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+# examples/ag-ui Local-Runnable Example Implementation Plan (Part 2a)
+
+> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking.
+
+**Goal:** A standalone, locally-runnable `examples/ag-ui/` — a single-conversation chat app fronted by the AG-UI adapter (`provideAgent`) talking to a duplicated a2ui LangGraph graph served over `ag-ui-langgraph` via uvicorn — demonstrating LangGraph↔AG-UI transport + a2ui parity.
+
+**Architecture:** Fork the `examples/chat` Python graph verbatim (transport-agnostic). Build a *simplified* Angular app (single conversation, no thread sidebar — ag-ui has no thread-CRUD equivalent) that hosts `<chat>` via `provideAgent({ url: '/agent' })`. Add a `server.py` wrapping the graph with `add_langgraph_fastapi_endpoint(path='/agent')` + token-optional auth + `/ok` health. Dev: an Angular `proxy.conf` routes `/agent` → the uvicorn port.
+
+**Tech Stack:** Angular (standalone, zoneless), `@threadplane/ag-ui`, `@threadplane/chat`, Nx; Python 3.12, LangGraph, `ag-ui-langgraph`, FastAPI, uvicorn; vitest/pytest.
+
+**Spec:** `docs/superpowers/specs/2026-06-06-examples-ag-ui-standalone-design.md` (Part 2). **Scope refinement (this plan):** the shell is a simplified single-conversation chat, not a fork of `examples/chat`'s thread-managed `demo-shell` — `LangGraphThreadsAdapter` (thread CRUD) has no AG-UI equivalent. e2e/smoke = Part 2b; deploy = Part 3.
+
+---
+
+## File Structure
+
+**New — `examples/ag-ui/python/`** (graph copied verbatim from `examples/chat/python`; server + config new):
+- `src/graph.py`, `src/schemas/**`, `src/streaming/**` — verbatim copy (transport-agnostic a2ui graph).
+- `src/server.py` — FastAPI app: `add_langgraph_fastapi_endpoint(graph, path='/agent')` + token-optional middleware + `/ok`.
+- `pyproject.toml` — copy + add `ag-ui-langgraph`, `fastapi`, `uvicorn`.
+- `requirements.txt` — uv-exported (for Part 3 Docker; generated here).
+- `langgraph.json`, `.env.example`, `.python-version`, `project.json`, `README.md`.
+
+**New — `examples/ag-ui/angular/`** (simplified single-conversation app):
+- `src/app/app.config.ts` — `provideAgent({ url: '/agent' })` + `provideChat` + telemetry.
+- `src/app/app.ts` + `src/app/app.html` — single-conversation `<chat>` host.
+- `src/main.ts`, `src/index.html`, `src/styles.css`, `src/test-setup.ts`.
+- `src/environments/environment.ts` + `environment.development.ts` — `agentUrl: '/agent'`.
+- `proxy.conf.mjs` — dev: `/agent` → `http://localhost:8000`.
+- `project.json`, `tsconfig.json`, `tsconfig.app.json`, `vite.config.mts`, `public/favicon.ico`.
+
+**New — `examples/ag-ui/project.json`** — umbrella project (mirror `examples/chat/project.json`).
+
+---
+
+## Task 1: Python backend — copy graph + ag-ui server
+
+**Files:** create `examples/ag-ui/python/**`
+
+- [ ] **Step 1: Copy the chat Python tree (graph is transport-agnostic)**
+
+```bash
+mkdir -p examples/ag-ui/python
+cp -R examples/chat/python/src examples/ag-ui/python/src
+cp examples/chat/python/langgraph.json examples/chat/python/.python-version examples/ag-ui/python/
+cp examples/chat/python/.env.example examples/ag-ui/python/.env.example
+# Do NOT copy: .venv, .langgraph_api, .pytest_cache, uv.lock, tests/ (Part 2b), .env
+rm -rf examples/ag-ui/python/src/__pycache__ examples/ag-ui/python/src/**/__pycache__ 2>/dev/null || true
+```
+
+Verify the graph entry exists:
+```bash
+grep -n "^graph = " examples/ag-ui/python/src/graph.py
+```
+Expected: `graph = _builder.compile()` (the importable `graph` symbol).
+
+- [ ] **Step 2: Write `examples/ag-ui/python/src/server.py`**
+
+```python
+# SPDX-License-Identifier: MIT
+"""Standalone AG-UI server for the examples/ag-ui demo.
+
+Wraps the (transport-agnostic) chat graph with ag-ui-langgraph and serves it
+over an AG-UI FastAPI endpoint at /agent. Mirrors the cockpit ag-ui pattern.
+
+Auth is OPTIONAL for clone-and-run: the X-Internal-Token check is enforced
+only when AG_UI_INTERNAL_TOKEN is set (production), so `uvicorn src.server:app`
+works locally with no env beyond OPENAI_API_KEY.
+"""
+import os
+from fastapi import FastAPI, Request
+from fastapi.responses import JSONResponse
+from ag_ui_langgraph import add_langgraph_fastapi_endpoint, LangGraphAgent
+
+from .graph import graph
+
+AG_UI_INTERNAL_TOKEN = os.environ.get("AG_UI_INTERNAL_TOKEN")
+
+app = FastAPI(title="examples-ag-ui")
+
+
+@app.middleware("http")
+async def require_internal_token(request: Request, call_next):
+    # /ok is always open (health). Token is enforced only when configured.
+    if request.url.path == "/ok" or not AG_UI_INTERNAL_TOKEN:
+        return await call_next(request)
+    if request.headers.get("x-internal-token") != AG_UI_INTERNAL_TOKEN:
+        return JSONResponse(status_code=401, content={"detail": "unauthorized"})
+    return await call_next(request)
+
+
+@app.get("/ok")
+def ok() -> dict:
+    return {"ok": True}
+
+
+add_langgraph_fastapi_endpoint(app, LangGraphAgent(name="chat", graph=graph), path="/agent")
+```
+
+> Note the `JSONResponse(401)` (NOT `raise HTTPException`, which surfaces as 500 inside Starlette middleware — see repo memory).
+
+- [ ] **Step 3: Write `examples/ag-ui/python/pyproject.toml`**
+
+```toml
+[project]
+name = "examples-ag-ui-python"
+version = "0.1.0"
+requires-python = ">=3.12"
+dependencies = [
+    "langgraph>=0.3",
+    "langchain-openai>=0.3",
+    "ag-ui-langgraph>=0.0.37",
+    "fastapi>=0.115",
+    "uvicorn>=0.30",
+    "python-dotenv>=1.0",
+]
+
+[tool.uv]
+dev-dependencies = [
+    "pytest>=8.0",
+    "pytest-asyncio>=0.23",
+]
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[tool.hatch.build.targets.wheel]
+packages = ["src"]
+
+[tool.pytest.ini_options]
+markers = [
+    "smoke: smoke tests that run on every CI build",
+]
+asyncio_mode = "auto"
+```
+
+- [ ] **Step 4: Create the venv + lock + verify the server imports**
+
+```bash
+cd examples/ag-ui/python
+uv venv && uv sync 2>&1 | tail -5
+uv export --no-hashes -o requirements.txt 2>&1 | tail -2
+uv run python -c "from src.server import app; print('server import OK:', app.title)"
+```
+Expected: `server import OK: examples-ag-ui` (confirms graph + ag-ui-langgraph wiring imports). Return to repo root afterward (`cd ../../..`).
+
+> If `uv sync` fails resolving `ag-ui-langgraph`, check the exact version available (the cockpit ag-ui examples pin `ag-ui-langgraph==0.0.37`); align the constraint.
+
+- [ ] **Step 5: Write `examples/ag-ui/python/project.json`**
+
+```json
+{
+  "name": "examples-ag-ui-python",
+  "$schema": "../../../node_modules/nx/schemas/project-schema.json",
+  "projectType": "application",
+  "sourceRoot": "examples/ag-ui/python/src",
+  "targets": {}
+}
+```
+
+- [ ] **Step 6: Write `examples/ag-ui/python/README.md`**
+
+```markdown
+# examples/ag-ui — Python backend
+
+The (duplicated) chat a2ui graph served over AG-UI via `ag-ui-langgraph`.
+
+```bash
+cd examples/ag-ui/python
+uv venv && uv sync
+OPENAI_API_KEY=sk-... uv run uvicorn src.server:app --port 8000
+```
+
+`/ok` is the health route; the agent is mounted at `/agent`. The graph is
+duplicated from `examples/chat/python` (copy, don't import — standalone
+examples convention); it is transport-agnostic and unchanged.
+```
+
+- [ ] **Step 7: Commit**
+
+```bash
+git add examples/ag-ui/python
+git commit -m "feat(examples/ag-ui): python backend — duplicated a2ui graph served over ag-ui (uvicorn)"
+```
+
+---
+
+## Task 2: Angular app — scaffold + transport-swapped config
+
+**Files:** create `examples/ag-ui/angular/**`
+
+- [ ] **Step 1: Copy the build scaffolding from examples/chat (configs only, not the shell)**
+
+```bash
+mkdir -p examples/ag-ui/angular/src/app examples/ag-ui/angular/src/environments examples/ag-ui/angular/public
+cp examples/chat/angular/tsconfig.json examples/ag-ui/angular/tsconfig.json
+cp examples/chat/angular/tsconfig.app.json examples/ag-ui/angular/tsconfig.app.json
+cp examples/chat/angular/vite.config.mts examples/ag-ui/angular/vite.config.mts
+cp examples/chat/angular/src/test-setup.ts examples/ag-ui/angular/src/test-setup.ts
+cp examples/chat/angular/src/styles.css examples/ag-ui/angular/src/styles.css
+cp examples/chat/angular/public/favicon.ico examples/ag-ui/angular/public/favicon.ico
+cp examples/chat/angular/proxy.conf.mjs examples/ag-ui/angular/proxy.conf.mjs 2>/dev/null || true
+```
+
+- [ ] **Step 2: Write `examples/ag-ui/angular/project.json`**
+
+Adapt `examples/chat/angular/project.json` with these path substitutions (replace every `examples/chat/angular` → `examples/ag-ui/angular`, `examples-chat-angular` → `examples-ag-ui-angular`, output `dist/examples/chat/angular` → `dist/examples/ag-ui/angular`). Keep the build/serve/test target shapes identical. Add a `serve` proxy option if examples/chat doesn't already point at `proxy.conf.mjs`:
+
+```json
+{
+  "name": "examples-ag-ui-angular",
+  "$schema": "../../../node_modules/nx/schemas/project-schema.json",
+  "sourceRoot": "examples/ag-ui/angular/src",
+  "projectType": "application",
+  "prefix": "app",
+  "targets": {
+    "build": {
+      "executor": "@angular/build:application",
+      "outputs": ["{options.outputPath.base}"],
+      "options": {
+        "outputPath": { "base": "dist/examples/ag-ui/angular", "browser": "" },
+        "index": "examples/ag-ui/angular/src/index.html",
+        "browser": "examples/ag-ui/angular/src/main.ts",
+        "tsConfig": "examples/ag-ui/angular/tsconfig.app.json",
+        "assets": [{ "glob": "**/*", "input": "examples/ag-ui/angular/public" }],
+        "styles": ["examples/ag-ui/angular/src/styles.css"]
+      },
+      "configurations": {
+        "production": {
+          "budgets": [
+            { "type": "initial", "maximumWarning": "500kb", "maximumError": "1.5mb" },
+            { "type": "anyComponentStyle", "maximumWarning": "10kb", "maximumError": "16kb" }
+          ],
+          "outputHashing": "all"
+        },
+        "development": {
+          "optimization": false,
+          "extractLicenses": false,
+          "sourceMap": true,
+          "fileReplacements": [
+            { "replace": "examples/ag-ui/angular/src/environments/environment.ts",
+              "with": "examples/ag-ui/angular/src/environments/environment.development.ts" }
+          ]
+        }
+      },
+      "defaultConfiguration": "production"
+    },
+    "serve": {
+      "executor": "@angular/build:dev-server",
+      "options": { "proxyConfig": "examples/ag-ui/angular/proxy.conf.mjs" },
+      "configurations": {
+        "development": { "buildTarget": "examples-ag-ui-angular:build:development" },
+        "production": { "buildTarget": "examples-ag-ui-angular:build:production" }
+      },
+      "defaultConfiguration": "development"
+    },
+    "test": {
+      "executor": "@nx/vite:test",
+      "options": { "config": "examples/ag-ui/angular/vite.config.mts" }
+    }
+  }
+}
+```
+
+> Read `examples/chat/angular/project.json` first and reconcile any target options that differ (e.g. polyfills, `inlineStyleLanguage`). Match its shape; only the paths/names/proxy change.
+
+- [ ] **Step 3: Write `proxy.conf.mjs`** (dev routes `/agent` to the local uvicorn)
+
+```js
+// SPDX-License-Identifier: MIT
+// Dev only: routes the relative /agent calls to the local uvicorn ag-ui server.
+export default {
+  '/agent': { target: 'http://localhost:8000', secure: false, changeOrigin: true, ws: true },
+};
+```
+
+- [ ] **Step 4: Write the environments**
+
+`examples/ag-ui/angular/src/environments/environment.ts`:
+```ts
+// SPDX-License-Identifier: MIT
+export const environment = {
+  production: true,
+  agentUrl: '/agent',
+  telemetry: { enabled: false, sampleRate: 1 },
+  license: undefined as string | undefined,
+};
+```
+`examples/ag-ui/angular/src/environments/environment.development.ts`:
+```ts
+// SPDX-License-Identifier: MIT
+export const environment = {
+  production: false,
+  agentUrl: '/agent',
+  telemetry: { enabled: false, sampleRate: 1 },
+  license: undefined as string | undefined,
+};
+```
+
+- [ ] **Step 5: Write `src/index.html` + `src/main.ts`**
+
+`examples/ag-ui/angular/src/index.html` (mirror examples/chat's; set title):
+```html
+<!doctype html>
+<html lang="en">
+  <head>
+    <meta charset="utf-8" />
+    <title>AG-UI Chat — Threadplane Example</title>
+    <base href="/" />
+    <meta name="viewport" content="width=device-width, initial-scale=1" />
+    <link rel="icon" type="image/x-icon" href="favicon.ico" />
+  </head>
+  <body>
+    <app-root></app-root>
+  </body>
+</html>
+```
+`examples/ag-ui/angular/src/main.ts`:
+```ts
+// SPDX-License-Identifier: MIT
+import { bootstrapApplication } from '@angular/platform-browser';
+import { appConfig } from './app/app.config';
+import { App } from './app/app';
+
+bootstrapApplication(App, appConfig).catch((err) => console.error(err));
+```
+
+- [ ] **Step 6: Commit**
+
+```bash
+git add examples/ag-ui/angular
+git commit -m "feat(examples/ag-ui): angular scaffold (project.json, env, proxy, index/main)"
+```
+
+---
+
+## Task 3: Angular app — provideAgent config + single-conversation host
+
+**Files:** create `examples/ag-ui/angular/src/app/{app.config.ts,app.ts,app.html}`
+
+- [ ] **Step 1: Write `app.config.ts` (the transport swap — the heart of the parity demo)**
+
+```ts
+// SPDX-License-Identifier: MIT
+import {
+  ApplicationConfig,
+  provideBrowserGlobalErrorListeners,
+  provideZonelessChangeDetection,
+} from '@angular/core';
+import { provideThreadplaneTelemetry } from '@threadplane/telemetry/browser';
+import { provideChat } from '@threadplane/chat';
+import { provideAgent } from '@threadplane/ag-ui';
+import { environment } from '../environments/environment';
+
+export const appConfig: ApplicationConfig = {
+  providers: [
+    provideBrowserGlobalErrorListeners(),
+    provideZonelessChangeDetection(),
+    provideThreadplaneTelemetry(environment.telemetry),
+    // AG-UI transport: the entire difference from examples/chat is this line
+    // (examples/chat uses LANGGRAPH_THREADS_CONFIG + @threadplane/langgraph).
