Add AI trading supervisor with WeChat push and daily session

Proactive monitoring for manual/hub closes and new opens prevents overtrading via in-app alerts, configurable WeChat links, and supervisor chat.

Co-authored-by: Cursor <cursoragent@cursor.com>

manual_trading_hub/hub_ai/prompts.py

@@ -174,6 +174,59 @@ ARCHIVE_QUOTE_REVIEW_INSTRUCTION = """
 """.strip()
 
 
+SUPERVISOR_SYSTEM = """
+你是交易监管值班员，职责是防止过度交易与频繁手动操作。用中文、短句、克制语气。
+
+规则：
+- 只依据提供的结构化事件与账户快照说话；禁止预测涨跌、保证收益。
+- **手动平仓、中控平仓、新开仓**：指出频率、间隔、是否偏急；提醒休息，不训斥。
+- **程序止盈/程序止损**：肯定按计划执行，鼓励保持纪律，提醒别立刻反手再开。
+- 不替用户做决定，不暗示绕过实例冷静期/日冻结。
+- 每次 1~3 句，必须写完整；禁止长清单和「第1点第2点」。
+- 实例已进入冷静期/日冻结时，明确说明状态，建议暂停手动开平。
+""".strip()
+
+
+def build_supervisor_ai_prompt(
+    *,
+    context_text: str,
+    trading_day: str,
+    event: dict,
+    warnings: list[dict],
+) -> str:
+    warn_lines = "\n".join(f"- {w.get('message')}" for w in (warnings or []) if w.get("message"))
+    parts = [
+        f"【交易日】{trading_day}",
+        "【监管事件】",
+        str(event or {}),
+        "【当前多账户快照】",
+        (context_text or "（无）").strip(),
+    ]
+    if warn_lines.strip():
+        parts.extend(["【已触发频率警告】", warn_lines.strip()])
+    parts.append("请给出 1~3 句监管评语：")
+    return "\n\n".join(parts)
+
+
+def build_supervisor_chat_prompt(
+    *,
+    context_text: str,
+    trading_day: str,
+    history_lines: str,
+    user_message: str,
+) -> str:
+    parts = [f"【交易日】{trading_day}"]
+    if history_lines.strip():
+        parts.extend(["【今日监管对话】", history_lines.strip()])
+    parts.extend([
+        "【当前多账户快照】",
+        (context_text or "（无）").strip(),
+        "【用户现在说】",
+        user_message.strip(),
+    ])
+    return "\n\n".join(parts)
+
+
 def build_archive_quote_review_prompt(
     *,
     quote_date: str,

manual_trading_hub/hub_ai/routes.py

@@ -19,8 +19,11 @@ from hub_ai.client import model_label
 from hub_ai.config import trading_day_reset_hour
 from hub_ai.context import build_daily_context
 from hub_ai.store import get_latest_summary, list_summaries
+from hub_ai.supervisor import send_supervisor_chat
+from hub_ai.supervisor_store import get_supervisor_session_state
 from hub_ai.summary import generate_daily_summary
 from hub_trades_lib import current_trading_day
+from settings_store import normalize_supervisor_settings
 
 
 class ChatSendBody(BaseModel):
@@ -47,6 +50,11 @@ class ArchiveQuoteChatBody(BaseModel):
     content: str = ""
 
 
+class SupervisorChatBody(BaseModel):
+    message: str = ""
+    trading_day: str = ""
+
+
 def create_hub_ai_router(*, load_all_exchanges: Callable[[], list]) -> APIRouter:
     router = APIRouter(prefix="/api/ai", tags=["hub-ai"])
 
@@ -165,4 +173,28 @@ def create_hub_ai_router(*, load_all_exchanges: Callable[[], list]) -> APIRouter
             raise HTTPException(status_code=502, detail=result.get("msg") or "发送失败")
         return result
 
+    @router.get("/supervisor/session")
+    def api_ai_supervisor_session(trading_day: str = ""):
+        day = _day(trading_day)
+        return get_supervisor_session_state(day)
+
+    @router.get("/supervisor/rules")
+    def api_ai_supervisor_rules():
+        from settings_store import load_settings
+
+        cfg = normalize_supervisor_settings(load_settings().get("supervisor"))
+        return {"ok": True, "supervisor": cfg}
+
+    @router.post("/supervisor/chat/send")
+    def api_ai_supervisor_chat_send(body: SupervisorChatBody = SupervisorChatBody()):
+        exchanges = load_all_exchanges()
+        result = send_supervisor_chat(
+            exchanges,
+            body.message,
+            trading_day=_day(body.trading_day) if body.trading_day.strip() else None,
+        )
+        if not result.get("ok"):
+            raise HTTPException(status_code=502, detail=result.get("msg") or "发送失败")
+        return result
+
     return router

manual_trading_hub/hub_ai/store.py

@@ -142,7 +142,8 @@ def get_active_session() -> Optional[dict]:
 
