newsletter_custom: params.custom, - newsletter_utm_source: params.utm_source ?? null, - newsletter_updated_at: sql`(datetime('now'))`, - }) - .onConflictDoUpdate({ - target: schema.users.email, - set: { - newsletter_categories: JSON.stringify(params.categories), - newsletter_custom: params.custom, - newsletter_utm_source: params.utm_source ?? null, - newsletter_updated_at: sql`(datetime('now'))`, - }, - }); -} - -export async function creditUser(params: { - email: string; - name?: string | null; - credits: number; -}): Promise { - await db() - .insert(schema.users) - .values({ - email: params.email, - name: params.name ?? null, - credits_remaining: params.credits, - }) - .onConflictDoUpdate({ - target: schema.users.email, - set: { - credits_remaining: sql`${schema.users.credits_remaining} + ${params.credits}`, - name: sql`COALESCE(${schema.users.name}, ${params.name ?? null})`, - }, - }); -} - -export async function setUserKeyHash( - userId: number, - keyHash: string, -): Promise { - await db() - .update(schema.users) - .set({ key_hash: keyHash }) - .where(eq(schema.users.id, userId)); -} - -export async function verifyKey( - keyHash: string, -): Promise<{ userId: number; balance: number } | null> { - const rows = await db() - .select({ - id: schema.users.id, - credits_remaining: schema.users.credits_remaining, - }) - .from(schema.users) - .where(eq(schema.users.key_hash, keyHash)) - .limit(1); - if (rows.length === 0) return null; - return { userId: rows[0].id, balance: rows[0].credits_remaining ?? 0 }; -} - -export async function chargeCredits( - userId: number, - cost: number, -): Promise { - const result = await db() - .update(schema.users) - .set({ - credits_remaining: sql`${schema.users.credits_remaining} - ${cost}`, - last_used_at: sql`(datetime('now'))`, - }) - .where( - and( - eq(schema.users.id, userId), - gte(schema.users.credits_remaining, cost), - ), - ); - return (result.rowsAffected ?? 0) > 0; -} - -export async function setGithubUsername( - userId: number, - username: string, -): Promise { - await db() - .update(schema.users) - .set({ github_username: username }) - .where(eq(schema.users.id, userId)); -} - -export async function setReferredBy( - userId: number, - referrerUsername: string, -): Promise { - await db().run( - sql`UPDATE users SET referred_by = ${referrerUsername} WHERE id = ${userId} AND referred_by IS NULL`, - ); -} - -export async function getUserByGithubUsername(username: string): Promise<{ - id: number; - email: string; -} | null> { - const rows = await db() - .select({ id: schema.users.id, email: schema.users.email }) - .from(schema.users) - .where(eq(schema.users.github_username, username)) - .limit(1); - return rows[0] ?? null; -} - -export async function logApiCall( - userId: number, - endpoint: string, - params: Record, -): Promise { - await db() - .insert(schema.apiCalls) - .values({ user_id: userId, endpoint, params: JSON.stringify(params) }); -} - -export async function getGithubAccessToken( - baUserId: string, -): Promise { - const rows = await db().all<{ access_token: string | null }>( - sql`SELECT access_token FROM account WHERE user_id = ${baUserId} AND provider_id = 'github' LIMIT 1`, - ); - return rows[0]?.access_token ?? null; -} diff --git a/temp/source/shared/embeddings.ts b/temp/source/shared/embeddings.ts deleted file mode 100644 index e221916d50..0000000000 --- a/temp/source/shared/embeddings.ts +++ /dev/null @@ -1,35 +0,0 @@ -const EMBED_MODEL = "nvidia/nv-embedqa-e5-v5"; - -export async function getEmbedding( - text: string, - inputType: "query" | "passage" = "query", - apiKey?: string, -): Promise { - const key = - apiKey ?? - (typeof process !