+    provideAgent({ url: environment.agentUrl }),
+    provideChat({ license: environment.license }),
+  ],
+};
+```
+
+> Verify the exact `provideAgent` option key by reading `libs/ag-ui/src/lib/provide-agent.ts` (`AgentConfig`). The cockpit ag-ui examples call `provideAgent({ url: '/agent' })`. If `provideThreadplaneTelemetry` requires a different config shape than `environment.telemetry`, match `examples/chat/angular/src/app/app.config.ts`'s usage.
+
+- [ ] **Step 2: Write the single-conversation host component `app.ts` + `app.html`**
+
+`examples/ag-ui/angular/src/app/app.ts`:
+```ts
+// SPDX-License-Identifier: MIT
+import { ChangeDetectionStrategy, Component } from '@angular/core';
+import { injectAgent } from '@threadplane/ag-ui';
+import { Chat } from '@threadplane/chat';
+
+@Component({
+  selector: 'app-root',
+  standalone: true,
+  changeDetection: ChangeDetectionStrategy.OnPush,
+  imports: [Chat],
+  templateUrl: './app.html',
+})
+export class App {
+  protected readonly agent = injectAgent();
+}
+```
+
+`examples/ag-ui/angular/src/app/app.html`:
+```html
+<main class="ag-ui-demo">
+  <header class="ag-ui-demo__header">
+    <h1>AG-UI Chat</h1>
+    <p>The Threadplane chat UI over the AG-UI transport.</p>
+  </header>
+  <chat main [agent]="agent" class="ag-ui-demo__chat" />
+</main>
+```
+
+> Verify the `<chat>` selector/inputs and the `Chat` export name against `libs/chat/src/public-api.ts` and how the cockpit ag-ui examples template it (`cockpit/ag-ui/streaming/angular/src/app/streaming.component.ts` uses `<chat main [agent]="agent" />`). Match that exactly. If `injectAgent`/`Chat` are imported from different entry points, fix the imports to match the cockpit ag-ui example.
+
+- [ ] **Step 3: Add minimal layout styles to `src/styles.css`**
+
+Append:
+```css
+.ag-ui-demo { display: flex; flex-direction: column; height: 100dvh; }
+.ag-ui-demo__header { padding: 12px 16px; border-bottom: 1px solid var(--tp-border, #e5e7eb); }
+.ag-ui-demo__header h1 { margin: 0; font-size: 1.1rem; }
+.ag-ui-demo__header p { margin: 2px 0 0; font-size: 0.85rem; opacity: 0.7; }
+.ag-ui-demo__chat { flex: 1 1 auto; min-height: 0; }
+```
+
+- [ ] **Step 4: Build the app**
+
+Run: `npx nx build examples-ag-ui-angular`
+Expected: builds successfully. If it fails on a missing import/selector, fix against the cockpit ag-ui example references noted above and rebuild. Do NOT introduce any `@threadplane/langgraph` import (that's the whole point — this app is langgraph-free).
+
+- [ ] **Step 5: Confirm no langgraph coupling leaked in**
+
+Run: `grep -rn "@threadplane/langgraph\|LANGGRAPH\|langGraphApiUrl\|LangGraphThreads" examples/ag-ui/angular/src || echo "clean: no langgraph references"`
+Expected: `clean: no langgraph references`.
+
+- [ ] **Step 6: Commit**
+
+```bash
+git add examples/ag-ui/angular/src/app examples/ag-ui/angular/src/styles.css
+git commit -m "feat(examples/ag-ui): provideAgent config + single-conversation chat host"
+```
+
+---
+
+## Task 4: Umbrella project + local end-to-end verification
+
+**Files:** create `examples/ag-ui/project.json`
+
+- [ ] **Step 1: Write `examples/ag-ui/project.json`**
+
+Read `examples/chat/project.json` and mirror it, substituting `chat` → `ag-ui` in name/paths:
+```json
+{
+  "name": "examples-ag-ui",
+  "$schema": "../../node_modules/nx/schemas/project-schema.json",
+  "projectType": "library",
+  "targets": {}
+}
+```
+(If `examples/chat/project.json` has real targets, mirror their shape with paths adjusted.)
+
+- [ ] **Step 2: Start the backend**
+
+```bash
+cd examples/ag-ui/python
+OPENAI_API_KEY="$(grep -E '^OPENAI_API_KEY=' /Users/blove/repos/angular-agent-framework/.env | cut -d= -f2-)" uv run uvicorn src.server:app --port 8000 &
+sleep 5
+curl -fsS http://localhost:8000/ok && echo
+cd ../../..
+```
+Expected: `{"ok":true}`.
+
+- [ ] **Step 3: Drive one real run through the backend (a2ui path)**
+
+```bash
+curl -sS --max-time 45 -X POST http://localhost:8000/agent \
+  -H "content-type: application/json" -H "accept: text/event-stream" \
+  -d '{"threadId":"local","runId":"r1","messages":[{"id":"u1","role":"user","content":"show me the weather in Paris"}],"state":{},"tools":[],"context":[],"forwardedProps":{}}' \
+  | grep -oE '"type":"[A-Z_]+"' | sort | uniq -c
+```
+Expected: AG-UI events including `RUN_STARTED`, `TEXT_MESSAGE_*` and/or `TOOL_CALL_*` (the a2ui `render_a2ui_surface` tool call) and `RUN_FINISHED`. This proves the duplicated graph emits a2ui over ag-ui.
+
+> The exact prompt that triggers a2ui depends on the graph; if "weather" doesn't trigger a surface, read `examples/chat/python/src/graph.py` for the tool-triggering intent and use a matching prompt. The pass criterion is a completed AG-UI run with tool-call events, not a specific surface.
+
+- [ ] **Step 4: Serve the Angular app + manual check (optional but recommended)**
+
+```bash
+npx nx serve examples-ag-ui-angular &
+sleep 25
+curl -sS -o /dev/null -w 'app http=%{http_code}\n' http://localhost:4200/
+```
+Expected: `200`. (Full visual a2ui-render confirmation is covered by Part 2b's e2e; this just confirms the app serves and proxies `/agent`.)
+
+- [ ] **Step 5: Tear down the background servers**
+
+```bash
+pkill -f "uvicorn src.server:app" 2>/dev/null || true
+pkill -f "nx serve examples-ag-ui-angular" 2>/dev/null || true
+```
+
+- [ ] **Step 6: Commit**
+
+```bash
+git add examples/ag-ui/project.json
+git commit -m "feat(examples/ag-ui): umbrella project + local run verified (uvicorn /ok + a2ui run)"
+```
+
+---
+
+## Task 5: PR
+
+- [ ] **Step 1: Push + open PR**
+
+```bash
+git push -u origin claude/examples-ag-ui-local
+gh pr create --title "feat(examples/ag-ui): local-runnable standalone ag-ui chat example (Part 2a)" --body "$(cat <<'EOF'
+## Summary
+
+Standalone `examples/ag-ui/` — a single-conversation chat app over the AG-UI transport + a uvicorn `ag-ui-langgraph` backend running the (duplicated) a2ui graph. Demonstrates LangGraph↔AG-UI transport + a2ui parity. Runnable via `nx serve` + `uvicorn`.
+
+- `examples/ag-ui/python/` — chat a2ui graph duplicated verbatim (transport-agnostic) + `server.py` (ag-ui-langgraph, token-optional auth, `/ok`).
+- `examples/ag-ui/angular/` — simplified single-conversation `<chat>` host via `provideAgent({ url: '/agent' })`. **No `@threadplane/langgraph`** — the entire delta from `examples/chat` is the transport provider.
+- **Scope note:** simplified shell (no thread sidebar) — `LangGraphThreadsAdapter` (thread CRUD) has no AG-UI equivalent. Relies on the `customEvents` signal (#606) for live a2ui.
+
+Part 2a of `docs/superpowers/specs/2026-06-06-examples-ag-ui-standalone-design.md`. e2e/smoke = Part 2b; deploy (Railway + `ag-ui-demo.threadplane.ai`) = Part 3.
+
+## Test plan
+- [x] `uvicorn src.server:app` → `/ok` 200; POST `/agent` streams an AG-UI a2ui run.
+- [x] `nx build examples-ag-ui-angular` clean; no langgraph references.
+- [ ] CI green.
+
+🤖 Generated with [Claude Code](https://claude.com/claude-code)
+EOF
+)"
+```
+
+- [ ] **Step 2: Arm auto-merge**
+
+```bash
+gh pr merge <PR_NUMBER> --squash --auto --delete-branch
+```
+
+- [ ] **Step 3: Wait for green + merge.** If `Vercel – threadplane` preview fails on the known transient npm-registry 404, redeploy that preview via the Vercel API rather than treating it as a real failure.
+
+---
+
+## Self-Review
+
+- [ ] **Spec coverage (Part 2, local subset):** angular app over provideAgent → Tasks 2-3. Duplicated graph + uvicorn server (token-optional) → Task 1. Local run parity → Task 4. e2e/smoke deferred to Part 2b (noted). Deploy deferred to Part 3 (noted).
+- [ ] **No placeholders:** every file has full content or an exact copy+substitute instruction with the reference file named.
+- [ ] **Type/name consistency:** `provideAgent`/`injectAgent` from `@threadplane/ag-ui`; `Chat` + `<chat main [agent]>` from `@threadplane/chat`; `environment.agentUrl`/`environment.telemetry`/`environment.license` consistent across app.config (Task 3) + environments (Task 2). Project names `examples-ag-ui-angular` / `examples-ag-ui-python` consistent across project.json + serve buildTarget.
+- [ ] **Verify-against-reference notes:** Tasks 2-3 instruct reading `examples/chat/angular/project.json`, `libs/ag-ui/src/lib/provide-agent.ts`, `libs/chat/src/public-api.ts`, and `cockpit/ag-ui/streaming/angular` to pin exact selectors/option keys — these are real files, not placeholders.
diff --git a/examples/ag-ui/angular/project.json b/examples/ag-ui/angular/project.json
new file mode 100644
index 000000000..70dd999a5
--- /dev/null
+++ b/examples/ag-ui/angular/project.json
@@ -0,0 +1,93 @@
+{
+  "name": "examples-ag-ui-angular",
+  "$schema": "../../../node_modules/nx/schemas/project-schema.json",
+  "sourceRoot": "examples/ag-ui/angular/src",
+  "projectType": "application",
+  "prefix": "app",
+  "targets": {
+    "build": {
+      "executor": "@angular/build:application",
+      "outputs": [
+        "{options.outputPath.base}"
+      ],
+      "options": {
+        "outputPath": {
+          "base": "dist/examples/ag-ui/angular",
+          "browser": ""
+        },
+        "index": "examples/ag-ui/angular/src/index.html",
+        "browser": "examples/ag-ui/angular/src/main.ts",
+        "tsConfig": "examples/ag-ui/angular/tsconfig.app.json",
+        "assets": [
+          {
+            "glob": "**/*",
+            "input": "examples/ag-ui/angular/public"
+          }
+        ],
+        "styles": [
+          "examples/ag-ui/angular/src/styles.css"
+        ]
+      },
+      "configurations": {
+        "production": {
+          "budgets": [
+            {
+              "type": "initial",
+              "maximumWarning": "500kb",
+              "maximumError": "1.5mb"
+            },
+            {
+              "type": "anyComponentStyle",
+              "maximumWarning": "10kb",
+              "maximumError": "16kb"
+            }
+          ],
+          "outputHashing": "all"
+        },
+        "development": {
+          "optimization": false,
+          "extractLicenses": false,
+          "sourceMap": true,
+          "fileReplacements": [
+            {
+              "replace": "examples/ag-ui/angular/src/environments/environment.ts",
+              "with": "examples/ag-ui/angular/src/environments/environment.development.ts"
+            }
+          ]
+        }
+      },
+      "defaultConfiguration": "development"
+    },
+    "serve": {
+      "continuous": true,
+      "executor": "@angular/build:dev-server",
+      "options": {
+        "port": 4201,
+        "proxyConfig": "examples/ag-ui/angular/proxy.conf.mjs"
+      },
+      "configurations": {
+        "production": {
+          "buildTarget": "examples-ag-ui-angular:build:production"
+        },
+        "development": {
+          "buildTarget": "examples-ag-ui-angular:build:development"
+        }
+      },
+      "defaultConfiguration": "development"
+    },
+    "test": {
+      "executor": "@nx/vitest:test",
+      "options": {
+        "configFile": "examples/ag-ui/angular/vite.config.mts"
+      }
+    },
+    "lint": {
+      "executor": "@nx/eslint:lint"
+    }
+  },
+  "tags": [
+    "scope:examples",
+    "scope:examples-ag-ui",
+    "type:app"
+  ]
+}
diff --git a/examples/ag-ui/angular/proxy.conf.mjs b/examples/ag-ui/angular/proxy.conf.mjs
new file mode 100644
index 000000000..e3884661c
--- /dev/null
+++ b/examples/ag-ui/angular/proxy.conf.mjs
@@ -0,0 +1,5 @@
+// SPDX-License-Identifier: MIT
+// Dev only: routes the relative /agent calls to the local uvicorn ag-ui server.
