Complete named expert growth tasks

app/growth_chains.py

@@ -36,6 +36,28 @@
 QQ_BUDDY_ID = "cb_y5Dy46tPQGGWtueMxXbe"
 QQ_BUDDY_NAME = "企鹅教师助手"
 LIGHTHOUSE_EXPERT_ID = "ex_2cvvUZQhDyeJ"
+NAMED_EXPERT_TASKS = {
+    "WorkBuddy_Valorant": {
+        "expert_id": "ex_xQHHD1u5Jkua", "expert_type": "agent",
+        "display_name_zh": "无畏契约拼豆专家", "profession_zh": "无畏契约拼豆专家",
+        "version": "1.2.7", "categories": ["03-GameSpatial", "06-ContentCreative"]},
+    "expert_use_bowangwang": {
+        "expert_id": "ex_WZY136wV5aMt", "expert_type": "agent",
+        "display_name_zh": "播旺旺", "profession_zh": "直播电商教练",
+        "version": "1.0.2", "categories": ["05-MarketingGrowth", "18-Double11"]},
+    "expert_use_douyinyin": {
+        "expert_id": "ex_FbY5nlWTqDod", "expert_type": "agent",
+        "display_name_zh": "斗音音", "profession_zh": "抖音策略师",
+        "version": "1.0.2", "categories": ["06-ContentCreative", "18-Double11"]},
+    "expert_use_maidehao": {
+        "expert_id": "ex_GDl31WahyIH0", "expert_type": "agent",
+        "display_name_zh": "卖得好", "profession_zh": "中国电商运营专家",
+        "version": "1.0.1", "categories": ["05-MarketingGrowth", "18-Double11"]},
+    "expert_use_shangjia_xuanchuan": {
+        "expert_id": "ex_Weo3x2EZuSDm", "expert_type": "agent",
+        "display_name_zh": "商家宣传设计师", "profession_zh": "商家宣传页与海报设计师",
+        "version": "1.6.0", "categories": ["01-ProductDesign", "05-MarketingGrowth", "18-Double11"]},
+}
 SKILL_NAME = "润泽小馆·日报撰写"
 SKILL_ID = "skill_2097350077599879168"
 THEME_KEY = "theme-tkmw7j"
@@ -279,18 +301,16 @@ def run_expert_team_3(ctx, task):
     return _run_expert_batch(ctx, "team", 3)
 
 
-def run_expert_lighthouse(ctx, task):
-    expert = {"expert_id": LIGHTHOUSE_EXPERT_ID, "expert_type": "agent",
-              "display_name_zh": "腾讯轻量云专家", "profession_zh": "腾讯轻量云专家",
-              "version": "1.0.2", "categories": []}
+def _run_named_expert(ctx, expert, *, local=False):
+    expert = dict(expert)
     try:
         for candidate in growth_events.market_expert_list(ctx.base, ctx.token, ctx.uid, "agent",
                                                           domain=ctx.domain):
-            if candidate.get("expert_id") == LIGHTHOUSE_EXPERT_ID:
+            if candidate.get("expert_id") == expert["expert_id"]:
                 expert = candidate
                 break
     except growth_events.Failure:
-        pass     # 市场不可用时用内置专家信息（id 为平台真实 id）
+        pass  # Fall back to the verified task-specific id when the market is unavailable.
     _report_desktop(ctx, growth_events.expert_summon_sequence(expert))
     conversation_id, request_id = _real_chat(ctx, expert_id=expert["expert_id"])
     events = growth_events.chat_sequence(conversation_id, request_id,
@@ -299,11 +319,40 @@ def run_expert_lighthouse(ctx, task):
         if event["eventCode"] == "agent_task_created":
             event.update(has_expert=True, expert_id=expert["expert_id"],
                          expert_name=expert.get("display_name_zh") or "", expert_industry_id="")
-    events.append(growth_events.expert_actual_use(expert, conversation_id, request_id, mode="LOCAL"))
+    events.append(growth_events.expert_actual_use(
+        expert, conversation_id, request_id, mode="LOCAL" if local else "craft"))
     _report_desktop(ctx, events)
+    return f"已上报「{expert.get('display_name_zh') or expert['expert_id']}」召唤+使用链（真实对话 requestId）"
+
+
+def run_expert_lighthouse(ctx, task):
+    _run_named_expert(ctx, {
+        "expert_id": LIGHTHOUSE_EXPERT_ID, "expert_type": "agent",
+        "display_name_zh": "腾讯轻量云专家", "profession_zh": "腾讯轻量云专家",
+        "version": "1.0.2", "categories": []}, local=True)
     return "已上报轻量云专家召唤+使用链（真实对话 requestId）"
 