== "undefined" - ? process.env?.NVIDIA_NIM_API_KEY - : undefined); - const resp = await fetch("https://integrate.api.nvidia.com/v1/embeddings", { - method: "POST", - headers: { - Authorization: `Bearer ${key}`, - "Content-Type": "application/json", - }, - body: JSON.stringify({ - model: EMBED_MODEL, - input: [text], - input_type: inputType, - }), - }); - if (!resp.ok) { - const body = await resp.text(); - throw new Error(`Embedding API ${resp.status}: ${body}`); - } - const data = (await resp.json()) as { data: { embedding: number[] }[] }; - return data.data[0].embedding; -} - -export function embeddingToVecString(embedding: number[]): string { - return `[${embedding.join(",")}]`; -} diff --git a/temp/source/shared/pricing.ts b/temp/source/shared/pricing.ts deleted file mode 100644 index 3c913dea35..0000000000 --- a/temp/source/shared/pricing.ts +++ /dev/null @@ -1,11 +0,0 @@ -export const ENDPOINT_COSTS = { - "/v1/articles": 1, - "/v1/search": 5, -} as const; - -export type PricedEndpoint = keyof typeof ENDPOINT_COSTS; - -export const CREDITS_PER_PURCHASE = 500; - -export const PRICE_CHF = 5; -export const CURRENCY = "CHF"; diff --git a/temp/source/shared/schema.ts b/temp/source/shared/schema.ts deleted file mode 100644 index ddd5c24f67..0000000000 --- a/temp/source/shared/schema.ts +++ /dev/null @@ -1,84 +0,0 @@ -import { sql } from "drizzle-orm"; -import { - blob, - index, - integer, - sqliteTable, - text, -} from "drizzle-orm/sqlite-core"; - -export const articles = sqliteTable( - "articles", - { - id: integer("id").primaryKey({ autoIncrement: true }), - title: text("title").notNull(), - content: text("content").default(""), - source: text("source").notNull(), - source_type: text("source_type").notNull(), - published_at: text("published_at"), - score: integer("score"), - summary: text("summary"), - categories: text("categories").default("[]"), - kind: text("kind"), - human_edits: text("human_edits").default("[]"), - // embedding is F32_BLOB(1024) — Turso-specific; kept as raw blob, managed via raw SQL - embedding: blob("embedding"), - url: text("url"), - release_date: text("release_date"), - created_at: text("created_at").default(sql`(datetime('now'))`), - }, - (t) => [ - index("idx_articles_score").on(t.score), - index("idx_articles_published_at").on(t.published_at), - ], -); - -export const articleUrls = sqliteTable("article_urls", { - url: text("url").primaryKey(), - article_id: integer("article_id") - .notNull() - .references(() => articles.id), -}); - -export const meta = sqliteTable("meta", { - key: text("key").primaryKey(), - value: text("value").notNull(), - updated_at: text("updated_at").default(sql`(datetime('now'))`), -}); - -export const scoredUrls = sqliteTable("scored_urls", { - url: text("url").primaryKey(), - scored_at: text("scored_at").default(sql`(datetime('now'))`), -}); - -export const users = sqliteTable("users", { - id: integer("id").primaryKey({ autoIncrement: true }), - email: text("email").notNull().unique(), - name: text("name"), - created_at: text("created_at").default(sql`(datetime('now'))`), - newsletter_categories: text("newsletter_categories"), - newsletter_custom: text("newsletter_custom"), - newsletter_utm_source: text("newsletter_utm_source"), - newsletter_updated_at: text("newsletter_updated_at"), - // key_plain dropped — API keys are show-once; only the hash is stored - key_hash: text("key_hash").unique(), - credits_remaining: integer("credits_remaining").default(0), - last_used_at: text("last_used_at"), - github_username: text("github_username"), - referred_by: text("referred_by"), -}); - -export const apiCalls = sqliteTable( - "api_calls", - { - id: integer("id").primaryKey({ autoIncrement: true }), - user_id: integer("user_id").notNull(), - endpoint: text("endpoint").notNull(), - params: text("params").notNull().default("{}"), - created_at: text("created_at").default(sql`(datetime('now'))`), - }, - (t) => [ - index("idx_api_calls_created_at").on(t.created_at), - index("idx_api_calls_user_id").on(t.user_id), - ], -); diff --git a/temp/source/shared/types.ts b/temp/source/shared/types.ts deleted file mode 100644 index 64c97ededa..0000000000 --- a/temp/source/shared/types.ts +++ /dev/null @@ -1,57 +0,0 @@ -export const ARTICLE_CATEGORIES = ["models", "dev", "research"] as const; - -export type ArticleCategory = (typeof ARTICLE_CATEGORIES)[number]; - -export const ARTICLE_KINDS = [ - "repo", - "paper", - "model", - "blog", - "product", - "announcement", -] as const; - -export type ArticleKind = (typeof ARTICLE_KINDS)[number]; - -export interface FetchedArticle { - title: string; - url: string; - content: string; - publishedDate: string; - source: string; - sourceType: "rss" | "hackerNews" | "newsletter" | "aiNews"; -} - -export interface DbArticle { - id: number; - /** Sanitized at insert; may be rewritten by ImproveTitles. */ - title: string; - /** Full article text extracted at ingest time. Capped before LLM calls. */ - content: string; - /** Human-readable source name, e.g. "Hacker News", "AI News", "Ben's Bites". */ - source: string; - /** Source channel: "rss" | "hackerNews" | "newsletter" | "aiNews". */ - source_type: string; - /** Original publication date from the source (RSS pubDate, newsletter date, etc.). Shown in UI. */ - published_at: string | null; - /** 1–10 relevance score from ScoreArticles. NULL = not yet scored or deleted (score=NULL hides from UI). */ - score: number | null; - /** 2–3 line summary from SummarizeAndCategorize. NULL = not yet summarized. */ - summary: string | null; - /** JSON array of ArticleCategory strings, e.g. '["models","dev"]'. */ - categories: string; - /** Content format: "repo" | "paper" | "model" | "blog" | "product" | "announcement". */ - kind: string | null; - /** Date the article was included in a released newsletter edition. NULL = not yet released. Gates UI visibility. */ - release_date: string | null; - /** When the article row was inserted into the DB. Used for pipeline windows (e.g. review-week -7 days). */ - created_at: string; - /** JSON array of field names manually edited by a human, e.g. '["score","categories"]'. Pipelines should not overwrite these. */ - human_edits?: string; -} - -export interface Source { - name: string; - rssUrl: string; - weight: number; -} From 16237f8e4d08ae11abde68760013ec0ef91b5515 Mon Sep 17 00:00:00 2001 From: Dimitar Slaev Date: Sun, 28 Jun 2026 23:17:01 +0200 Subject: [PATCH 16/42] feat(frontend): make articles the public home page Move ArticlesList to the root route and remove the layout auth guard so visitors land on articles without logging in. Co-Authored-By: Claude Sonnet 4.6 --- CHANGES.md | 3 ++ .../Articles/ArticlesList.tsx} | 22 ++++--------- frontend/src/routeTree.gen.ts | 27 ++-------------- frontend/src/routes/_layout.tsx | 18 +++++------ frontend/src/routes/_layout/index.tsx | 32 +++---------------- 5 files changed, 27 insertions(+), 75 deletions(-) rename frontend/src/{routes/articles.tsx => components/Articles/ArticlesList.tsx} (85%) diff --git a/CHANGES.md b/CHANGES.md index 9dea7c0be1..7958dbff74 100644 --- a/CHANGES.md +++ b/CHANGES.md @@ -6,6 +6,9 @@ Changes made on top of `fastapi/full-stack-fastapi-template`. Upstream files are ## 2026-06-28 +- `frontend/src/routes/_layout.tsx` — `beforeLoad` auth guard commented out so unauthenticated users reach the layout. Low conflict risk (small, isolated block). +- `frontend/src/routes/_layout/index.tsx` — Dashboard component replaced with `ArticlesList`; `useAuth` import removed. Medium conflict risk if upstream extends Dashboard. + - `.env` — Deleted and added to `.gitignore`. In upstream it's tracked and used as an example. - `compose.yml` — Frontend Traefik rule changed from `Host(\`dashboard.${DOMAIN}\`)` to `Host(\`${DOMAIN}\`)` so the app is served at the root domain. Added `PROJECT_NAME` to prestart and backend service environments. - `deploy-production.yml` — Split into build job (GitHub-hosted runner, pushes to ghcr.io) and deploy job (self-hosted runner, pulls and restarts). Added buildx + GHA layer caching. Added all missing compose env vars. diff --git a/frontend/src/routes/articles.tsx b/frontend/src/components/Articles/ArticlesList.tsx similarity index 85% rename from frontend/src/routes/articles.tsx rename to frontend/src/components/Articles/ArticlesList.tsx index f385468959..53c824c309 100644 --- a/frontend/src/routes/articles.tsx +++ b/frontend/src/components/Articles/ArticlesList.tsx @@ -1,26 +1,18 @@ -import { useQuery } from "@tanstack/react-query"; -import { createFileRoute } from "@tanstack/react-router"; -import { ArticlesService, type ArticlePublic } from "@/client"; +import { useQuery } from "@tanstack/react-query" +import { ArticlesService, type ArticlePublic } from "@/client" -export const Route = createFileRoute("/articles")({ - component: ArticlesPage, - head: () => ({ - meta: [{ title: "Articles - Agentique" }], - }), -}); - -function ArticlesPage() { +export function ArticlesList() { const { data, isLoading, isError } = useQuery({ queryKey: ["articles"], queryFn: () => ArticlesService.readArticles({ limit: 20 }), - }); + }) if (isLoading) { return (
    Loading…
    - ); + ) } if (isError || !data) { @@ -28,7 +20,7 @@ function ArticlesPage() {
    Failed to load articles.
    - ); + ) } return ( @@ -83,5 +75,5 @@ function ArticlesPage() { ))} - ); + ) } diff --git a/frontend/src/routeTree.gen.ts b/frontend/src/routeTree.gen.ts index 7ec39d20d3..08d665fef8 100644 --- a/frontend/src/routeTree.gen.ts +++ b/frontend/src/routeTree.gen.ts @@ -9,7 +9,6 @@ // Additionally, you should also exclude this file from your linter and/or formatter to prevent it from being checked or modified. import { Route as rootRouteImport } from './routes/__root' -import { Route as ArticlesRouteImport } from './routes/articles' import { Route as SignupRouteImport } from './routes/signup' import { Route as ResetPasswordRouteImport } from './routes/reset-password' import { Route as RecoverPasswordRouteImport } from './routes/recover-password' @@ -20,11 +19,6 @@ import { Route as LayoutSettingsRouteImport } from './routes/_layout/settings' import { Route as LayoutItemsRouteImport } from './routes/_layout/items' import { Route as LayoutAdminRouteImport } from './routes/_layout/admin' -const ArticlesRoute = ArticlesRouteImport.update({ - id: '/articles', - path: '/articles', - getParentRoute: () => rootRouteImport, -} as any) const SignupRoute = SignupRouteImport.update({ id: '/signup', path: '/signup', @@ -71,7 +65,7 @@ const LayoutAdminRoute = LayoutAdminRouteImport.update({ } as any) export interface FileRoutesByFullPath { - '/articles': typeof ArticlesRoute + '/': typeof LayoutIndexRoute '/login': typeof LoginRoute '/recover-password': typeof RecoverPasswordRoute '/reset-password': typeof ResetPasswordRoute @@ -79,10 +73,8 @@ export interface FileRoutesByFullPath { '/admin': typeof LayoutAdminRoute '/items': typeof LayoutItemsRoute '/settings': typeof LayoutSettingsRoute - '/': typeof LayoutIndexRoute } export interface FileRoutesByTo { - '/articles': typeof ArticlesRoute '/login': typeof LoginRoute '/recover-password': typeof RecoverPasswordRoute '/reset-password': typeof ResetPasswordRoute @@ -94,7 +86,6 @@ export interface FileRoutesByTo { } export interface FileRoutesById { __root__: typeof rootRouteImport - '/articles': typeof ArticlesRoute '/_layout': typeof LayoutRouteWithChildren '/login': typeof LoginRoute '/recover-password': typeof RecoverPasswordRoute @@ -108,7 +99,7 @@ export interface FileRoutesById { export interface FileRouteTypes { fileRoutesByFullPath: FileRoutesByFullPath fullPaths: - | '/articles' + | '/' | '/login' | '/recover-password' | '/reset-password' @@ -116,10 +107,8 @@ export interface FileRouteTypes { | '/admin' | '/items' | '/settings' - | '/' fileRoutesByTo: FileRoutesByTo to: - | '/articles' | '/login' | '/recover-password' | '/reset-password' @@ -130,7 +119,6 @@ export interface FileRouteTypes { | '/' id: | '__root__' - | '/articles' | '/_layout' | '/login' | '/recover-password' @@ -143,7 +131,6 @@ export interface FileRouteTypes { fileRoutesById: FileRoutesById } export interface RootRouteChildren { - ArticlesRoute: typeof ArticlesRoute LayoutRoute: typeof LayoutRouteWithChildren LoginRoute: typeof LoginRoute RecoverPasswordRoute: typeof RecoverPasswordRoute @@ -184,7 +171,7 @@ declare module '@tanstack/react-router' { '/_layout': { id: '/_layout' path: '' - fullPath: '' + fullPath: '/' preLoaderRoute: typeof LayoutRouteImport parentRoute: typeof rootRouteImport } @@ -216,13 +203,6 @@ declare module '@tanstack/react-router' { preLoaderRoute: typeof LayoutAdminRouteImport parentRoute: typeof LayoutRoute } - '/articles': { - id: '/articles' - path: '/articles' - fullPath: '/articles' - preLoaderRoute: typeof ArticlesRouteImport - parentRoute: typeof rootRouteImport - } } } @@ -244,7 +224,6 @@ const LayoutRouteWithChildren = LayoutRoute._addFileChildren(LayoutRouteChildren) const rootRouteChildren: RootRouteChildren = { - ArticlesRoute: ArticlesRoute, LayoutRoute: LayoutRouteWithChildren, LoginRoute: LoginRoute, RecoverPasswordRoute: RecoverPasswordRoute, diff --git a/frontend/src/routes/_layout.tsx b/frontend/src/routes/_layout.tsx index 169730546e..b6a455117c 100644 --- a/frontend/src/routes/_layout.tsx +++ b/frontend/src/routes/_layout.tsx @@ -1,4 +1,5 @@ -import { createFileRoute, Outlet, redirect } from "@tanstack/react-router" +import { createFileRoute, Outlet } from "@tanstack/react-router" +// import { isLoggedIn } from "@/hooks/useAuth" import { Footer } from "@/components/Common/Footer" import AppSidebar from "@/components/Sidebar/AppSidebar" @@ -7,17 +8,16 @@ import { SidebarProvider, SidebarTrigger, } from "@/components/ui/sidebar" -import { isLoggedIn } from "@/hooks/useAuth" export const Route = createFileRoute("/_layout")({ component: Layout, - beforeLoad: async () => { - if (!isLoggedIn()) { - throw redirect({ - to: "/login", - }) - } - }, + // beforeLoad: async () => { + // if (!isLoggedIn()) { + // throw redirect({ + // to: "/login", + // }) + // } + // }, }) function Layout() { diff --git a/frontend/src/routes/_layout/index.tsx b/frontend/src/routes/_layout/index.tsx index 3e640cbbb8..d4adf832ef 100644 --- a/frontend/src/routes/_layout/index.tsx +++ b/frontend/src/routes/_layout/index.tsx @@ -1,31 +1,9 @@ -import { createFileRoute } from "@tanstack/react-router" - -import useAuth from "@/hooks/useAuth" +import { createFileRoute } from "@tanstack/react-router"; +import { ArticlesList } from "@/components/Articles/ArticlesList"; export const Route = createFileRoute("/_layout/")({ - component: Dashboard, + component: ArticlesList, head: () => ({ - meta: [ - { - title: "Dashboard - FastAPI Template", - }, - ], + meta: [{ title: "Articles - Agentique" }], }), -}) - -function Dashboard() { - const { user: currentUser } = useAuth() - - return ( -
    -
    -

    - Hi, {currentUser?.full_name || currentUser?.email} 👋 -

    -

    - Welcome back, nice to see you again!!! -

    -
    -
    - ) -} +}); From 960d250aafa76e8e3a5d6723f28675648ddfb8e4 Mon Sep 17 00:00:00 2001 From: Dimitar Slaev Date: Mon, 29 Jun 2026 23:29:30 +0200 Subject: [PATCH 17/42] feat: migrate home and layout --- CHANGES.md | 6 + backend/app/api/routes/articles.py | 24 ++- backend/app/core/config.py | 4 +- frontend/src/client/sdk.gen.ts | 3 +- frontend/src/client/types.gen.ts | 1 + .../src/components/Articles/ArticlesList.tsx | 184 ++++++++++++------ frontend/src/components/Common/AuthLayout.tsx | 2 +- frontend/src/components/Common/Footer.tsx | 80 ++++---- frontend/src/components/Common/Logo.tsx | 64 ++---- .../src/components/Sidebar/AppSidebar.tsx | 27 +-- frontend/src/components/Sidebar/Filters.tsx | 149 ++++++++++++++ frontend/src/components/Sidebar/Main.tsx | 19 +- frontend/src/context/filters.tsx | 47 +++++ frontend/src/routes/_layout.tsx | 33 ++-- 14 files changed, 463 insertions(+), 180 deletions(-) create mode 100644 frontend/src/components/Sidebar/Filters.tsx create mode 100644 frontend/src/context/filters.tsx diff --git a/CHANGES.md b/CHANGES.md index 7958dbff74..73fa4ba223 100644 --- a/CHANGES.md +++ b/CHANGES.md @@ -4,6 +4,12 @@ Changes made on top of `fastapi/full-stack-fastapi-template`. Upstream files are --- +## 2026-06-29 + +- `backend/app/core/config.py` — `ENVIRONMENT` Literal changed from `"local"` to `"development"` (value and default); matching `== "local"` guard updated to `== "development"`. Low conflict risk (one-line change; upstream uses `"local"` as the dev environment name). + +--- + ## 2026-06-28 - `frontend/src/routes/_layout.tsx` — `beforeLoad` auth guard commented out so unauthenticated users reach the layout. Low conflict risk (small, isolated block). diff --git a/backend/app/api/routes/articles.py b/backend/app/api/routes/articles.py index a7f27a00f4..6362ca7fc0 100644 --- a/backend/app/api/routes/articles.py +++ b/backend/app/api/routes/articles.py @@ -5,6 +5,7 @@ from model2vec import StaticModel from pgvector.sqlalchemy import Vector from sqlalchemy import cast, func, or_ +from sqlalchemy.dialects.postgresql import JSONB from sqlmodel import col, select from app.api.deps import SessionDep @@ -42,6 +43,7 @@ def read_articles( min_score: int | None = Query(default=None, ge=1, le=10), category: str | None = None, kind: str | None = None, + sort: str = Query(default="score-desc"), ) -> Any: since_dt: datetime if since: @@ -64,19 +66,16 @@ def read_articles( statement = statement.where(Article.kind == kind) if category is not None: statement = statement.where( - func.json_array_length(Article.categories) > 