+export default {
+  '/agent': { target: 'http://localhost:8000', secure: false, changeOrigin: true, ws: true },
+};
diff --git a/examples/ag-ui/angular/public/favicon.ico b/examples/ag-ui/angular/public/favicon.ico
new file mode 100644
index 000000000..317ebcb23
Binary files /dev/null and b/examples/ag-ui/angular/public/favicon.ico differ
diff --git a/examples/ag-ui/angular/src/app/app.config.ts b/examples/ag-ui/angular/src/app/app.config.ts
new file mode 100644
index 000000000..28d0278fe
--- /dev/null
+++ b/examples/ag-ui/angular/src/app/app.config.ts
@@ -0,0 +1,20 @@
+// SPDX-License-Identifier: MIT
+import {
+  ApplicationConfig,
+  provideBrowserGlobalErrorListeners,
+  provideZonelessChangeDetection,
+} from '@angular/core';
+import { provideThreadplaneTelemetry } from '@threadplane/telemetry/browser';
+import { provideChat } from '@threadplane/chat';
+import { provideAgent } from '@threadplane/ag-ui';
+import { environment } from '../environments/environment';
+
+export const appConfig: ApplicationConfig = {
+  providers: [
+    provideBrowserGlobalErrorListeners(),
+    provideZonelessChangeDetection(),
+    provideThreadplaneTelemetry(environment.telemetry),
+    provideAgent({ url: environment.agentUrl }),
+    provideChat({ license: environment.license }),
+  ],
+};
diff --git a/examples/ag-ui/angular/src/app/app.html b/examples/ag-ui/angular/src/app/app.html
new file mode 100644
index 000000000..a35381138
--- /dev/null
+++ b/examples/ag-ui/angular/src/app/app.html
@@ -0,0 +1,7 @@
+<main class="ag-ui-demo">
+  <header class="ag-ui-demo__header">
+    <h1>AG-UI Chat</h1>
+    <p>The Threadplane chat UI over the AG-UI transport.</p>
+  </header>
+  <chat main [agent]="agent" class="ag-ui-demo__chat" />
+</main>
diff --git a/examples/ag-ui/angular/src/app/app.ts b/examples/ag-ui/angular/src/app/app.ts
new file mode 100644
index 000000000..c1bf26ce7
--- /dev/null
+++ b/examples/ag-ui/angular/src/app/app.ts
@@ -0,0 +1,15 @@
+// SPDX-License-Identifier: MIT
+import { ChangeDetectionStrategy, Component } from '@angular/core';
+import { injectAgent } from '@threadplane/ag-ui';
+import { ChatComponent } from '@threadplane/chat';
+
+@Component({
+  selector: 'app-root',
+  standalone: true,
+  changeDetection: ChangeDetectionStrategy.OnPush,
+  imports: [ChatComponent],
+  templateUrl: './app.html',
+})
+export class App {
+  protected readonly agent = injectAgent();
+}
diff --git a/examples/ag-ui/angular/src/environments/environment.development.ts b/examples/ag-ui/angular/src/environments/environment.development.ts
new file mode 100644
index 000000000..56685712d
--- /dev/null
+++ b/examples/ag-ui/angular/src/environments/environment.development.ts
@@ -0,0 +1,7 @@
+// SPDX-License-Identifier: MIT
+export const environment = {
+  production: false,
+  agentUrl: '/agent',
+  telemetry: { enabled: false, sampleRate: 1 },
+  license: undefined as string | undefined,
+};
diff --git a/examples/ag-ui/angular/src/environments/environment.ts b/examples/ag-ui/angular/src/environments/environment.ts
new file mode 100644
index 000000000..814fd718e
--- /dev/null
+++ b/examples/ag-ui/angular/src/environments/environment.ts
@@ -0,0 +1,7 @@
+// SPDX-License-Identifier: MIT
+export const environment = {
+  production: true,
+  agentUrl: '/agent',
+  telemetry: { enabled: false, sampleRate: 1 },
+  license: undefined as string | undefined,
+};
diff --git a/examples/ag-ui/angular/src/index.html b/examples/ag-ui/angular/src/index.html
new file mode 100644
index 000000000..40c8ac2b9
--- /dev/null
+++ b/examples/ag-ui/angular/src/index.html
@@ -0,0 +1,13 @@
+<!doctype html>
+<html lang="en">
+  <head>
+    <meta charset="utf-8" />
+    <title>AG-UI Chat — Threadplane Example</title>
+    <base href="/" />
+    <meta name="viewport" content="width=device-width, initial-scale=1" />
+    <link rel="icon" type="image/x-icon" href="favicon.ico" />
+  </head>
+  <body>
+    <app-root></app-root>
+  </body>
+</html>
diff --git a/examples/ag-ui/angular/src/main.ts b/examples/ag-ui/angular/src/main.ts
new file mode 100644
index 000000000..5e219f151
--- /dev/null
+++ b/examples/ag-ui/angular/src/main.ts
@@ -0,0 +1,6 @@
+// SPDX-License-Identifier: MIT
+import { bootstrapApplication } from '@angular/platform-browser';
+import { appConfig } from './app/app.config';
+import { App } from './app/app';
+
+bootstrapApplication(App, appConfig).catch((err) => console.error(err));
diff --git a/examples/ag-ui/angular/src/styles.css b/examples/ag-ui/angular/src/styles.css
new file mode 100644
index 000000000..6d9a5bde9
--- /dev/null
+++ b/examples/ag-ui/angular/src/styles.css
@@ -0,0 +1,100 @@
+html, body {
+  margin: 0;
+  padding: 0;
+  height: 100%;
+  font-family: system-ui, -apple-system, sans-serif;
+  background: var(--demo-page-bg);
+  color: var(--demo-page-text);
+}
+
+/*
+ * Demo page color scheme — driven by `data-color-scheme` on <html>.
+ * The pre-bootstrap inline script in index.html sets the attribute
+ * from persisted state before any stylesheet applies; the runtime
+ * effect in DemoShell keeps it in sync afterwards. Default (no
+ * attribute) is dark to match prior behavior.
+ */
+html {
+  --demo-page-bg: #0f1116;
+  --demo-page-text: #e6e9ef;
+}
+html[data-color-scheme="light"] {
+  --demo-page-bg: #ffffff;
+  --demo-page-text: #1c1c1c;
+}
+
+/*
+ * A2UI theme presets — switched at runtime via the palette "Theme"
+ * dropdown by toggling `data-theme` on the document root. Mirrors the
+ * preset CSS files shipped from `@threadplane/chat/themes/*.css`; we inline
+ * them here to avoid the workspace-vs-published-path resolution
+ * complexity of importing them dynamically. Default ('default-dark')
+ * uses the lib's :host defaults, so no override block is needed.
+ */
+
+html[data-theme='default-light'] {
+  --a2ui-primary: #4f8df5;
+  --a2ui-on-primary: #ffffff;
+  --a2ui-primary-hover: #3b7be3;
+  --a2ui-secondary: #5b6275;
+  --a2ui-on-secondary: #ffffff;
+  --a2ui-surface: #fafafa;
+  --a2ui-on-surface: #1a1d23;
+  --a2ui-surface-variant: rgba(0, 0, 0, 0.04);
+  --a2ui-on-surface-variant: rgba(0, 0, 0, 0.6);
+  --a2ui-outline: rgba(0, 0, 0, 0.12);
+  --a2ui-outline-variant: rgba(0, 0, 0, 0.06);
+  --a2ui-error: #d33533;
+  --a2ui-on-error: #ffffff;
+  --a2ui-scrim: rgba(0, 0, 0, 0.4);
+  --a2ui-elevation-1: 0 1px 2px rgba(0, 0, 0, 0.08);
+  --a2ui-elevation-2: 0 2px 4px rgba(0, 0, 0, 0.10);
+  --a2ui-elevation-3: 0 4px 8px rgba(0, 0, 0, 0.12);
+  --a2ui-elevation-4: 0 8px 16px rgba(0, 0, 0, 0.14);
+  --a2ui-elevation-5: 0 16px 32px rgba(0, 0, 0, 0.16);
+}
+
+html[data-theme='material-dark'] {
+  --a2ui-primary: #D0BCFF;
+  --a2ui-on-primary: #381E72;
+  --a2ui-primary-hover: #B69DF8;
+  --a2ui-secondary: #CCC2DC;
+  --a2ui-on-secondary: #332D41;
+  --a2ui-surface: #1C1B1F;
+  --a2ui-on-surface: #E6E1E5;
+  --a2ui-surface-variant: #49454F;
+  --a2ui-on-surface-variant: #CAC4D0;
+  --a2ui-outline: #938F99;
+  --a2ui-outline-variant: #49454F;
+  --a2ui-error: #F2B8B5;
+  --a2ui-on-error: #601410;
+  --a2ui-scrim: rgba(0, 0, 0, 0.6);
+}
+
+html[data-theme='material-light'] {
+  --a2ui-primary: #6750A4;
+  --a2ui-on-primary: #FFFFFF;
+  --a2ui-primary-hover: #533F8E;
+  --a2ui-secondary: #625B71;
+  --a2ui-on-secondary: #FFFFFF;
+  --a2ui-surface: #FFFBFE;
+  --a2ui-on-surface: #1C1B1F;
+  --a2ui-surface-variant: #E7E0EC;
+  --a2ui-on-surface-variant: #49454F;
+  --a2ui-outline: #79747E;
+  --a2ui-outline-variant: #CAC4D0;
+  --a2ui-error: #B3261E;
+  --a2ui-on-error: #FFFFFF;
+  --a2ui-scrim: rgba(0, 0, 0, 0.4);
+  --a2ui-elevation-1: 0 1px 2px rgba(0, 0, 0, 0.08);
+  --a2ui-elevation-2: 0 2px 4px rgba(0, 0, 0, 0.10);
+  --a2ui-elevation-3: 0 4px 8px rgba(0, 0, 0, 0.12);
+  --a2ui-elevation-4: 0 8px 16px rgba(0, 0, 0, 0.14);
+  --a2ui-elevation-5: 0 16px 32px rgba(0, 0, 0, 0.16);
+}
+
+.ag-ui-demo { display: flex; flex-direction: column; height: 100dvh; }
+.ag-ui-demo__header { padding: 12px 16px; border-bottom: 1px solid var(--tp-border, #e5e7eb); }
+.ag-ui-demo__header h1 { margin: 0; font-size: 1.1rem; }
+.ag-ui-demo__header p { margin: 2px 0 0; font-size: 0.85rem; opacity: 0.7; }
+.ag-ui-demo__chat { flex: 1 1 auto; min-height: 0; }
diff --git a/examples/ag-ui/angular/src/test-setup.ts b/examples/ag-ui/angular/src/test-setup.ts
new file mode 100644
index 000000000..054534fcf
--- /dev/null
+++ b/examples/ag-ui/angular/src/test-setup.ts
@@ -0,0 +1,12 @@
+// SPDX-License-Identifier: MIT
+import { getTestBed } from '@angular/core/testing';
+import {
+  BrowserTestingModule,
+  platformBrowserTesting,
+} from '@angular/platform-browser/testing';
+
+getTestBed().initTestEnvironment(
+  BrowserTestingModule,
+  platformBrowserTesting(),
+  { teardown: { destroyAfterEach: true } },
+);
diff --git a/examples/ag-ui/angular/tsconfig.app.json b/examples/ag-ui/angular/tsconfig.app.json
new file mode 100644
index 000000000..8ad2e6feb
--- /dev/null
+++ b/examples/ag-ui/angular/tsconfig.app.json
@@ -0,0 +1,22 @@
+{
+  "extends": "./tsconfig.json",
+  "compilerOptions": {
+    "outDir": "../../../dist/out-tsc",
+    "lib": ["es2022", "dom"],
+    "types": [],
+    "emitDeclarationOnly": false
+  },
+  "files": ["src/main.ts"],
+  "include": ["src/**/*.ts"],
+  "references": [
+    {
+      "path": "../../../libs/ag-ui"
+    },
+    {
+      "path": "../../../libs/chat"
+    },
+    {
+      "path": "../../../libs/telemetry/tsconfig.lib.json"
+    }
+  ]
+}
diff --git a/examples/ag-ui/angular/tsconfig.json b/examples/ag-ui/angular/tsconfig.json
new file mode 100644
index 000000000..1139eb967
--- /dev/null
+++ b/examples/ag-ui/angular/tsconfig.json
@@ -0,0 +1,24 @@
+{
+  "extends": "../../../tsconfig.base.json",
+  "compilerOptions": {
+    "noPropertyAccessFromIndexSignature": false,
+    "experimentalDecorators": true,
+    "module": "preserve",
+    "emitDeclarationOnly": false,
+    "composite": false,
+    "lib": ["es2022", "dom"],
+    "skipLibCheck": true,
+    "strict": false
+  },
+  "angularCompilerOptions": {
+    "enableI18nLegacyMessageIdFormat": false,
+    "strictInjectionParameters": false,
+    "strictInputAccessModifiers": false,
+    "strictTemplates": false
+  },
+  "files": [],
+  "include": [],
+  "references": [
+    { "path": "./tsconfig.app.json" }
+  ]
+}
diff --git a/examples/ag-ui/angular/vite.config.mts b/examples/ag-ui/angular/vite.config.mts
new file mode 100644
index 000000000..44f5e5e99
--- /dev/null
+++ b/examples/ag-ui/angular/vite.config.mts
@@ -0,0 +1,19 @@
+/// <reference types='vitest' />
+import { defineConfig } from 'vite';
+import angular from '@analogjs/vite-plugin-angular';
+import { nxViteTsPaths } from '@nx/vite/plugins/nx-tsconfig-paths.plugin';
+
+export default defineConfig({
+  root: __dirname,
+  cacheDir: '../../../node_modules/.vite/examples-ag-ui-angular',
+  plugins: [angular(), nxViteTsPaths()],
+  test: {
+    globals: true,
+    environment: 'jsdom',
+    setupFiles: ['src/test-setup.ts'],
+    include: ['src/**/*.spec.ts'],
+    reporters: ['default'],
+    pool: 'forks',
+    passWithNoTests: true,
+  },
+});
diff --git a/examples/ag-ui/project.json b/examples/ag-ui/project.json
new file mode 100644
index 000000000..daf37283a
--- /dev/null
+++ b/examples/ag-ui/project.json
@@ -0,0 +1,21 @@
+{
+  "name": "examples-ag-ui",
+  "$schema": "../../node_modules/nx/schemas/project-schema.json",
+  "projectType": "application",
+  "sourceRoot": "examples/ag-ui",
+  "targets": {
+    "serve": {
+      "executor": "nx:run-commands",
+      "options": {
+        "commands": [
+          "npx nx run examples-ag-ui-python:serve",
+          "npx nx run examples-ag-ui-angular:serve"
+        ],
+        "parallel": true
+      }
+    }
+  },
+  "tags": [
+    "scope:examples-ag-ui"
+  ]
+}
diff --git a/examples/ag-ui/python/.env.example b/examples/ag-ui/python/.env.example
new file mode 100644
index 000000000..714d02a06
--- /dev/null
+++ b/examples/ag-ui/python/.env.example
@@ -0,0 +1,3 @@
+# Copy to .env and fill in your key. Required for the demo to make
+# real LLM calls against the OpenAI API.
+OPENAI_API_KEY=sk-...
diff --git a/examples/ag-ui/python/.python-version b/examples/ag-ui/python/.python-version
new file mode 100644
index 000000000..e4fba2183
--- /dev/null
+++ b/examples/ag-ui/python/.python-version
@@ -0,0 +1 @@
+3.12
diff --git a/examples/ag-ui/python/README.md b/examples/ag-ui/python/README.md
new file mode 100644
index 000000000..d291f601d
--- /dev/null
+++ b/examples/ag-ui/python/README.md
@@ -0,0 +1,13 @@
+# examples/ag-ui — Python backend
+
+The (duplicated) chat a2ui graph served over AG-UI via `ag-ui-langgraph`.
+
+```bash
+cd examples/ag-ui/python
+uv venv && uv sync
+OPENAI_API_KEY=sk-... uv run uvicorn src.server:app --port 8000
+```
+
+`/ok` is the health route; the agent is mounted at `/agent`. The graph is
+duplicated from `examples/chat/python` (copy, don't import — standalone
+examples convention); it is transport-agnostic and unchanged.
diff --git a/examples/ag-ui/python/langgraph.json b/examples/ag-ui/python/langgraph.json
new file mode 100644
index 000000000..afa5fa1c4
--- /dev/null
+++ b/examples/ag-ui/python/langgraph.json
@@ -0,0 +1,8 @@
+{
+  "graphs": {
+    "chat": "./src/graph.py:graph"
+  },
+  "dependencies": ["."],
+  "python_version": "3.12",
+  "env": ".env"
+}
diff --git a/examples/ag-ui/python/project.json b/examples/ag-ui/python/project.json
new file mode 100644
index 000000000..a8ebd2427
--- /dev/null
+++ b/examples/ag-ui/python/project.json
@@ -0,0 +1,7 @@
+{
+  "name": "examples-ag-ui-python",
+  "$schema": "../../../node_modules/nx/schemas/project-schema.json",
+  "projectType": "application",
+  "sourceRoot": "examples/ag-ui/python/src",
+  "targets": {}
+}
diff --git a/examples/ag-ui/python/pyproject.toml b/examples/ag-ui/python/pyproject.toml
new file mode 100644
index 000000000..7cbd62c08
--- /dev/null
+++ b/examples/ag-ui/python/pyproject.toml
@@ -0,0 +1,31 @@
+[project]
+name = "examples-ag-ui-python"
+version = "0.1.0"
+requires-python = ">=3.12"
+dependencies = [
+    "langgraph>=0.3",
+    "langchain-openai>=0.3",
+    "ag-ui-langgraph>=0.0.37",
+    "fastapi>=0.115",
+    "uvicorn>=0.30",
+    "python-dotenv>=1.0",
+]
+
+[tool.uv]
+dev-dependencies = [
+    "pytest>=8.0",
+    "pytest-asyncio>=0.23",
+]
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[tool.hatch.build.targets.wheel]
+packages = ["src"]
+
+[tool.pytest.ini_options]
+markers = [
+    "smoke: smoke tests that run on every CI build",
+]
+asyncio_mode = "auto"
diff --git a/examples/ag-ui/python/requirements.txt b/examples/ag-ui/python/requirements.txt
new file mode 100644
index 000000000..f36244806
--- /dev/null
+++ b/examples/ag-ui/python/requirements.txt
@@ -0,0 +1,181 @@
+# This file was autogenerated by uv via the following command:
+#    uv export --no-hashes -o requirements.txt
+-e .