 
+def run_workbuddy_valorant(ctx, task):
+    return _run_named_expert(ctx, NAMED_EXPERT_TASKS["WorkBuddy_Valorant"])
+
+
+def run_expert_bowangwang(ctx, task):
+    return _run_named_expert(ctx, NAMED_EXPERT_TASKS["expert_use_bowangwang"])
+
+
+def run_expert_douyinyin(ctx, task):
+    return _run_named_expert(ctx, NAMED_EXPERT_TASKS["expert_use_douyinyin"])
+
+
+def run_expert_maidehao(ctx, task):
+    return _run_named_expert(ctx, NAMED_EXPERT_TASKS["expert_use_maidehao"])
+
+
+def run_expert_shangjia_xuanchuan(ctx, task):
+    return _run_named_expert(ctx, NAMED_EXPERT_TASKS["expert_use_shangjia_xuanchuan"])
+
+
 def run_black_cat(ctx, task):
     if not in_night_window():
         return "当前不在 23:00–08:00 计数窗口，行为不计分；窗口内自动补足"
@@ -522,6 +571,11 @@ def events():
     "Hp_Appearance": run_hp_appearance,
     "Model_chat_GLM5.2": run_model_chat_glm, "skill_1": run_skill_1, "expert_5": run_expert_5,
     "Expert_team_use_3": run_expert_team_3, "Expert_lighthouse": run_expert_lighthouse,
+    "WorkBuddy_Valorant": run_workbuddy_valorant,
+    "expert_use_bowangwang": run_expert_bowangwang,
+    "expert_use_douyinyin": run_expert_douyinyin,
+    "expert_use_maidehao": run_expert_maidehao,
+    "expert_use_shangjia_xuanchuan": run_expert_shangjia_xuanchuan,
     "black_cat": run_black_cat,
     "school_season": run_school_season, "Sequential_Tasks_1": run_sequential_1,
     "Sequential_Tasks_2": run_sequential_2, "Sequential_Tasks_3": run_sequential_3,

app/growth_tasks.py

@@ -30,6 +30,9 @@
     "Hp_Appearance": "behavior",
     "Model_chat_GLM5.2": "chat", "skill_1": "chat", "expert_5": "chat",
     "Expert_team_use_3": "chat", "Expert_lighthouse": "chat", "black_cat": "chat",
+    "WorkBuddy_Valorant": "chat", "expert_use_bowangwang": "chat",
+    "expert_use_douyinyin": "chat", "expert_use_maidehao": "chat",
+    "expert_use_shangjia_xuanchuan": "chat",
     "school_season": "miniprogram", "Sequential_Tasks_1": "miniprogram",
     "Sequential_Tasks_2": "miniprogram", "Sequential_Tasks_3": "miniprogram",
     "Sequential_Tasks_4": "miniprogram", "Sequential_Tasks_5": "miniprogram",

docs/advanced.md

@@ -142,7 +142,7 @@ Upstream client identities follow verified official packages: domestic CLI 2.165
 ## Automation and rewards
 