0 # type: ignore[arg-type] - ).where( - func.exists( - select(func.json_array_elements_text(Article.categories).label("cat")) # type: ignore[arg-type] - .correlate(Article) - .where(func.json_array_elements_text(Article.categories) == category) # type: ignore[arg-type] - ) + cast(Article.categories, JSONB).contains([category]) # type: ignore[arg-type] ) count_statement = select(func.count()).select_from(statement.subquery()) count = session.exec(count_statement).one() - statement = statement.order_by(col(Article.score).desc()).limit(limit) + if sort == "published_at-desc": + statement = statement.order_by(col(Article.published_at).desc()).limit(limit) + else: + statement = statement.order_by(col(Article.score).desc()).limit(limit) articles = session.exec(statement).all() return ArticlesPublic( @@ -107,3 +106,12 @@ def search_articles( data=[ArticlePublic.model_validate(a) for a in articles], count=len(articles), ) + + +@router.get("/stats") +def article_stats(session: SessionDep) -> Any: + total = session.exec(select(func.count()).select_from(Article)).one() + last = session.exec( + select(func.max(Article.created_at)) # type: ignore[arg-type] + ).one() + return {"total": total, "lastUpdated": last.isoformat() if last else None} diff --git a/backend/app/core/config.py b/backend/app/core/config.py index 8710696271..9c19a49692 100644 --- a/backend/app/core/config.py +++ b/backend/app/core/config.py @@ -34,7 +34,7 @@ class Settings(BaseSettings): # 60 minutes * 24 hours * 8 days = 8 days ACCESS_TOKEN_EXPIRE_MINUTES: int = 60 * 24 * 8 FRONTEND_HOST: str = "http://localhost:5173" - ENVIRONMENT: Literal["local", "staging", "production"] = "local" + ENVIRONMENT: Literal["development", "staging", "production"] = "development" BACKEND_CORS_ORIGINS: Annotated[ list[AnyUrl] | str, BeforeValidator(parse_cors) @@ -99,7 +99,7 @@ def _check_default_secret(self, var_name: str, value: str | None) -> None: f'The value of {var_name} is "changethis", ' "for security, please change it, at least for deployments." ) - if self.ENVIRONMENT == "local": + if self.ENVIRONMENT == "development": warnings.warn(message, stacklevel=1) else: raise ValueError(message) diff --git a/frontend/src/client/sdk.gen.ts b/frontend/src/client/sdk.gen.ts index abb01e9579..fe7c8d716b 100644 --- a/frontend/src/client/sdk.gen.ts +++ b/frontend/src/client/sdk.gen.ts @@ -26,7 +26,8 @@ export class ArticlesService { since: data.since, min_score: data.minScore, category: data.category, - kind: data.kind + kind: data.kind, + sort: data.sort }, errors: { 422: 'Validation Error' diff --git a/frontend/src/client/types.gen.ts b/frontend/src/client/types.gen.ts index 99deeb5a0d..a7eb93ef7f 100644 --- a/frontend/src/client/types.gen.ts +++ b/frontend/src/client/types.gen.ts @@ -131,6 +131,7 @@ export type ArticlesReadArticlesData = { limit?: number; minScore?: (number | null); since?: (string | null); + sort?: (string | null); }; export type ArticlesReadArticlesResponse = (ArticlesPublic); diff --git a/frontend/src/components/Articles/ArticlesList.tsx b/frontend/src/components/Articles/ArticlesList.tsx index 53c824c309..c9c5e316dc 100644 --- a/frontend/src/components/Articles/ArticlesList.tsx +++ b/frontend/src/components/Articles/ArticlesList.tsx @@ -1,79 +1,151 @@ -import { useQuery } from "@tanstack/react-query" +import { keepPreviousData, useQuery } from "@tanstack/react-query" import { ArticlesService, type ArticlePublic } from "@/client" +import { cn } from "@/lib/utils" +import { useFilters } from "@/context/filters" + +const PUBLISHED_DAYS: Record = { "3d": 3, "1w": 7, "1m": 30 } + +function cutoffIso(days: number): string { + const d = new Date() + d.setDate(d.getDate() - days) + return d.toISOString() +} + +function ArticleSkeleton() { + return ( +