+ag-ui-a2ui-toolkit==0.0.2
+    # via ag-ui-langgraph
+ag-ui-langgraph==0.0.40
+    # via examples-ag-ui-python
+ag-ui-protocol==0.1.19
+    # via ag-ui-langgraph
+annotated-doc==0.0.4
+    # via fastapi
+annotated-types==0.7.0
+    # via pydantic
+anyio==4.13.0
+    # via
+    #   httpx
+    #   openai
+    #   starlette
+certifi==2026.5.20
+    # via
+    #   httpcore
+    #   httpx
+    #   requests
+charset-normalizer==3.4.7
+    # via requests
+click==8.4.1
+    # via uvicorn
+colorama==0.4.6 ; sys_platform == 'win32'
+    # via
+    #   click
+    #   pytest
+    #   tqdm
+distro==1.9.0
+    # via openai
+fastapi==0.136.3
+    # via examples-ag-ui-python
+h11==0.16.0
+    # via
+    #   httpcore
+    #   uvicorn
+httpcore==1.0.9
+    # via httpx
+httpx==0.28.1
+    # via
+    #   langgraph-sdk
+    #   langsmith
+    #   openai
+idna==3.18
+    # via
+    #   anyio
+    #   httpx
+    #   requests
+iniconfig==2.3.0
+    # via pytest
+jiter==0.15.0
+    # via openai
+jsonpatch==1.33
+    # via langchain-core
+jsonpointer==3.1.1
+    # via jsonpatch
+langchain==1.3.4
+    # via ag-ui-langgraph
+langchain-core==1.4.1
+    # via
+    #   ag-ui-langgraph
+    #   langchain
+    #   langchain-openai
+    #   langgraph
+    #   langgraph-checkpoint
+    #   langgraph-prebuilt
+    #   langgraph-sdk
+langchain-openai==1.2.2
+    # via examples-ag-ui-python
+langchain-protocol==0.0.16
+    # via
+    #   langchain-core
+    #   langgraph-sdk
+langgraph==1.2.4
+    # via
+    #   ag-ui-langgraph
+    #   examples-ag-ui-python
+    #   langchain
+langgraph-checkpoint==4.1.1
+    # via
+    #   langgraph
+    #   langgraph-prebuilt
+langgraph-prebuilt==1.1.0
+    # via langgraph
+langgraph-sdk==0.4.2
+    # via langgraph
+langsmith==0.8.9
+    # via langchain-core
+openai==2.41.0
+    # via langchain-openai
+orjson==3.11.9
+    # via
+    #   langgraph-sdk
+    #   langsmith
+ormsgpack==1.12.2
+    # via langgraph-checkpoint
+packaging==26.2
+    # via
+    #   langchain-core
+    #   langsmith
+    #   pytest
+pluggy==1.6.0
+    # via pytest
+pydantic==2.13.4
+    # via
+    #   ag-ui-langgraph
+    #   ag-ui-protocol
+    #   fastapi
+    #   langchain
+    #   langchain-core
+    #   langgraph
+    #   langsmith
+    #   openai
+pydantic-core==2.46.4
+    # via pydantic
+pygments==2.20.0
+    # via pytest
+pytest==9.0.3
+    # via pytest-asyncio
+pytest-asyncio==1.4.0
+python-dotenv==1.2.2
+    # via examples-ag-ui-python
+pyyaml==6.0.3
+    # via langchain-core
+regex==2026.5.9
+    # via tiktoken
+requests==2.34.2
+    # via
+    #   langsmith
+    #   requests-toolbelt
+    #   tiktoken
+requests-toolbelt==1.0.0
+    # via langsmith
+sniffio==1.3.1
+    # via openai
+starlette==1.2.1
+    # via fastapi
+tenacity==9.1.4
+    # via langchain-core
+tiktoken==0.13.0
+    # via langchain-openai
+tqdm==4.68.1
+    # via openai
+typing-extensions==4.15.0
+    # via
+    #   anyio
+    #   fastapi
+    #   langchain-core
+    #   langchain-protocol
+    #   openai
+    #   pydantic
+    #   pydantic-core
+    #   pytest-asyncio
+    #   starlette
+    #   typing-inspection
+typing-inspection==0.4.2
+    # via
+    #   fastapi
+    #   pydantic
+urllib3==2.7.0
+    # via requests
+uuid-utils==0.16.0
+    # via
+    #   langchain-core
+    #   langsmith
+uvicorn==0.49.0
+    # via examples-ag-ui-python
+websockets==15.0.1
+    # via
+    #   langgraph-sdk
+    #   langsmith
+xxhash==3.7.0
+    # via
+    #   langgraph
+    #   langsmith
+zstandard==0.25.0
+    # via langsmith
diff --git a/examples/ag-ui/python/src/graph.py b/examples/ag-ui/python/src/graph.py
new file mode 100644
index 000000000..48e0c4c6d
--- /dev/null
+++ b/examples/ag-ui/python/src/graph.py
@@ -0,0 +1,688 @@
+"""Single-node-plus-tools streaming chat graph.
+
+State the client may send via the LangGraph ``submit``'s ``state`` field:
+
+  - ``model`` — OpenAI model name. Default: ``gpt-5-mini``.
+  - ``reasoning_effort`` — 'minimal' | 'low' | 'medium' | 'high'.
+                           Default: 'minimal' so first-token latency
+                           stays low. Demos surface this as a palette
+                           dropdown so users can dial in visible reasoning.
+
+Topology:
+
+  __start__ → generate ─┬─ [has tool_calls] ─→ tools ─→ generate (loop)
+                        └─ [no tool_calls]  ─→ attach_citations ─→ generate_title ─→ __end__
+
+The terminal ``attach_citations`` node walks back from the final AI
+message to the most recent ToolMessage, parses its JSON content, and
+replaces the AI message with one carrying ``additional_kwargs.citations``
+populated. Uses RemoveMessage + AIMessage with the same id (standard
+LangGraph in-place edit pattern), keeping the chat composition's
+track-by-id stable.
+"""
+import json
+import os
+from typing import Annotated, Literal, Optional
+from typing_extensions import TypedDict
+
+from langgraph.graph import StateGraph, END
+from langgraph.graph.message import add_messages
+from langgraph.prebuilt import ToolNode
+from langgraph.types import interrupt
+from langchain_openai import ChatOpenAI
+from langchain_core.messages import (
+    AIMessage,
+    HumanMessage,
+    RemoveMessage,
+    SystemMessage,
+    ToolMessage,
+)
+from langchain_core.runnables import RunnableConfig
+from langchain_core.tools import tool
+from langgraph_sdk import get_client
+from langsmith import traceable
+
+from src.streaming.a2ui_partial_handler import A2uiPartialHandler
+from src.streaming.envelope_tool import render_a2ui_surface
+from src.streaming.envelope_normalizer import normalize_envelope_args
+from src.schemas.a2ui_v1 import A2UI_V1_SCHEMA_PROMPT
+
+
+_TITLE_PROMPT = (
+    "In 3-5 words, summarize what the user is asking about. "
+    "Output ONLY the title — no quotes, no period, no prefix."
+)
+_TITLE_MODEL = "gpt-5-mini"
+
+
+@traceable(name="generate_title", run_type="tool")
+async def generate_title(state: "State", config: RunnableConfig) -> dict:
+    """Terminal side effect: generate and persist a short thread title.
+
+    Idempotent — only writes when metadata.title is currently absent.
+    Errors are NOT raised (title is a UX nicety, never a blocker) but
+    ARE returned in the run output so LangSmith captures them — the
+    bare `except Exception: return` previously hid a prod failure
+    where every title write was throwing silently. The @traceable
+    decorator creates a LangSmith child run with these outputs
+    visible in the trace UI / runs API.
+    """
+    thread_id = (config.get("configurable") or {}).get("thread_id")
+    # url=None lets the SDK use its in-process ASGI transport when the
+    # call originates from inside a LangGraph server graph (which is
+    # always the case here). The old fallback to http://localhost:2024
+    # PREVENTED that path: it always forced an HTTP round-trip to a
+    # port that doesn't exist on the prod runtime container (it does
+    # locally because `langgraph dev` listens on 2024 — which is why
+    # this only broke in prod). LANGGRAPH_API_URL is only honoured
+    # when explicitly set, e.g. for cross-process callbacks.
+    sdk_url = os.environ.get("LANGGRAPH_API_URL")
+    if not isinstance(thread_id, str) or not thread_id:
+        return {}
+
+    try:
+        client = get_client(url=sdk_url)
+        thread = await client.threads.get(thread_id)
+        existing = (thread.get("metadata") or {}).get("title")
+        if isinstance(existing, str) and existing.strip():
+            return {}
+
+        # Find the first user message in the current state.
+        first_user = None
+        for m in state.get("messages", []):
+            type_attr = getattr(m, "type", None)
+            getter = getattr(m, "_getType", None)
+            msg_type = type_attr if type_attr else (getter() if callable(getter) else None)
+            if msg_type == "human":
+                content = getattr(m, "content", None)
+                if isinstance(content, str) and content.strip():
+                    first_user = content
+                    break
+        if not first_user:
+            return {}
+        if first_user.lstrip().startswith("{"):
+            return {}
+
+        llm = ChatOpenAI(model=_TITLE_MODEL, temperature=0)
+        response = await llm.ainvoke([
+            SystemMessage(content=_TITLE_PROMPT),
+            HumanMessage(content=first_user),
+        ])
+        title = (response.content or "").strip().strip('"').strip("'")[:80]
+        if not title:
+            return {}
+
+        await client.threads.update(
+            thread_id,
+            metadata={"title": title},
+        )
+        return {}
+    except Exception as e:  # noqa: BLE001 — title is a UX nicety; never block
+        # Don't break the run, but DO surface the failure. A bare swallow
+        # has hidden a prod bug where every title write was throwing
+        # silently. The @traceable decorator captures this return dict in
+        # the LangSmith run output (visible via /api/v1/runs/query) so we
+        # can diagnose without needing platform stdout access.
+        return {
+            "error_type": type(e).__name__,
+            "error_message": str(e),
+            "sdk_url": sdk_url,
+            "thread_id": thread_id,
+        }
+
+
+SYSTEM_PROMPT = (
+    "You are a helpful, concise assistant. "
+    "Format responses with markdown when useful (headings, lists, code blocks, tables). "
+    "When the user asks about specific Angular topics or technical questions, "
+    "use the `search_documents` tool to find authoritative information before answering. "
+    "Cite sources inline using Pandoc-style citation references with the "
+    "document `id` field as the refId, e.g. `[^ng-signals-overview]` or "
+    "`[^ng-control-flow]`. Each first-use of a document gets an auto-numbered "
+    "marker; subsequent references to the same document share the number. "
+    "Do not write `[1]` or `[1, 2]` — those are plain text and won't link to "
+    "the sources panel. "
+    "When the user describes a sensitive or destructive action (deleting "
+    "data, sending a customer email, modifying production state, etc.), "
+    "call `request_approval` with a clear `reason` BEFORE doing the action. "
+    "Do not assume permission. The human's response will tell you whether to "
+    "proceed, modify, or stop. "
+    "When the user asks for in-depth research on a focused topic (history, "
+    "motivation, comparison, deep-dive on something they want explained), "
+    "call the `research` tool to dispatch a subagent that focuses on that "
+    "topic. Pass the topic verbatim or as a concise rephrasing, and pass "
+    "`subagent_type=\"research\"` so the UI surfaces a subagent card while "
+    "the child runs. Use the subagent's returned summary to compose your "
+    "final answer. Do not call `research` for trivial chit-chat or simple "
+    "lookups — those are handled by `search_documents`. "
+    " "
+    "If the user asks to see / build / render / show / display a UI, "
+    "form, card, panel, button, picker, slider, table, list, or any "
+    "other interactive surface — INCLUDING phrases like 'build me X', "
+    "'render Y', 'show a Z', 'create a form for', 'make a card with' — "
+    "you MUST IMMEDIATELY dispatch the schema-generation tool bound "
+    "to the conversation. Exactly ONE such tool is bound per request: "
+    "either `render_a2ui_surface` or `generate_json_render_spec`. "
+    "Do NOT ask clarifying questions about platform, framework, fields, "
+    "validation, styling, or anything else. Do NOT describe the UI in "
+    "prose. Do NOT request more details from the user. The tool ITSELF "
+    "is responsible for filling in reasonable defaults from the user's "
+    "request. Pass the user's request VERBATIM as the `request` "
+    "argument. Your only job for UI-rendering requests is to route "
+    "them to the tool. After the tool returns its payload (a wire-"
+    "format string the chat composition renders directly), respond with "
+    "at most ONE short sentence acknowledging the dispatch — the user "
+    "sees the rendered surface, not your prose. Examples of prompts "
+    "that MUST dispatch the tool: 'build a feedback form', 'render a "
+    "settings card', 'show me a poll', 'make a contact form'. If the "
+    "user is having a casual conversation or asking factual questions, "
+    "do NOT dispatch the UI tool — only dispatch when they explicitly "
+    "ask for a UI / form / card / interactive surface."
+)
+
+# Reasoning-capable model prefixes. We only attach the ``reasoning``
+# parameter when the model name suggests reasoning support; setting it
+# on a non-reasoning model would be ignored anyway.
+REASONING_PREFIXES = ("gpt-5", "o1", "o3", "o4")
+
+
+def _is_reasoning_model(name: str) -> bool:
+    return any(name.startswith(p) for p in REASONING_PREFIXES)
+
+
+# Hardcoded corpus for the search_documents tool. Five Angular topics
+# that align with the demo's existing welcome suggestions. Deterministic;
+# no external API calls; no API keys required.
+DOCUMENTS = [
+    {
+        "id": "ng-signals-overview",
+        "title": "Signals — Angular guide",
+        "url": "https://angular.dev/guide/signals",
+        "snippet": "Signals are a reactivity primitive that lets you describe values that change over time without manual subscriptions.",
+    },
+    {
+        "id": "ng-signals-rxjs",
+        "title": "RxJS interop with signals",
+        "url": "https://angular.dev/guide/signals/rxjs-interop",
+        "snippet": "toSignal() and toObservable() bridge between RxJS Observables and signals.",
+    },
+    {
+        "id": "ng-control-flow",
+        "title": "Built-in control flow — @if, @for, @switch",
+        "url": "https://angular.dev/guide/templates/control-flow",
+        "snippet": "Native template control flow replaces structural directives like *ngIf and *ngFor with built-in syntax.",
+    },
+    {
+        "id": "ng-standalone",
+        "title": "Standalone components",
+        "url": "https://angular.dev/guide/components/importing",
+        "snippet": "Standalone components, directives, and pipes import their dependencies directly without NgModules.",
+    },
+    {
+        "id": "ng-zoneless",
+        "title": "Zoneless change detection",
+        "url": "https://angular.dev/guide/experimental/zoneless",
+        "snippet": "provideExperimentalZonelessChangeDetection lets Angular run without zone.js by tracking signals and async state directly.",
+    },
+]
+
+
+@tool
+def search_documents(query: str) -> str:
+    """Search the corpus for documents relevant to the query.
+
+    Returns a JSON list of hits, each with id, title, url, snippet.
+    Up to 4 hits are returned. If the query has no matches, returns
+    the first 3 documents as a fallback so the demo always has
+    something to cite.