 Automatic check-in and Buddy travel are per-account switches (WebUI credentials page): on by default for domestic personal accounts, off internationally, applied live without restart. The growth center is personal-only, so enterprise accounts never travel and no longer surface the upstream 403.
-The growth-center sweep (`auto_growth`, on by default for domestic personal accounts) rides the hourly maintenance pass as pure accept/claim: it claims finished tasks for credit and energy and never starts a behavior chain by itself. Per-task `growth_auto` switches (off by default) opt specific tasks into automation, so the sweep also drives the matching chain — real conversations, app opens or expert summons that may spend credits. The credential drawer lists live tasks with one-click manual runs for a single task or all enabled ones, and task switches can be copied to selected accounts (`POST /admin/credentials/growth-batch`); `GET /admin/credentials/{id}/growth-tasks`, `.../growth-tasks/auto` and `.../auto-all` back the panel. Manual runs are server-side jobs, one per account: the request returns the job at once, closing the drawer or the page does not stop it, starting again while it runs returns the running job, and `GET /admin/growth-jobs` lists every account's current or last job with the task in progress for the page banner. Manual runs and sweep claims are audited; enterprise or international accounts never see the panel.
+The growth-center sweep (`auto_growth`, on by default for domestic personal accounts) rides the hourly maintenance pass as pure accept/claim: it claims finished tasks for credit and energy and never starts a behavior chain by itself. Per-task `growth_auto` switches (off by default) opt specific tasks into automation, so the sweep also drives the matching chain — real conversations, app opens or expert summons that may spend credits. The credential drawer lists live tasks with one-click manual runs for a single task or all enabled ones, and task switches can be copied to selected accounts (`POST /admin/credentials/growth-batch`); `GET /admin/credentials/{id}/growth-tasks`, `.../growth-tasks/auto` and `.../auto-all` back the panel. Manual runs are server-side jobs, one per account: the request returns the job at once, closing the drawer or the page does not stop it, starting again while it runs returns the running job, and `GET /admin/growth-jobs` lists every account's current or last job with the task in progress for the page banner. Named expert tasks use verified task-specific expert IDs through the same opt-in real-conversation chain. Manual runs and sweep claims are audited; enterprise or international accounts never see the panel.
 Check-in, travel, growth and daily-chat results or exceptions carrying 11140 use the same persistent two-hour restricted state as inference. The current sweep stops immediately, including remaining growth claims, and later sweeps skip the account until the rest expires or an operator releases it; other codes retain their existing logging and retry behavior.
 
 `CODEBUDDY2API_AUTO_ACCEPT_BUDDY` is startup-only and defaults to `false`. It preauthorizes enabled domestic accounts for first-Buddy onboarding, agreement and travel; automatic travel still respects its account switch. `first_buddy` needs no acceptance API: pending states, including `not_accepted`, allow one real domestic WorkBuddy conversation on that account. Prefer an eligible zero-rate model, otherwise the lowest known rate; request at most 32 output tokens with possible credit usage. Other reward tasks, paid boxes, pet switching and international trials are excluded.

docs/advanced.zh-CN.md

@@ -143,7 +143,7 @@ scoped 模式可选传入 `X-Codebuddy-Session-ID`、`metadata.conversation_id`
 
 自动签到与 Buddy 旅行是按账号设置的开关（WebUI 凭证页）：国内个人账号默认开启，国际默认关闭，保存即生效，无需重启。成长中心仅面向个人账号，企业账号不参与旅行（也不再显示上游 403）。
 
-成长中心补领（`auto_growth`，国内个人账号默认开启）随每小时维护扫描执行，只做接取与领取：领取已完成任务的积分与能量，自身不启动任何行为链。任务级 `growth_auto` 开关（默认全部关闭）把指定任务纳入自动化，扫描随后驱动对应行为链——可能消耗积分的真实对话、应用体验或专家召唤。凭证页展示实时任务列表，支持单任务与已开开关任务的一键手动执行，任务开关可复制到已选账号（`POST /admin/credentials/growth-batch`）；面板由 `GET /admin/credentials/{id}/growth-tasks`、`.../growth-tasks/auto` 与 `.../auto-all` 支撑。手动执行是服务端后台任务（每个账号同时只有一个）：请求立即返回任务，关闭抽屉或页面不影响执行，运行中再次发起会返回当前任务；`GET /admin/growth-jobs` 列出各账号当前或最近一次任务及正在执行的任务，供页面横幅显示。手动执行与扫描领取均入审计；企业与国际账号不显示该面板。
+成长中心补领（`auto_growth`，国内个人账号默认开启）随每小时维护扫描执行，只做接取与领取：领取已完成任务的积分与能量，自身不启动任何行为链。任务级 `growth_auto` 开关（默认全部关闭）把指定任务纳入自动化，扫描随后驱动对应行为链——可能消耗积分的真实对话、应用体验或专家召唤。凭证页展示实时任务列表，支持单任务与已开开关任务的一键手动执行，任务开关可复制到已选账号（`POST /admin/credentials/growth-batch`）；面板由 `GET /admin/credentials/{id}/growth-tasks`、`.../growth-tasks/auto` 与 `.../auto-all` 支撑。手动执行是服务端后台任务（每个账号同时只有一个）：请求立即返回任务，关闭抽屉或页面不影响执行，运行中再次发起会返回当前任务；`GET /admin/growth-jobs` 列出各账号当前或最近一次任务及正在执行的任务，供页面横幅显示。指定专家任务使用已核实的任务专属专家 ID，沿用需主动开启的真实对话链。手动执行与扫描领取均入审计；企业与国际账号不显示该面板。
 签到、旅行、成长和活跃打卡的结果或异常携带 11140 时，与推理共用持久两小时官方限制状态。当前扫描立即停止，包括剩余成长领取；限制到期或人工解除前，后续扫描跳过该账号；其他业务码保持原有日志和重试行为。
 