  • +
    +
    +
    +
    +
    +
    +
    +
    +
  • + ) +} export function ArticlesList() { - const { data, isLoading, isError } = useQuery({ - queryKey: ["articles"], - queryFn: () => ArticlesService.readArticles({ limit: 20 }), + const { filters } = useFilters() + const { search, dateRange, sort, category, kind } = filters + + const since = cutoffIso(PUBLISHED_DAYS[dateRange] ?? 7) + + const { data, isLoading, isFetching, isError } = useQuery({ + queryKey: ["articles", search, dateRange, sort, category, kind], + queryFn: () => { + if (search) { + return ArticlesService.searchArticles({ q: search, limit: 50 }) + } + return ArticlesService.readArticles({ + limit: 50, + since, + sort, + category: category || undefined, + kind: kind || undefined, + }) + }, + placeholderData: keepPreviousData, }) if (isLoading) { return ( -
    - Loading… -
    +
      + {Array.from({ length: 8 }).map((_, i) => ( + // biome-ignore lint/suspicious/noArrayIndexKey: static placeholder list + + ))} +
    ) } if (isError || !data) { return ( -
    +
    Failed to load articles.
    ) } + const articles = data.data + return ( -
    -

    Latest articles

    -
    + + ))} + + )} + + {!isFetching && articles.length > 0 && ( +

    + {articles.length} article{articles.length !== 1 ? "s" : ""} +

    + )}
    ) } diff --git a/frontend/src/components/Common/AuthLayout.tsx b/frontend/src/components/Common/AuthLayout.tsx index 4551610267..0b894146b9 100644 --- a/frontend/src/components/Common/AuthLayout.tsx +++ b/frontend/src/components/Common/AuthLayout.tsx @@ -10,7 +10,7 @@ export function AuthLayout({ children }: AuthLayoutProps) { return (
    - +
    diff --git a/frontend/src/components/Common/Footer.tsx b/frontend/src/components/Common/Footer.tsx index 279e1e7628..a8003f5f6c 100644 --- a/frontend/src/components/Common/Footer.tsx +++ b/frontend/src/components/Common/Footer.tsx @@ -1,42 +1,56 @@ -import { FaGithub, FaLinkedinIn } from "react-icons/fa" -import { FaXTwitter } from "react-icons/fa6" +import { useQuery } from "@tanstack/react-query" -const socialLinks = [ - { - icon: FaGithub, - href: "https://github.com/fastapi/fastapi", - label: "GitHub", - }, - { icon: FaXTwitter, href: "https://x.com/fastapi", label: "X" }, - { - icon: FaLinkedinIn, - href: "https://linkedin.com/company/fastapi", - label: "LinkedIn", - }, -] +async function fetchStats(): Promise<{ + total: number + lastUpdated: string | null +}> { + const res = await fetch(`${import.meta.env.VITE_API_URL}/articles/stats`) + if (!res.ok) return { total: 0, lastUpdated: null } + return res.json() +} + +function formatLastUpdated(iso: string | null): string { + if (!iso) return "" + try { + const d = new Date(`${iso}Z`) + const diffMs = Date.now() - d.getTime() + const diffH = Math.floor(diffMs / 3_600_000) + if (diffH < 1) return "Updated just now" + if (diffH < 24) return `Updated ${diffH}h ago` + const diffD = Math.floor(diffH / 24) + return `Updated ${diffD}d ago` + } catch { + return "" + } +} export function Footer() { - const currentYear = new Date().getFullYear() + const { data } = useQuery({ + queryKey: ["stats"], + queryFn: fetchStats, + staleTime: 5 * 60_000, + }) + + const total = data?.total ?? 0 + const updatedLabel = formatLastUpdated(data?.lastUpdated ?? null) return ( -