+    """
+    q = (query or "").lower()
+    hits = [
+        d
+        for d in DOCUMENTS
+        if q in (d["title"] + " " + d["snippet"]).lower()
+    ]
+    if not hits:
+        hits = DOCUMENTS[:3]
+    return json.dumps(hits[:4])
+
+
+@tool
+def request_approval(reason: str) -> str:
+    """Pause and request the human's approval before performing a sensitive
+    or destructive action. Provide a clear reason — the human will see it.
+    Returns the human's decision verbatim; incorporate it into your next
+    step.
+    """
+    response = interrupt({"type": "approval_request", "reason": reason})
+    return f"Human response: {response}"
+
+
+# Research subagent — a small compiled child graph the parent dispatches
+# via the `research` @tool. Running it as an actual subgraph (vs. inline
+# logic) is what causes LangGraph to emit stream events under namespace
+# prefix `tools:<id>` for the child run, which is what the @threadplane/langgraph
+# SubagentTracker keys on to populate `agent.subagents()`.
+class ResearchState(TypedDict):
+    messages: Annotated[list, add_messages]
+    topic: Optional[str]
+
+
+async def research_node(state: ResearchState) -> dict:
+    """Single-node child graph: focus on the topic, return a short brief.
+
+    Uses gpt-5-mini directly (the parent's model selection does not
+    propagate into the subagent — the subagent is a focused contractor).
+    """
+    topic = state.get("topic") or ""
+    llm = ChatOpenAI(model="gpt-5-mini", streaming=True)
+    system = SystemMessage(content=(
+        "You are a focused research subagent. Given a topic, return a "
+        "concise factual summary (3-6 bullets). Do not ask the user "
+        "questions; the parent agent already gathered the topic."
+    ))
+    user = HumanMessage(content=f"Topic: {topic}")
+    response = await llm.ainvoke([system, user])
+    return {"messages": [response]}
+
+
+_research_builder = StateGraph(ResearchState)
+_research_builder.add_node("research_node", research_node)
+_research_builder.set_entry_point("research_node")
+_research_builder.add_edge("research_node", END)
+research_subgraph = _research_builder.compile()
+
+
+@tool
+async def research(topic: str, subagent_type: str = "research") -> str:
+    """Dispatch a research subagent to gather facts on a focused topic.
+    The subagent returns a concise summary; pass that summary back to
+    the user, citing it with the inline citation syntax if appropriate.
+
+    `subagent_type` is a free-form label the parent uses to identify the
+    subagent in the UI (the @threadplane/langgraph SubagentTracker keys on it
+    to populate `agent.subagents()` for the chat-subagents primitive).
+    Always pass a stable identifier like "research".
+    """
+    # subagent_type is intentionally accepted but unused server-side —
+    # it travels in the tool call args so the SubagentTracker can
+    # register the dispatch and surface a card while the child graph runs.
+    del subagent_type
+    result = await research_subgraph.ainvoke({"topic": topic, "messages": []})
+    msgs = result.get("messages") if isinstance(result, dict) else None
+    if not msgs:
+        return "(no research returned)"
+    last = msgs[-1]
+    content = getattr(last, "content", None) if not isinstance(last, dict) else last.get("content")
+    if isinstance(content, str):
+        return content
+    if isinstance(content, list):
+        # ChatOpenAI may return content as list of blocks; collect text.
+        parts = []
+        for b in content:
+            if isinstance(b, dict) and b.get("type") == "text":
+                parts.append(b.get("text", ""))
+        return "\n".join(parts) if parts else "(no research returned)"
+    return "(no research returned)"
+
+
+# Used by emit_generated_surface to prepend the chat composition's
+# content-classifier sentinel for A2UI mode. The classifier triggers
+# rendering when an AI message content begins with this prefix.
+A2UI_PREFIX = "---a2ui_JSON---"
+
+
+@tool
+async def generate_json_render_spec(request: str) -> str:
+    """Dispatch the json-render schema sub-agent to render a UI surface
+    as a json-render Spec ({root, elements, state}). Use this when the
+    user asks for UI/forms/cards and state.gen_ui_mode is 'json-render'.
+    Pass the user's request verbatim as the `request` argument."""
+    from src.schemas.json_render import JSON_RENDER_SCHEMA_PROMPT
+    llm = ChatOpenAI(model="gpt-5-mini", temperature=0)
+    response = await llm.ainvoke([
+        SystemMessage(content=JSON_RENDER_SCHEMA_PROMPT),
+        HumanMessage(content=request),
+    ])
+    return _as_text(response.content).strip()
+
+
+def _as_text(content) -> str:
+    """Normalize a langchain message content to a plain string. ChatOpenAI
+    may return content as either str or a list of typed blocks; this
+    pulls the text out of either."""
+    if isinstance(content, str):
+        return content
+    if isinstance(content, list):
+        return "\n".join(
+            b.get("text", "")
+            for b in content
+            if isinstance(b, dict) and b.get("type") == "text"
+        )
+    return ""
+
+
+class State(TypedDict):
+    messages: Annotated[list, add_messages]
+    model: Optional[str]
+    reasoning_effort: Optional[str]
+    gen_ui_mode: Optional[str]
+
+
+async def generate(state: State, config: RunnableConfig) -> dict:
+    model_name = state.get("model") or "gpt-5-mini"
+    kwargs = {"model": model_name, "streaming": True}
+    if _is_reasoning_model(model_name):
+        # Honor the client's effort selection when present; default to
+        # 'minimal' so first-token latency stays low for unconfigured callers.
+        effort = state.get("reasoning_effort") or "minimal"
+        # `summary='auto'` instructs the OpenAI Responses API to emit
+        # summary text inside the reasoning block (otherwise the block
+        # arrives with an empty `summary: []` and the chat UI has nothing
+        # to render). The adapter's `extractReasoning` reads either the
+        # legacy `block.text` field or the modern `block.summary[].text`.
+        kwargs["reasoning"] = {"effort": effort, "summary": "auto"}
+    # Pick the GenUI tool matching the user's palette dropdown. Only ONE
+    # is bound per request so the parent LLM has a single, unambiguous
+    # render tool to choose. ToolNode below is bound to BOTH so either
+    # side of the conditional resolves at execution time.
+    gen_ui_mode = state.get("gen_ui_mode") or "a2ui"
+    gen_ui_tool = (
+        render_a2ui_surface if gen_ui_mode == "a2ui"
+        else generate_json_render_spec
+    )
+    # Note on strict mode: OpenAI strict tool binding requires every nested
+    # object schema in the parameters tree to declare additionalProperties:
+    # false. The envelope shape carries list[dict] for components/contents
+    # (untyped inner objects), which strict mode rejects with a 400
+    # ('additionalProperties is required to be supplied and to be false').
+    # Typing the inner shapes would over-couple this example to the A2UI v1
+    # spec; instead we leave strict OFF and rely on the envelope-args
+    # normalizer (Python: src/streaming/envelope_normalizer.py; TS:
+    # libs/chat/src/lib/a2ui/envelope-normalizer.ts) to canonicalize the
+    # four observed argument shapes (envelopes / envelope / positional /
+    # flat). The spike showed 80-93% canonical even without strict.
+    llm = ChatOpenAI(**kwargs).bind_tools(
+        [search_documents, request_approval, research, gen_ui_tool],
+    )
+    # Append A2UI v1 schema to system prompt when in a2ui mode, so the parent
+    # LLM knows how to construct the envelopes directly.
+    system = SYSTEM_PROMPT
+    if gen_ui_mode == "a2ui":
+        system = SYSTEM_PROMPT + "\n\n--- A2UI v1 SCHEMA ---\n" + A2UI_V1_SCHEMA_PROMPT + (
+            "\n\nWhen rendering UI in a2ui mode, emit envelopes in this order: "
+            "surfaceUpdate FIRST, then beginRendering, then any dataModelUpdate "
+            "entries. This lets the client mount the surface as early as possible."
+        )
+    messages = [SystemMessage(content=system)] + state["messages"]
+    # When in a2ui mode, attach the partial-envelope sideband handler so
+    # the parent LLM's tool_call_chunks for render_a2ui_surface are
+    # dispatched as a2ui-partial custom events (consumed by the frontend
+    # partial-args bridge).
+    callbacks = []
+    if gen_ui_mode == "a2ui":
+        callbacks.append(A2uiPartialHandler(tool_name="render_a2ui_surface"))
+    response = await llm.ainvoke(messages, config={"callbacks": callbacks})
+    return {"messages": [response]}
+
+
+def should_continue(state: State) -> Literal["tools", "attach_citations"]:
+    """Conditional edge from generate: route to tools node when any
+    tool_call is present (GenUI tools, search, approval, research),
+    otherwise route to attach_citations terminal post-process."""
+    last = state["messages"][-1]
+    if isinstance(last, AIMessage) and last.tool_calls:
+        return "tools"
+    return "attach_citations"
+
+
+def after_tools(state: State) -> Literal["emit_generated_surface", "generate"]:
+    """Conditional edge from tools: if the most recent ToolMessage came
+    from a GenUI tool, route to emit_generated_surface (terminal
+    post-process that wraps the sub-LLM payload). Otherwise loop back
+    to generate so the parent LLM can incorporate the tool result."""
+    msgs = state["messages"]
+    # Find the most recent ToolMessage and its originating tool_call name
+    for m in reversed(msgs):
+        if isinstance(m, ToolMessage):
+            for prior in reversed(msgs):
+                if isinstance(prior, AIMessage) and prior.tool_calls:
+                    for tc in prior.tool_calls:
+                        if tc.get("id") == m.tool_call_id and tc.get("name") in (
+                            "render_a2ui_surface", "generate_json_render_spec",
+                        ):
+                            return "emit_generated_surface"
+                    break
+            break
+    return "generate"
+
+
+async def emit_generated_surface(state: State) -> dict:
+    """Post-process for GenUI tool dispatches. Reads the most recent
+    ToolMessage carrying the sub-LLM's wire-format payload, identifies
+    which protocol the AI dispatched (by tool_call name), wraps the
+    payload with the chat composition's content-classifier sentinel,
+    emits a fresh AIMessage carrying the wrapped content, and REMOVES
+    the AI tool-call message + ToolMessage from history so the chat UI
+    doesn't render the raw schema JSON dump alongside the surface."""
+    msgs = state["messages"]
+
+    # Find the most recent ToolMessage + its originating AI tool-call message
+    tool_msg = None
+    ai_tool_call_msg = None
+    tool_name = None
+    for m in reversed(msgs):
+        if isinstance(m, ToolMessage):
+            tool_msg = m
+            for prior in reversed(msgs):
+                if isinstance(prior, AIMessage) and prior.tool_calls:
+                    for tc in prior.tool_calls:
+                        if tc.get("id") == tool_msg.tool_call_id:
+                            tool_name = tc.get("name")
+                            ai_tool_call_msg = prior
+                            break
+                    if tool_name:
+                        break
+            break
+
+    if tool_msg is None or tool_name is None:
+        return {}
+
+    payload = tool_msg.content if isinstance(tool_msg.content, str) else ""
+    if not payload:
+        return {}
+
+    if tool_name == "render_a2ui_surface":
+        # Sub-LLM returns a JSON array of v1 envelopes. Convert to JSONL
+        # (one envelope per line) and prepend the classifier sentinel.
+        try:
+            arr = json.loads(payload)
+            if isinstance(arr, list):
+                jsonl = "\n".join(json.dumps(env) for env in arr)
+            else:
+                jsonl = payload
+        except json.JSONDecodeError:
+            # Sub-LLM may have leading/trailing whitespace or markdown
+            # fencing despite the prompt instructions. Try to strip.
+            stripped = payload.strip()
+            if stripped.startswith("```"):
+                lines = stripped.split("\n")
+                stripped = "\n".join(line for line in lines if not line.startswith("```"))
+            try:
+                arr = json.loads(stripped)
+                jsonl = "\n".join(json.dumps(env) for env in arr) if isinstance(arr, list) else stripped
+            except json.JSONDecodeError:
+                arr = None
+                jsonl = payload  # let the parser deal with malformed lines
+
+        # Reorder envelopes so beginRendering lands in position 2 (right
+        # after the first surfaceUpdate). The surface store gates surface
+        # materialization on beginRendering; emitting it early lets the
+        # frontend mount the (initially empty) surface and reveal per-
+        # component fallbacks while dataModelUpdate envelopes flow.
+        try:
+            if isinstance(arr, list):
+                surface_updates = [e for e in arr if isinstance(e, dict) and "surfaceUpdate" in e]
+                begin_renderings = [e for e in arr if isinstance(e, dict) and "beginRendering" in e]
+                data_updates = [e for e in arr if isinstance(e, dict) and "dataModelUpdate" in e]
+                others = [
+                    e for e in arr
+                    if isinstance(e, dict)
+                    and not ("surfaceUpdate" in e or "beginRendering" in e or "dataModelUpdate" in e)
+                ]
+                reordered = (
+                    surface_updates
+                    + (begin_renderings[:1] if begin_renderings else [])
+                    + data_updates
+                    + others
+                    + begin_renderings[1:]
+                )
+                jsonl = "\n".join(json.dumps(env) for env in reordered)
+        except (TypeError, AttributeError, NameError):
+            # arr may be unbound or unexpected shape — fall back to existing jsonl.
+            pass
+
+        wrapped = A2UI_PREFIX + "\n" + jsonl + "\n"
+    elif tool_name == "generate_json_render_spec":
+        # json-render: classifier detects content starting with `{`, no
+        # prefix needed. Strip whitespace and any markdown fencing the
+        # sub-LLM may have included.
+        stripped = payload.strip()
+        if stripped.startswith("```"):
+            lines = stripped.split("\n")
+            stripped = "\n".join(line for line in lines if not line.startswith("```"))
+            stripped = stripped.strip()
+        wrapped = stripped
+    else:
+        return {}
+
+    # In-place replace the ToolMessage with a tiny "rendered" placeholder
+    # (langgraph add_messages reducer matches by id and replaces). This
+    # collapses the chat-tool-calls result panel from a multi-KB schema
+    # dump to a single word. The AI tool-call message stays — its small
+    # tool-call card chrome is fine. We append the wrapped surface
+    # AIMessage as the final message; the chat composition's content
+    # classifier picks up the prefix and mounts <a2ui-surface> /
+    # <chat-generative-ui>.
+    # In-place replacement: return an AIMessage with the SAME id as the
+    # upstream tool-call AI. LangGraph's add_messages reducer matches by
+    # id and replaces, so the thread carries ONE AI message per GenUI
+    # turn (with both tool_calls AND the wrapped surface content)
+    # instead of two — the user sees a single bubble that transforms
+    # from skeleton to surface, not a skeleton bubble followed by a
+    # separate surface bubble.
+    out = []
+    placeholder_kwargs = {
+        "content": "rendered",
+        "tool_call_id": tool_msg.tool_call_id,
+    }
+    if getattr(tool_msg, "id", None):
+        placeholder_kwargs["id"] = tool_msg.id
+    out.append(ToolMessage(**placeholder_kwargs))
+    replacement_kwargs = {"content": wrapped}
+    if ai_tool_call_msg is not None:
+        if getattr(ai_tool_call_msg, "id", None):
+            replacement_kwargs["id"] = ai_tool_call_msg.id
+        replacement_kwargs["tool_calls"] = ai_tool_call_msg.tool_calls
+        replacement_kwargs["additional_kwargs"] = ai_tool_call_msg.additional_kwargs or {}
+        replacement_kwargs["response_metadata"] = ai_tool_call_msg.response_metadata or {}
+    out.append(AIMessage(**replacement_kwargs))
+    return {"messages": out}
+
+
+async def attach_citations(state: State) -> dict:
+    """Terminal post-process: walk back from the final AI message to
+    the most recent ToolMessage, parse its JSON content, and replace
+    the AI message with one carrying additional_kwargs.citations.