 `CODEBUDDY2API_AUTO_ACCEPT_BUDDY` 仅启动读取，默认 `false`；预授权已启用国内账号完成首次领猫任务、协议及旅行，自动旅行仍受账号开关控制。`first_buddy` 无需单独接取，包含 `not_accepted` 在内的待完成状态可直接发起一次本账号的真实国内 WorkBuddy 对话；优先可用零倍率模型，否则取最低已知倍率，最多请求 32 个输出 token，可能消耗少量积分。不执行其他奖励任务、不付费开盒、不切猫、不领取国际试用积分。

tests/test_growth_chains.py

@@ -220,6 +220,54 @@ def test_real_chat_request_id_shape(self):
         self.assertTrue(growth_events.SERVER_ID_RE.match("a" * 32))
 
 
+class NamedExpertTests(ChainHarness):
+    def exercise(self, code, expert):
+        reports, seen = [], {}
+
+        def real_chat(_ctx, expert_id="", model=growth_chains.DEFAULT_CHAT_MODEL):
+            seen["expert_id"] = expert_id
+            return "wb2api-conv-x", "cmb-" + "a" * 32
+
+        # Same-name market entries must never replace the task-specific expert id.
+        wrong = {"expert_id": "ex_wrong", "display_name_zh": expert["display_name_zh"]}
+        ctx = growth_chains.Context(base="https://www.workbuddy.cn", token="tok", uid="u1")
+        with patch.object(growth_events, "market_expert_list", return_value=[wrong]), \
+                patch.object(growth_chains, "_real_chat", side_effect=real_chat), \
+                patch.object(growth_chains, "_report_desktop",
+                             side_effect=lambda _ctx, events: reports.append(events)):
+            message = growth_chains.RUNNERS[code](ctx, raw_task(code))
+        return message, reports, seen
+
+    def test_cloud_expert_tasks_keep_their_verified_ids(self):
+        for code, expert in growth_chains.NAMED_EXPERT_TASKS.items():
+            with self.subTest(code=code):
+                message, reports, seen = self.exercise(code, expert)
+                self.assertEqual(seen["expert_id"], expert["expert_id"])
+                self.assertEqual(growth_tasks.GROUPS[code], "chat")
+                self.assertIn(expert["display_name_zh"], message)
+                summoned = next(event for report in reports for event in report
+                                if event["eventCode"] == "expert_summoned")
+                actual = next(event for report in reports for event in report
+                              if event["eventCode"] == "expert_actual_use")
+                self.assertEqual(summoned["id"], expert["expert_id"])
+                self.assertEqual(actual["id"], expert["expert_id"])
+                self.assertEqual(actual["name"], expert["display_name_zh"])
+                self.assertEqual(actual["version"], expert["version"])
+                self.assertEqual(actual["type"], expert["categories"][0])
+                self.assertEqual(actual["mode"], "craft")
+
+    def test_lighthouse_keeps_its_local_event_shape(self):
+        expert = {"expert_id": growth_chains.LIGHTHOUSE_EXPERT_ID,
+                  "display_name_zh": "腾讯轻量云专家"}
+        _message, reports, seen = self.exercise("Expert_lighthouse", expert)
+        self.assertEqual(seen["expert_id"], growth_chains.LIGHTHOUSE_EXPERT_ID)
+        actual = next(event for report in reports for event in report
+                      if event["eventCode"] == "expert_actual_use")
+        self.assertEqual(actual["mode"], "LOCAL")
+        self.assertEqual(actual["type"], "")
+        self.assertEqual(actual["cost"], 0)
+
+
 class NightWindowTests(ChainHarness):
     def test_window_boundaries(self):
         for hour, expected in ((22, False), (23, True), (0, True), (7, True), (8, False)):