+
+    Returns an empty dict (no state update) when there is no preceding
+    ToolMessage to draw citations from. The AI message is left as-is
+    in that case — citations are an opt-in surface, not required.
+    """
+    msgs = state["messages"]
+    last = msgs[-1]
+    if not isinstance(last, AIMessage) or last.tool_calls:
+        return {}
+
+    citations = []
+    for m in reversed(msgs[:-1]):
+        if isinstance(m, ToolMessage):
+            try:
+                hits = json.loads(m.content) if isinstance(m.content, str) else []
+            except json.JSONDecodeError:
+                continue
+            if isinstance(hits, list):
+                for i, h in enumerate(hits):
+                    if not isinstance(h, dict):
+                        continue
+                    # Only treat dicts that look like citation hits — must
+                    # carry at least one of title/url/snippet. Skips unrelated
+                    # JSON arrays (e.g. A2UI envelope arrays) that the
+                    # search_documents tool would never produce.
+                    if not any(k in h for k in ("title", "url", "snippet")):
+                        continue
+                    citations.append(
+                        {
+                            "id": h.get("id") or f"c{i+1}",
+                            "index": i + 1,
+                            "title": h.get("title"),
+                            "url": h.get("url"),
+                            "snippet": h.get("snippet"),
+                        }
+                    )
+            break  # only the most recent ToolMessage batch
+        elif isinstance(m, AIMessage):
+            break
+
+    if not citations:
+        return {}
+
+    new_kwargs = dict(getattr(last, "additional_kwargs", {}) or {})
+    new_kwargs["citations"] = citations
+    return {
+        "messages": [
+            RemoveMessage(id=last.id),
+            AIMessage(
+                id=last.id,
+                content=last.content,
+                additional_kwargs=new_kwargs,
+                tool_calls=getattr(last, "tool_calls", []) or [],
+                response_metadata=getattr(last, "response_metadata", {}) or {},
+            ),
+        ]
+    }
+
+
+_builder = StateGraph(State)
+_builder.add_node("generate", generate)
+_builder.add_node("tools", ToolNode([
+    search_documents, request_approval, research,
+    render_a2ui_surface, generate_json_render_spec,
+]))
+_builder.add_node("emit_generated_surface", emit_generated_surface)
+_builder.add_node("attach_citations", attach_citations)
+_builder.add_node("generate_title", generate_title)
+_builder.set_entry_point("generate")
+_builder.add_conditional_edges(
+    "generate",
+    should_continue,
+    {
+        "tools": "tools",
+        "attach_citations": "attach_citations",
+    },
+)
+_builder.add_conditional_edges(
+    "tools",
+    after_tools,
+    {
+        "emit_generated_surface": "emit_generated_surface",
+        "generate": "generate",
+    },
+)
+_builder.add_edge("emit_generated_surface", "generate_title")
+_builder.add_edge("attach_citations", "generate_title")
+_builder.add_edge("generate_title", END)
+
+# LangGraph API manages persistence for the deployed graph; keep the
+# exported graph free of a custom checkpointer.
+graph = _builder.compile()
diff --git a/examples/ag-ui/python/src/schemas/__init__.py b/examples/ag-ui/python/src/schemas/__init__.py
new file mode 100644
index 000000000..69cf75749
--- /dev/null
+++ b/examples/ag-ui/python/src/schemas/__init__.py
@@ -0,0 +1,2 @@
+# SPDX-License-Identifier: MIT
+"""Schema-prompt modules for the GenUI sub-LLM tools."""
diff --git a/examples/ag-ui/python/src/schemas/a2ui_v1.py b/examples/ag-ui/python/src/schemas/a2ui_v1.py
new file mode 100644
index 000000000..e40f5efba
--- /dev/null
+++ b/examples/ag-ui/python/src/schemas/a2ui_v1.py
@@ -0,0 +1,828 @@
+# SPDX-License-Identifier: MIT
+"""A2UI v1 protocol schema documentation, used as the system prompt for
+the `generate_a2ui_schema` sub-LLM tool. Sourced verbatim from the
+L4 production reference (canonical Google A2UI v1 schema)."""
+
+A2UI_V1_SCHEMA_PROMPT = """
+Generate A2UI JSON.
+
+## A2UI Protocol Instructions
+
+A2UI (Agent to UI) is a protocol for rendering rich UI surfaces from agent responses.
+
+To render a surface, you MUST send ALL messages in a SINGLE tool call, in this order:
+1. **surfaceUpdate** - Define all UI components (REQUIRED)
+2. **dataModelUpdate** - Set any data values (OPTIONAL)
+3. **beginRendering** - Signal the client to start rendering (REQUIRED)
+
+### Minimal Working Example
+
+Here is the simplest possible A2UI surface - a button:
+
+```json
+[
+  {
+    "surfaceUpdate": {
+      "surfaceId": "my-surface",
+      "components": [
+        {
+          "id": "root",
+          "component": {
+            "Button": {
+              "child": "btn-text",
+              "action": { "name": "button_clicked" }
+            }
+          }
+        },
+        {
+          "id": "btn-text",
+          "component": {
+            "Text": { "text": { "literalString": "Click Me" } }
+          }
+        }
+      ]
+    }
+  },
+  {
+    "beginRendering": {
+      "surfaceId": "my-surface",
+      "root": "root"
+    }
+  }
+]
+```
+
+## JSON Schema Reference
+{
+  "type": "array",
+  "items": {
+    "title": "A2UI Message Schema",
+    "description": "Describes a JSON payload for an A2UI (Agent to UI) message, which is used to dynamically construct and update user interfaces. A message MUST contain exactly ONE of the action properties: 'beginRendering', 'surfaceUpdate', 'dataModelUpdate', or 'deleteSurface'.",
+    "type": "object",
+  "properties": {
+    "beginRendering": {
+      "type": "object",
+      "description": "Signals the client to begin rendering a surface with a root component and specific styles.",
+      "properties": {
+        "surfaceId": {
+          "type": "string",
+          "description": "The unique identifier for the UI surface to be rendered."
+        },
+        "root": {
+          "type": "string",
+          "description": "The ID of the root component to render."
+        },
+        "styles": {
+          "type": "object",
+          "description": "Styling information for the UI.",
+          "properties": {
+            "font": {
+              "type": "string",
+              "description": "The primary font for the UI."
+            },
+            "primaryColor": {
+              "type": "string",
+              "description": "The primary UI color as a hexadecimal code (e.g., '#00BFFF').",
+              "pattern": "^#[0-9a-fA-F]{6}$"
+            }
+          }
+        }
+      },
+      "required": ["root", "surfaceId"]
+    },
+    "surfaceUpdate": {
+      "type": "object",
+      "description": "Updates a surface with a new set of components.",
+      "properties": {
+        "surfaceId": {
+          "type": "string",
+          "description": "The unique identifier for the UI surface to be updated. If you are adding a new surface this *must* be a new, unique identified that has never been used for any existing surfaces shown."
+        },
+        "components": {
+          "type": "array",
+          "description": "A list containing all UI components for the surface.",
+          "minItems": 1,
+          "items": {
+            "type": "object",
+            "description": "Represents a *single* component in a UI widget tree. This component could be one of many supported types.",
+            "properties": {
+              "id": {
+                "type": "string",
+                "description": "The unique identifier for this component."
+              },
+              "weight": {
+                "type": "number",
+                "description": "The relative weight of this component within a Row or Column. This corresponds to the CSS 'flex-grow' property. Note: this may ONLY be set when the component is a direct descendant of a Row or Column."
+              },
+              "component": {
+                "type": "object",
+                "description": "A wrapper object that MUST contain exactly one key, which is the name of the component type (e.g., 'Heading'). The value is an object containing the properties for that specific component.",
+                "properties": {
+                  "Text": {
+                    "type": "object",
+                    "properties": {
+                      "text": {
+                        "type": "object",
+                        "description": "The text content to display. This can be a literal string or a reference to a value in the data model ('path', e.g., '/doc/title'). While simple Markdown formatting is supported (i.e. without HTML, images, or links), utilizing dedicated UI components is generally preferred for a richer and more structured presentation.",
+                        "properties": {
+                          "literalString": {
+                            "type": "string"
+                          },
+                          "path": {
+                            "type": "string"
+                          }
+                        }
+                      },
+                      "usageHint": {
+                        "type": "string",
+                        "description": "A hint for the base text style. One of:\\n- `h1`: Largest heading.\\n- `h2`: Second largest heading.\\n- `h3`: Third largest heading.\\n- `h4`: Fourth largest heading.\\n- `h5`: Fifth largest heading.\\n- `caption`: Small text for captions.\\n- `body`: Standard body text.",
+                        "enum": [
+                          "h1",
+                          "h2",
+                          "h3",
+                          "h4",
+                          "h5",
+                          "caption",
+                          "body"
+                        ]
+                      }
+                    },
+                    "required": ["text"]
+                  },
+                  "Image": {
+                    "type": "object",
+                    "properties": {
+                      "url": {
+                        "type": "object",
+                        "description": "The URL of the image to display. This can be a literal string ('literal') or a reference to a value in the data model ('path', e.g. '/thumbnail/url').",
+                        "properties": {
+                          "literalString": {
+                            "type": "string"
+                          },
+                          "path": {
+                            "type": "string"
+                          }
+                        }
+                      },
+                      "fit": {
+                        "type": "string",
+                        "description": "Specifies how the image should be resized to fit its container. This corresponds to the CSS 'object-fit' property.",
+                        "enum": [
+                          "contain",
+                          "cover",
+                          "fill",
+                          "none",
+                          "scale-down"
+                        ]
+                      },
+                      "usageHint": {
+                        "type": "string",
+                        "description": "A hint for the image size and style. One of:\\n- `icon`: Small square icon.\\n- `avatar`: Circular avatar image.\\n- `smallFeature`: Small feature image.\\n- `mediumFeature`: Medium feature image.\\n- `largeFeature`: Large feature image.\\n- `header`: Full-width, full bleed, header image.",
+                        "enum": [
+                          "icon",
+                          "avatar",
+                          "smallFeature",
+                          "mediumFeature",
+                          "largeFeature",
+                          "header"
+                        ]
+                      }
+                    },
+                    "required": ["url"]
+                  },
+                  "Icon": {
+                    "type": "object",
+                    "properties": {
+                      "name": {
+                        "type": "object",
+                        "description": "The name of the icon to display. This can be a literal string or a reference to a value in the data model ('path', e.g. '/form/submit').",
+                        "properties": {
+                          "literalString": {
+                            "type": "string",
+                            "enum": [
+                              "accountCircle",
+                              "add",
+                              "arrowBack",
+                              "arrowForward",
+                              "attachFile",
+                              "calendarToday",
+                              "call",
+                              "camera",
+                              "check",
+                              "close",
+                              "delete",
+                              "download",
+                              "edit",
+                              "event",
+                              "error",
+                              "favorite",
+                              "favoriteOff",
+                              "folder",
+                              "help",
+                              "home",
+                              "info",
+                              "locationOn",
+                              "lock",
+                              "lockOpen",
+                              "mail",
+                              "menu",
+                              "moreVert",
+                              "moreHoriz",
+                              "notificationsOff",
+                              "notifications",
+                              "payment",
+                              "person",
+                              "phone",
+                              "photo",
+                              "print",
+                              "refresh",
+                              "search",
+                              "send",
+                              "settings",
+                              "share",
+                              "shoppingCart",
+                              "star",
+                              "starHalf",
+                              "starOff",
+                              "upload",
+                              "visibility",
+                              "visibilityOff",
+                              "warning"
+                            ]
+                          },
+                          "path": {
+                            "type": "string"
+                          }
+                        }
+                      }
+                    },
+                    "required": ["name"]
+                  },
+                  "Video": {
+                    "type": "object",
+                    "properties": {
+                      "url": {
+                        "type": "object",
+                        "description": "The URL of the video to display. This can be a literal string or a reference to a value in the data model ('path', e.g. '/video/url').",
+                        "properties": {
+                          "literalString": {
+                            "type": "string"
+                          },
+                          "path": {
+                            "type": "string"
+                          }
+                        }
+                      }
+                    },
+                    "required": ["url"]
+                  },
+                  "AudioPlayer": {
+                    "type": "object",
+                    "properties": {
+                      "url": {
+                        "type": "object",
+                        "description": "The URL of the audio to be played. This can be a literal string ('literal') or a reference to a value in the data model ('path', e.g. '/song/url').",
+                        "properties": {
+                          "literalString": {
+                            "type": "string"
+                          },
+                          "path": {
+                            "type": "string"
+                          }
+                        }
+                      },
+                      "description": {
+                        "type": "object",
+                        "description": "A description of the audio, such as a title or summary. This can be a literal string or a reference to a value in the data model ('path', e.g. '/song/title').",
+                        "properties": {
+                          "literalString": {
+                            "type": "string"
+                          },
+                          "path": {
+                            "type": "string"
+                          }
+                        }
+                      }
+                    },
+                    "required": ["url"]
+                  },
+                  "Row": {
+                    "type": "object",
+                    "properties": {
+                      "children": {
+                        "type": "object",
+                        "description": "Defines the children. Use 'explicitList' for a fixed set of children, or 'template' to generate children from a data list.",
+                        "properties": {
+                          "explicitList": {
+                            "type": "array",
+                            "items": {
+                              "type": "string"
+                            }
+                          },
+                          "template": {
+                            "type": "object",
+                            "description": "A template for generating a dynamic list of children from a data model list. `componentId` is the component to use as a template, and `dataBinding` is the path to the map of components in the data model. Values in the map will define the list of children.",
+                            "properties": {
+                              "componentId": {
+                                "type": "string"
+                              },
+                              "dataBinding": {
+                                "type": "string"
+                              }
+                            },
+                            "required": ["componentId", "dataBinding"]
+                          }
+                        }
+                      },
+                      "distribution": {
+                        "type": "string",
+                        "description": "Defines the arrangement of children along the main axis (horizontally). This corresponds to the CSS 'justify-content' property.",
+                        "enum": [
+                          "center",
+                          "end",
+                          "spaceAround",
+                          "spaceBetween",
+                          "spaceEvenly",
+                          "start"
+                        ]
+                      },
+                      "alignment": {
+                        "type": "string",
+                        "description": "Defines the alignment of children along the cross axis (vertically). This corresponds to the CSS 'align-items' property.",
+                        "enum": ["start", "center", "end", "stretch"]
+                      }
+                    },
+                    "required": ["children"]
+                  },
+                  "Column": {
+                    "type": "object",
+                    "properties": {
+                      "children": {
+                        "type": "object",
+                        "description": "Defines the children. Use 'explicitList' for a fixed set of children, or 'template' to generate children from a data list.",
+                        "properties": {
+                          "explicitList": {
+                            "type": "array",
+                            "items": {
+                              "type": "string"
+                            }
+                          },
+                          "template": {
+                            "type": "object",
+                            "description": "A template for generating a dynamic list of children from a data model list. `componentId` is the component to use as a template, and `dataBinding` is the path to the map of components in the data model. Values in the map will define the list of children.",
+                            "properties": {
+                              "componentId": {
+                                "type": "string"
+                              },
+                              "dataBinding": {
+                                "type": "string"
+                              }
+                            },
+                            "required": ["componentId", "dataBinding"]
+                          }
+                        }
+                      },
+                      "distribution": {
+                        "type": "string",
+                        "description": "Defines the arrangement of children along the main axis (vertically). This corresponds to the CSS 'justify-content' property.",
+                        "enum": [
+                          "start",
+                          "center",
+                          "end",
+                          "spaceBetween",
+                          "spaceAround",
+                          "spaceEvenly"
+                        ]
+                      },
+                      "alignment": {
+                        "type": "string",
+                        "description": "Defines the alignment of children along the cross axis (horizontally). This corresponds to the CSS 'align-items' property.",
+                        "enum": ["center", "end", "start", "stretch"]
+                      }
+                    },
+                    "required": ["children"]
+                  },
+                  "List": {
+                    "type": "object",
+                    "properties": {
+                      "children": {
+                        "type": "object",
+                        "description": "Defines the children. Use 'explicitList' for a fixed set of children, or 'template' to generate children from a data list.",
+                        "properties": {
+                          "explicitList": {
+                            "type": "array",
+                            "items": {
+                              "type": "string"
+                            }
+                          },
+                          "template": {
+                            "type": "object",
+                            "description": "A template for generating a dynamic list of children from a data model list. `componentId` is the component to use as a template, and `dataBinding` is the path to the map of components in the data model. Values in the map will define the list of children.",
+                            "properties": {
+                              "componentId": {
+                                "type": "string"
+                              },
+                              "dataBinding": {
+                                "type": "string"
+                              }
+                            },
+                            "required": ["componentId", "dataBinding"]
+                          }
+                        }
+                      },
+                      "direction": {
+                        "type": "string",
+                        "description": "The direction in which the list items are laid out.",
+                        "enum": ["vertical", "horizontal"]
+                      },
+                      "alignment": {
+                        "type": "string",
+                        "description": "Defines the alignment of children along the cross axis.",
+                        "enum": ["start", "center", "end", "stretch"]
+                      }
+                    },
+                    "required": ["children"]
+                  },
+                  "Card": {
+                    "type": "object",
+                    "properties": {
+                      "child": {
+                        "type": "string",
+                        "description": "The ID of the component to be rendered inside the card."
+                      }
+                    },
+                    "required": ["child"]
+                  },
+                  "Tabs": {
+                    "type": "object",
+                    "properties": {
+                      "tabItems": {
+                        "type": "array",
+                        "description": "An array of objects, where each object defines a tab with a title and a child component.",
+                        "items": {
+                          "type": "object",
+                          "properties": {
+                            "title": {
+                              "type": "object",
+                              "description": "The tab title. Defines the value as either a literal value or a path to data model value (e.g. '/options/title').",
+                              "properties": {
+                                "literalString": {
+                                  "type": "string"
+                                },
+                                "path": {
+                                  "type": "string"
+                                }
+                              }
+                            },
+                            "child": {
+                              "type": "string"
+                            }
+                          },
+                          "required": ["title", "child"]
+                        }
+                      }
+                    },
+                    "required": ["tabItems"]
+                  },
+                  "Divider": {
+                    "type": "object",
+                    "properties": {
+                      "axis": {
+                        "type": "string",
+                        "description": "The orientation of the divider.",
+                        "enum": ["horizontal", "vertical"]
+                      }
+                    }
+                  },
+                  "Modal": {
+                    "type": "object",
+                    "properties": {
+                      "entryPointChild": {
+                        "type": "string",
+                        "description": "The ID of the component that opens the modal when interacted with (e.g., a button)."
+                      },
+                      "contentChild": {
+                        "type": "string",
+                        "description": "The ID of the component to be displayed inside the modal."
+                      }
+                    },
+                    "required": ["entryPointChild", "contentChild"]
+                  },
+                  "Button": {
+                    "type": "object",
+                    "properties": {
+                      "child": {
+                        "type": "string",
+                        "description": "The ID of the component to display in the button, typically a Text component."
+                      },
+                      "primary": {
+                        "type": "boolean",
+                        "description": "Indicates if this button should be styled as the primary action."
+                      },
+                      "action": {
+                        "type": "object",
+                        "description": "The client-side action to be dispatched when the button is clicked. It includes the action's name and an optional context payload.",
+                        "properties": {
+                          "name": {
+                            "type": "string"
+                          },
+                          "context": {
+                            "type": "array",
+                            "items": {
+                              "type": "object",
+                              "properties": {
+                                "key": {
+                                  "type": "string"
+                                },
+                                "value": {
+                                  "type": "object",
+                                  "description": "Defines the value to be included in the context as either a literal value or a path to a data model value (e.g. '/user/name').",
+                                  "properties": {
+                                    "path": {
+                                      "type": "string"
+                                    },
+                                    "literalString": {
+                                      "type": "string"
+                                    },
+                                    "literalNumber": {
+                                      "type": "number"
+                                    },
+                                    "literalBoolean": {
+                                      "type": "boolean"
+                                    }
+                                  }
+                                }
+                              },
+                              "required": ["key", "value"]
+                            }
+                          }
+                        },
+                        "required": ["name"]
+                      }
+                    },
+                    "required": ["child", "action"]
+                  },
+                  "CheckBox": {
+                    "type": "object",
+                    "properties": {
+                      "label": {
+                        "type": "object",
+                        "description": "The text to display next to the checkbox. Defines the value as either a literal value or a path to data model ('path', e.g. '/option/label').",
+                        "properties": {
+                          "literalString": {
+                            "type": "string"
+                          },
+                          "path": {
+                            "type": "string"
+                          }
+                        }
+                      },
+                      "value": {
+                        "type": "object",
+                        "description": "The current state of the checkbox (true for checked, false for unchecked). This can be a literal boolean ('literalBoolean') or a reference to a value in the data model ('path', e.g. '/filter/open').",
+                        "properties": {
+                          "literalBoolean": {
+                            "type": "boolean"
+                          },
+                          "path": {
+                            "type": "string"
+                          }
+                        }
+                      }
+                    },
+                    "required": ["label", "value"]
+                  },
+                  "TextField": {
+                    "type": "object",
+                    "properties": {
+                      "label": {
+                        "type": "object",
+                        "description": "The text label for the input field. This can be a literal string or a reference to a value in the data model ('path, e.g. '/user/name').",
+                        "properties": {
+                          "literalString": {
+                            "type": "string"
+                          },
+                          "path": {
+                            "type": "string"
+                          }
+                        }
+                      },
+                      "text": {
+                        "type": "object",
+                        "description": "The value of the text field. This can be a literal string or a reference to a value in the data model ('path', e.g. '/user/name').",
+                        "properties": {
+                          "literalString": {
+                            "type": "string"
+                          },
+                          "path": {
+                            "type": "string"
+                          }
+                        }
+                      },
+                      "textFieldType": {
+                        "type": "string",
+                        "description": "The type of input field to display.",
+                        "enum": [
+                          "date",
+                          "longText",
+                          "number",
+                          "shortText",
+                          "obscured"
+                        ]
+                      },
+                      "validationRegexp": {
+                        "type": "string",
+                        "description": "A regular expression used for client-side validation of the input."
+                      }
+                    },
+                    "required": ["label"]
+                  },
+                  "DateTimeInput": {
+                    "type": "object",
+                    "properties": {
+                      "value": {
+                        "type": "object",
+                        "description": "The selected date and/or time value in ISO 8601 format. This can be a literal string ('literalString') or a reference to a value in the data model ('path', e.g. '/user/dob').",
+                        "properties": {
+                          "literalString": {
+                            "type": "string"
+                          },
+                          "path": {
+                            "type": "string"
+                          }
+                        }
+                      },
+                      "enableDate": {
+                        "type": "boolean",
+                        "description": "If true, allows the user to select a date."
+                      },
+                      "enableTime": {
+                        "type": "boolean",
+                        "description": "If true, allows the user to select a time."
+                      }
+                    },
+                    "required": ["value"]
+                  },
+                  "MultipleChoice": {
+                    "type": "object",
+                    "properties": {
+                      "selections": {
+                        "type": "object",
+                        "description": "The currently selected values for the component. This can be a literal array of strings or a path to an array in the data model('path', e.g. '/hotel/options').",
+                        "properties": {
+                          "literalArray": {
+                            "type": "array",
+                            "items": {
+                              "type": "string"
+                            }
+                          },
+                          "path": {
+                            "type": "string"
+                          }
+                        }
+                      },
+                      "options": {
+                        "type": "array",
+                        "description": "An array of available options for the user to choose from.",
+                        "items": {
+                          "type": "object",
+                          "properties": {
+                            "label": {
+                              "type": "object",
+                              "description": "The text to display for this option. This can be a literal string or a reference to a value in the data model (e.g. '/option/label').",
+                              "properties": {
+                                "literalString": {
+                                  "type": "string"
+                                },
+                                "path": {
+                                  "type": "string"
+                                }
+                              }
+                            },
+                            "value": {
+                              "type": "string",
+                              "description": "The value to be associated with this option when selected."
+                            }
+                          },
+                          "required": ["label", "value"]
+                        }
+                      },
+                      "maxAllowedSelections": {
+                        "type": "integer",
+                        "description": "The maximum number of options that the user is allowed to select."
+                      }
+                    },
+                    "required": ["selections", "options"]
+                  },
+                  "Slider": {
+                    "type": "object",
+                    "properties": {
+                      "value": {
+                        "type": "object",
+                        "description": "The current value of the slider. This can be a literal number ('literalNumber') or a reference to a value in the data model ('path', e.g. '/restaurant/cost').",
+                        "properties": {
+                          "literalNumber": {
+                            "type": "number"
+                          },
+                          "path": {
+                            "type": "string"
+                          }
+                        }
+                      },
+                      "minValue": {
+                        "type": "number",
+                        "description": "The minimum value of the slider."
+                      },
+                      "maxValue": {
+                        "type": "number",
+                        "description": "The maximum value of the slider."
+                      }
+                    },
+                    "required": ["value"]
+                  }
+                }
+              }
+            },
+            "required": ["id", "component"]
+          }
+        }
+      },
+      "required": ["surfaceId", "components"]
+    },
+    "dataModelUpdate": {
+      "type": "object",
+      "description": "Updates the data model for a surface.",
+      "properties": {
+        "surfaceId": {
+          "type": "string",
+          "description": "The unique identifier for the UI surface this data model update applies to."
+        },
+        "path": {
+          "type": "string",
+          "description": "An optional path to a location within the data model (e.g., '/user/name'). If omitted, or set to '/', the entire data model will be replaced."
+        },
+        "contents": {
+          "type": "array",
+          "description": "An array of data entries. Each entry must contain a 'key' and exactly one corresponding typed 'value*' property.",
+          "items": {
+            "type": "object",
+            "description": "A single data entry. Exactly one 'value*' property should be provided alongside the key.",
+            "properties": {
+              "key": {
+                "type": "string",
+                "description": "The key for this data entry."
+              },
+              "valueString": {
+                "type": "string"
+              },
+              "valueNumber": {
+                "type": "number"
+              },
+              "valueBoolean": {
+                "type": "boolean"
+              },
+              "valueMap": {
+                "description": "Represents a map as an adjacency list.",
+                "type": "array",
+                "items": {
+                  "type": "object",
+                  "description": "One entry in the map. Exactly one 'value*' property should be provided alongside the key.",
+                  "properties": {
+                    "key": {
+                      "type": "string"
+                    },
+                    "valueString": {
+                      "type": "string"
+                    },
+                    "valueNumber": {
+                      "type": "number"
+                    },
+                    "valueBoolean": {
+                      "type": "boolean"
+                    }
+                  },
+                  "required": ["key"]
+                }
+              }
+            },
+            "required": ["key"]
+          }
+        }
+      },
+      "required": ["contents", "surfaceId"]
+    },
+    "deleteSurface": {
+      "type": "object",
+      "description": "Signals the client to delete the surface identified by 'surfaceId'.",
+      "properties": {
+        "surfaceId": {
+          "type": "string",
+          "description": "The unique identifier for the UI surface to be deleted."
+        }
+      },
+      "required": ["surfaceId"]
+    }
+  }
+  }
+}
+""".strip()
diff --git a/examples/ag-ui/python/src/schemas/json_render.py b/examples/ag-ui/python/src/schemas/json_render.py
new file mode 100644
index 000000000..57ec6dab0
--- /dev/null
+++ b/examples/ag-ui/python/src/schemas/json_render.py
@@ -0,0 +1,89 @@
+# SPDX-License-Identifier: MIT
+"""json-render protocol schema documentation, used as the system prompt
+for the `generate_json_render_spec` sub-LLM tool. Targets the
+@json-render/core Spec shape: { root, elements, state }."""
+
+JSON_RENDER_SCHEMA_PROMPT = """
+Generate a json-render Spec.
+
+## json-render Protocol Instructions
+
+json-render renders a UI from a single JSON object describing a flat
+component tree. Output ONE JSON object, no array, no prefix, no
+markdown fences. The chat client detects the leading `{` and routes
+the message to `<chat-generative-ui>`.
+
+The Spec shape is:
+
+```json
+{
+  "root": "<id of the root element>",
+  "elements": {
+    "<id1>": { "type": "<ComponentName>", "props": { ... }, "children": ["<childId>", ...], "on": { "click": { "action": "<name>", "params": {...} } } },
+    "<id2>": { ... }
+  },
+  "state": {
+    "<key>": "<initial value>"
+  }
+}
+```
+
+Rules:
+- `root` is the id of the entry-point element. The renderer mounts it first.
+- `elements` is a flat map of element id → element definition. Children are referenced by id, not nested.
+- `props` carries plain literal values (strings, numbers, booleans, arrays, objects). Components whose props bind to state use a special `statePath` field: `props: { value: { statePath: "/name" } }`.
+- `children` is an array of element ids (in render order).
+- `on` maps DOM event names to action descriptors. Most components only emit `click`. The `action` string is a free-form intent name; `params` is a flat object passed to the handler.
+- `state` is the initial state model. Keys are paths (e.g. `name`, `email`); values are initial values.
+
+## Component Catalog (matches @threadplane/chat's a2uiBasicCatalog)
+
+The renderer consumes the same component catalog as A2UI, so component
+names match: `Card`, `Column`, `Row`, `List`, `Tabs`, `Modal`,
+`Divider`, `Button`, `CheckBox`, `TextField`, `DateTimeInput`,
+`MultipleChoice`, `Slider`, `Text`, `Image`, `Icon`, `Video`,
+`AudioPlayer`.
+
+Common props per component:
+- `Card`: no props (children is single id wrapped in array)
+- `Column` / `Row`: `{ gap?: 'small'|'medium'|'large', alignment?: 'start'|'center'|'end'|'stretch' }`
+- `Text`: `{ text: string, usageHint?: 'h1'|'h2'|'h3'|'h4'|'h5'|'caption'|'body' }`
+- `TextField`: `{ label: string, text: string | { statePath: '/path' }, placeholder?: string, textFieldType?: 'shortText'|'longText'|'number'|'date'|'obscured', validationRegexp?: string }`
+- `MultipleChoice`: `{ label: string, options: [{ label: string, value: string }, ...], selections: string[] | { statePath: '/path' }, maxAllowedSelections?: number }`
+- `CheckBox`: `{ label: string, value: boolean | { statePath: '/path' } }`
+- `Slider`: `{ label: string, value: number | { statePath: '/path' }, minValue: number, maxValue: number }`
+- `Button`: `{ label: string, primary?: boolean }` plus `on.click.action` for the action name
+- `DateTimeInput`: `{ label: string, value: string | { statePath: '/path' }, enableDate?: boolean, enableTime?: boolean }`
+- `Image` / `Video` / `AudioPlayer`: `{ url: string }` plus `Image.fit?: 'contain'|'cover'|'fill'|'none'|'scale-down'`, `Image.usageHint?: 'icon'|'avatar'|'smallFeature'|'mediumFeature'|'largeFeature'|'header'`
+- `Icon`: `{ icon: string, size?: number }`
+- `Divider`: `{ direction?: 'horizontal'|'vertical' }`
+- `Tabs`: special — uses `tabTitles: string[]` and one child id per tab in `children`
+- `Modal`: special — `children: [triggerId, contentId]` (entry point + content)
+
+## Minimal Working Example
+
+A "Quick feedback" form:
+
+```json
+{
+  "root": "card",
+  "elements": {
+    "card": { "type": "Card", "children": ["body"] },
+    "body": { "type": "Column", "props": { "gap": "medium" }, "children": ["title", "name", "rating", "submit"] },
+    "title": { "type": "Text", "props": { "text": "Quick feedback", "usageHint": "h3" } },
+    "name": { "type": "TextField", "props": { "label": "Your name", "text": { "statePath": "/name" }, "textFieldType": "shortText" } },
+    "rating": { "type": "MultipleChoice", "props": { "label": "Rating", "options": [
+      { "label": "1", "value": "1" }, { "label": "2", "value": "2" }, { "label": "3", "value": "3" }, { "label": "4", "value": "4" }, { "label": "5", "value": "5" }
+    ], "selections": { "statePath": "/rating" }, "maxAllowedSelections": 1 } },
+    "submit": { "type": "Button", "props": { "label": "Submit feedback", "primary": true }, "on": { "click": { "action": "feedbackSubmit", "params": { "surface": "feedback" } } } }
+  },
+  "state": { "name": "", "rating": "5" }
+}
+```
+
+## Output Requirements
+
+Return ONLY the JSON object. No prose. No markdown code fence. The first
+character of your response MUST be `{`. The chat client's content
+classifier detects this and routes the message to render.
+""".strip()
diff --git a/examples/ag-ui/python/src/server.py b/examples/ag-ui/python/src/server.py
new file mode 100644
index 000000000..6607e072e
--- /dev/null
+++ b/examples/ag-ui/python/src/server.py
@@ -0,0 +1,44 @@
+# SPDX-License-Identifier: MIT
+"""Standalone AG-UI server for the examples/ag-ui demo.
+
+Wraps the (transport-agnostic) chat graph with ag-ui-langgraph and serves it
+over an AG-UI FastAPI endpoint at /agent. Mirrors the cockpit ag-ui pattern.
+
+Auth is OPTIONAL for clone-and-run: the X-Internal-Token check is enforced
+only when AG_UI_INTERNAL_TOKEN is set (production), so `uvicorn src.server:app`
+works locally with no env beyond OPENAI_API_KEY.
+"""
+import os
+from fastapi import FastAPI, Request
+from fastapi.responses import JSONResponse
+from langgraph.checkpoint.memory import MemorySaver
+from ag_ui_langgraph import add_langgraph_fastapi_endpoint, LangGraphAgent
+
+from .graph import _builder
+
+# The exported graph is checkpointer-free for LangGraph Platform (which manages
+# persistence). The standalone ag-ui-langgraph endpoint reads graph state via
+# aget_state, which requires a checkpointer — so compile a local copy with an
+# in-process MemorySaver. Mirrors the cockpit/ag-ui graphs.
+graph = _builder.compile(checkpointer=MemorySaver())
+
+AG_UI_INTERNAL_TOKEN = os.environ.get("AG_UI_INTERNAL_TOKEN")
+
+app = FastAPI(title="examples-ag-ui")
+
+
+@app.middleware("http")
+async def require_internal_token(request: Request, call_next):
+    if request.url.path == "/ok" or not AG_UI_INTERNAL_TOKEN:
+        return await call_next(request)
+    if request.headers.get("x-internal-token") != AG_UI_INTERNAL_TOKEN:
+        return JSONResponse(status_code=401, content={"detail": "unauthorized"})
+    return await call_next(request)
+
+
+@app.get("/ok")
+def ok() -> dict:
+    return {"ok": True}
+
+
+add_langgraph_fastapi_endpoint(app, LangGraphAgent(name="chat", graph=graph), path="/agent")
diff --git a/examples/ag-ui/python/src/streaming/__init__.py b/examples/ag-ui/python/src/streaming/__init__.py
new file mode 100644
index 000000000..20ecb624d
--- /dev/null
+++ b/examples/ag-ui/python/src/streaming/__init__.py
@@ -0,0 +1,2 @@
+# SPDX-License-Identifier: MIT
+"""Backend streaming helpers for progressive A2UI envelope emission."""
diff --git a/examples/ag-ui/python/src/streaming/a2ui_partial_handler.py b/examples/ag-ui/python/src/streaming/a2ui_partial_handler.py
new file mode 100644
index 000000000..7b08a606f
--- /dev/null
+++ b/examples/ag-ui/python/src/streaming/a2ui_partial_handler.py
@@ -0,0 +1,153 @@
+# SPDX-License-Identifier: MIT
+"""Streaming callback handler that sidebands a parent LLM's growing
+tool_call.arguments as A2UI-partial custom events.
+
+Hooks into LangChain's `on_llm_new_token` callback (the canonical
+streaming-token callback fired by ChatOpenAI when streaming=True is
+enabled). Two delta shapes are observed in production depending on
+which OpenAI API the model uses:
+
+  - Chat Completions API: `chunk.message.tool_call_chunks` carries the
+    classic `[{name, id, args, index}, ...]` deltas.
+  - Responses API (gpt-5 family): `chunk.message.content` carries a
+    list of content blocks; tool-call deltas appear as
+    `{type: 'function_call', name?: str, call_id?: str, arguments: str,
+    index: int}`. The first block for each call carries `name` and
+    `call_id`; subsequent blocks for the same `index` carry only the
+    `arguments` delta.
+
+The handler covers both shapes. For each delta belonging to our target
+tool name, it concatenates arguments per `tool_call_id` and writes an
+`a2ui-partial` event into LangGraph's custom stream via the writer
+returned by `langgraph.config.get_stream_writer()`. The writer's
+payload reaches the frontend under `stream_mode='custom'` as a
+`{type: 'custom', data: ...}` SSE event; the partial-args bridge
+consumes it.
+
+LangGraph's `custom` stream mode is decoupled from langchain_core's
+`adispatch_custom_event` — they're different layers. `adispatch_custom_event`
+emits callback events visible only via `stream_mode='events'`; the
+LangGraph writer is the canonical way to surface custom data on the
+SDK's `custom` channel.
+"""
+from __future__ import annotations
+
+from typing import Any
+from uuid import UUID
+
+from langchain_core.callbacks import AsyncCallbackHandler
+from langchain_core.outputs import ChatGenerationChunk, GenerationChunk
+from langgraph.config import get_stream_writer
+
+
+class A2uiPartialHandler(AsyncCallbackHandler):
+    """Track per-tool_call_id cumulative arguments; write a2ui-partial
+    custom events to the LangGraph stream when the cumulative string
+    grows."""
+
+    def __init__(self, tool_name: str = "render_a2ui_surface") -> None:
+        super().__init__()
+        self._tool_name = tool_name
+        # tool_call_id -> cumulative args string
+        self._buffers: dict[str, str] = {}
+        # Responses-API index -> tool_call_id mapping. The first content
+        # block for each tool call carries name + call_id; subsequent
+        # blocks for that `index` carry only the args delta, so we
+        # remember the mapping to attribute later deltas correctly.
+        self._index_to_call_id: dict[int, str] = {}
+
+    async def on_llm_new_token(
+        self,
+        token: str,
+        *,
+        chunk: ChatGenerationChunk | GenerationChunk | None = None,
+        run_id: UUID | None = None,
+        parent_run_id: UUID | None = None,
+        tags: list[str] | None = None,
+        **kwargs: Any,
+    ) -> None:
+        if chunk is None:
+            return
+        message = getattr(chunk, "message", None)
+        if message is None:
+            return
+
+        # Path 1: Chat Completions API — classic tool_call_chunks list.
+        for tc in getattr(message, "tool_call_chunks", None) or []:
+            self._handle_classic_chunk(tc)
+
+        # Path 2: Responses API — content blocks with type='function_call'.
+        content = getattr(message, "content", None)
+        if isinstance(content, list):
+            for block in content:
+                if isinstance(block, dict) and block.get("type") == "function_call":
+                    self._handle_responses_block(block)
+
+    def _handle_classic_chunk(self, tc: dict) -> None:
+        """Chat Completions delta: {id, name?, args?, index}."""
+        name = tc.get("name") or ""
+        call_id = tc.get("id")
+        delta = tc.get("args") or ""
+        if not call_id:
+            return
+        # The first chunk for a call carries the name; later chunks may omit
+        # it but should be attributed to the same call_id (which IS carried
+        # on every chunk in this shape).
+        if name and name != self._tool_name:
+            return
+        self._dispatch_delta(call_id, delta)
+
+    def _handle_responses_block(self, block: dict) -> None:
+        """Responses API delta: {type, name?, call_id?, arguments, index}.
+
+        The first block for a call carries `name` and `call_id`. Subsequent
+        blocks for the same `index` carry only the `arguments` delta — we
+        remember the index→call_id mapping to attribute them correctly.
+        """
+        index = block.get("index")
+        name = block.get("name") or ""
+        call_id = block.get("call_id")
+        delta = block.get("arguments") or ""
+
+        if call_id:
+            # First block for this call. Validate target tool name.
+            if name and name != self._tool_name:
+                # Not our target — drop any prior mapping for this index.
+                if isinstance(index, int):
+                    self._index_to_call_id.pop(index, None)
+                return
+            if isinstance(index, int):
+                self._index_to_call_id[index] = call_id
+        else:
+            # Subsequent block — look up call_id by index.
+            if not isinstance(index, int):
+                return
+            call_id = self._index_to_call_id.get(index)
+            if not call_id:
+                # Either we never saw a first-block for this index, or it
+                # was for a non-target tool. Skip.
+                return
+
+        self._dispatch_delta(call_id, delta)
+
+    def _dispatch_delta(self, call_id: str, delta: str) -> None:
+        existing = self._buffers.get(call_id, "")
+        updated = existing + delta
+        if updated == existing:
+            return  # No growth — suppress duplicate dispatch.
+        self._buffers[call_id] = updated
+        # `get_stream_writer()` is contextvar-scoped to the currently
+        # executing LangGraph node. Even though this handler runs deep
+        # inside the LLM's callback chain, the contextvar is inherited
+        # so the writer reaches the parent node's `custom` stream.
+        try:
+            writer = get_stream_writer()
+        except RuntimeError:
+            # No stream writer in this context — handler is being invoked
+            # outside a LangGraph stream run (e.g. in unit tests). Silently
+            # skip; tests can mock get_stream_writer to assert behavior.
+            return
+        writer({
+            "name": "a2ui-partial",
+            "data": {"tool_call_id": call_id, "args_so_far": updated},
+        })
diff --git a/examples/ag-ui/python/src/streaming/envelope_normalizer.py b/examples/ag-ui/python/src/streaming/envelope_normalizer.py
new file mode 100644
index 000000000..063a30d1c
--- /dev/null
+++ b/examples/ag-ui/python/src/streaming/envelope_normalizer.py
@@ -0,0 +1,36 @@
+# SPDX-License-Identifier: MIT
+"""Normalises the four envelope-args shapes the parent LLM may emit into
+a canonical envelope list. Parity with libs/chat/src/lib/a2ui/envelope-normalizer.ts.
+
+The spike (examples/chat/python/spike/parent_envelope_quality.py) observed
+these shapes across gpt-5-mini and gpt-5; strict-mode tool binding should
+eliminate the non-canonical ones in production, but this normalizer is
+the safety net.
+"""
+from __future__ import annotations
+
+from typing import Any
+
+_ENVELOPE_KEYS = ("surfaceUpdate", "beginRendering", "dataModelUpdate", "deleteSurface")
+
+
+def normalize_envelope_args(args: Any) -> list[dict] | None:
+    """Return a canonical envelope list, or None if `args` is unrecognised."""
+    if not isinstance(args, dict) or not args:
+        return None
+    # (a) canonical {envelopes: [...]}
+    envelopes = args.get("envelopes")
+    if isinstance(envelopes, list):
+        return envelopes
+    # (b) singular {envelope: [...]} typo
+    envelope = args.get("envelope")
+    if isinstance(envelope, list):
+        return envelope
+    keys = list(args.keys())
+    # (c) positional keys {"0": env, "1": env, ...}
+    if keys and all(isinstance(k, str) and k.isdigit() for k in keys):
+        return [args[k] for k in sorted(keys, key=int)]
+    # (d) flat single envelope
+    if any(k in args for k in _ENVELOPE_KEYS):
+        return [args]
+    return None
diff --git a/examples/ag-ui/python/src/streaming/envelope_tool.py b/examples/ag-ui/python/src/streaming/envelope_tool.py
new file mode 100644
index 000000000..1f32af91f
--- /dev/null
+++ b/examples/ag-ui/python/src/streaming/envelope_tool.py
@@ -0,0 +1,78 @@
+# SPDX-License-Identifier: MIT
+"""Parent-LLM-bound tool that emits A2UI v1 envelopes as structured tool
+arguments. Replaces the old two-LLM `generate_a2ui_schema` flow (parent
+calls a sub-LLM that produces envelopes); the parent now emits envelopes
+directly so the natural token stream IS the surface-rendering stream.
+
+The Pydantic schemas enable OpenAI strict-mode validation when the tool
+is bound via `bind_tools([..., render_a2ui_surface], strict=True)`.
+"""
+from __future__ import annotations
+
+import json
+from typing import Optional
+
+from langchain_core.tools import tool
+from pydantic import BaseModel, Field, model_validator
+
+
+class SurfaceUpdate(BaseModel):
+    """Component-tree envelope. Required first envelope per turn."""
+    surfaceId: str = Field(description="Stable identifier for this surface.")
+    components: list[dict] = Field(
+        description="Component tree as a list of {id, type, props} objects."
+    )
+
+
+class BeginRendering(BaseModel):
+    """Render-start envelope. Required; identifies the root component."""
+    surfaceId: str
+    root: str = Field(description="Component id of the surface root.")
+    styles: Optional[dict] = None
+
+
+class DataModelUpdate(BaseModel):
+    """Initial state envelope. Optional; one per state path the surface binds to."""
+    surfaceId: str
+    path: Optional[str] = None
+    contents: list[dict] = Field(
+        description="Entries: {key, valueString|valueNumber|valueBoolean|valueMap}."
+    )
+
+
+class A2uiEnvelope(BaseModel):
+    """Single A2UI v1 envelope. Exactly one of the three discriminators
+    is set per envelope — the model_validator below enforces this so the
+    parent LLM cannot emit ambiguous or empty envelopes."""
+    surfaceUpdate: Optional[SurfaceUpdate] = None
+    beginRendering: Optional[BeginRendering] = None
+    dataModelUpdate: Optional[DataModelUpdate] = None
+
+    @model_validator(mode="after")
+    def _exactly_one_discriminator(self) -> "A2uiEnvelope":
+        present = sum(
+            1 for v in (self.surfaceUpdate, self.beginRendering, self.dataModelUpdate)
+            if v is not None
+        )
+        if present != 1:
+            raise ValueError(
+                f"A2uiEnvelope requires exactly one of "
+                f"surfaceUpdate / beginRendering / dataModelUpdate; got {present}"
+            )
+        return self
+
+
+@tool
+def render_a2ui_surface(envelopes: list[A2uiEnvelope]) -> str:
+    """Render a UI surface using A2UI v1 envelopes. Emit:
+      - exactly one `surfaceUpdate` (component tree),
+      - exactly one `beginRendering` (root reference),
+      - zero or more `dataModelUpdate` entries (initial state).
+
+    Envelope order in this call should be: surfaceUpdate, beginRendering,
+    then any dataModelUpdate entries (so the surface mounts and per-component
+    placeholders show before initial state arrives).
+    """
+    if not envelopes:
+        raise ValueError("render_a2ui_surface requires at least one envelope")
+    return json.dumps([e.model_dump(exclude_none=True) for e in envelopes])
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new file mode 100644
index 000000000..166d36c94
--- /dev/null
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@@ -0,0 +1,1362 @@
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+revision = 3
+requires-python = ">=3.12"
+
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+version = "0.0.2"
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