 CHAT_BOT_TRADING = "trading"
 CHAT_BOT_GENERAL = "general"
-CHAT_BOT_MODES = frozenset({CHAT_BOT_TRADING, CHAT_BOT_GENERAL})
+CHAT_BOT_SUPERVISOR = "supervisor"
+CHAT_BOT_MODES = frozenset({CHAT_BOT_TRADING, CHAT_BOT_GENERAL, CHAT_BOT_SUPERVISOR})
 
 
 def _normalize_bot_mode(raw: Any) -> str:

manual_trading_hub/hub_ai/supervisor.py

@@ -0,0 +1,111 @@
+"""交易监管：AI 评语与用户回聊。"""
+from __future__ import annotations
+
+from typing import Any, Optional
+
+from hub_ai.client import generate_text, model_label
+from hub_ai.config import (
+    CHAT_MAX_OUTPUT_TOKENS,
+    CHAT_TEMPERATURE,
+    trading_day_reset_hour,
+)
+from hub_ai.context import build_chat_context, format_chat_context_for_chat
+from hub_ai.prompts import SUPERVISOR_SYSTEM, build_supervisor_ai_prompt, build_supervisor_chat_prompt
+from hub_ai.supervisor_store import (
+    append_supervisor_ai_message,
+    ensure_supervisor_session,
+    get_supervisor_session_state,
+)
+from hub_ai.store import append_chat_message
+from hub_trades_lib import current_trading_day
+
+
+def generate_supervisor_ai_reply(
+    *,
+    event: dict,
+    warnings: list[dict],
+    trading_day: str,
+    session_id: str,
+    exchanges: list[dict],
+) -> str:
+    ctx = build_chat_context(exchanges, trading_day=trading_day)
+    brief = format_chat_context_for_chat(ctx, max_chars=6000)
+    user_prompt = build_supervisor_ai_prompt(
+        context_text=brief,
+        trading_day=trading_day,
+        event=event,
+        warnings=warnings,
+    )
+    return generate_text(
+        system=SUPERVISOR_SYSTEM,
+        user=user_prompt,
+        temperature=min(0.35, CHAT_TEMPERATURE),
+        max_tokens=min(512, CHAT_MAX_OUTPUT_TOKENS),
+        max_continuations=1,
+    )
+
+
+def make_supervisor_ai_reply_fn(exchanges: list[dict]):
+    def _fn(*, event: dict, warnings: list[dict], trading_day: str, session_id: str) -> str:
+        return generate_supervisor_ai_reply(
+            event=event,
+            warnings=warnings or [],
+            trading_day=trading_day,
+            session_id=session_id,
+            exchanges=exchanges,
+        )
+
+    return _fn
+
+
+def send_supervisor_chat(
+    exchanges: list[dict],
+    message: str,
+    *,
+    trading_day: str | None = None,
+) -> dict[str, Any]:
+    text = (message or "").strip()
+    if not text:
+        return {"ok": False, "msg": "消息不能为空"}
+    day = (trading_day or "").strip()[:10] or current_trading_day(
+        reset_hour=trading_day_reset_hour()
+    )
+    session = ensure_supervisor_session(day)
+    sid = str(session.get("id") or "")
+    prior = session.get("messages") or []
+    ctx = build_chat_context(exchanges, trading_day=day)
+    brief = format_chat_context_for_chat(ctx, max_chars=6000)
+    recent = []
+    for m in prior[-8:]:
+        role = m.get("role")
+        if role not in ("user", "assistant", "system"):
+            continue
+        label = {"user": "用户", "assistant": "监管", "system": "系统"}.get(role, role)
+        recent.append(f"{label}：{str(m.get('content') or '').strip()}")
+    user_prompt = build_supervisor_chat_prompt(
+        context_text=brief,
+        trading_day=day,
+        history_lines="\n".join(recent),
+        user_message=text,
+    )
+    reply = generate_text(
+        system=SUPERVISOR_SYSTEM,
+        user=user_prompt,
+        temperature=min(0.4, CHAT_TEMPERATURE),
+        max_tokens=min(768, CHAT_MAX_OUTPUT_TOKENS),
+        max_continuations=1,
+    )
+    if not reply or reply.strip().startswith("AI "):
+        return {"ok": False, "msg": reply or "AI 生成失败", "session_id": sid}
+    append_chat_message(sid, "user", text)
+    session = append_supervisor_ai_message(sid, reply.strip())
+    state = get_supervisor_session_state(day)
+    return {
+        "ok": True,
+        "trading_day": day,
+        "session": session,
+        "reply": reply.strip(),
+        "model": model_label(),
+        "message_count": state.get("message_count"),
+        "unread_system": state.get("unread_system"),
+    }

manual_trading_hub/hub_ai/supervisor_store.py

@@ -0,0 +1,101 @@
+"""交易监管专用会话（今日长会话，bot_mode=supervisor）。"""
+from __future__ import annotations
+
+from typing import Any, Optional
+
+from hub_ai.store import (
+    CHAT_BOT_SUPERVISOR,
+    append_chat_message,
+    load_chat_store,
+    save_chat_store,
+)
+
+
+def _supervisor_title(trading_day: str) -> str:
+    return f"今日监管 {trading_day}"
+
+
+def find_supervisor_session(trading_day: str) -> Optional[dict]:
+    day = (trading_day or "").strip()[:10]
+    store = load_chat_store()
+    for s in store.get("sessions") or []:
+        if str(s.get("bot_mode") or "") != CHAT_BOT_SUPERVISOR:
+            continue
+        if str(s.get("trading_day") or "") == day:
+            return s
+    return None
+
+
+def ensure_supervisor_session(trading_day: str) -> dict:
+    day = (trading_day or "").strip()[:10]
+    existing = find_supervisor_session(day)
+    if existing:
+        return existing
+    store = load_chat_store()
+    from datetime import datetime
+    import uuid
+
+    session = {
+        "id": uuid.uuid4().hex,
+        "trading_day": day,
+        "title": _supervisor_title(day),
+        "bot_mode": CHAT_BOT_SUPERVISOR,
+        "created_at": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
+        "updated_at": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
+        "messages": [],
+        "rolling_summary": "",
+        "supervisor_locked": True,
+    }
+    store.setdefault("sessions", []).append(session)
+    save_chat_store(store)
+    return session
+
+
+def append_supervisor_system_message(
+    session_id: str,
+    content: str,
+    *,
+    event_type: str = "",
+    level: str = "info",
+) -> dict:
+    store = load_chat_store()
+    target = None
+    for s in store.get("sessions") or []:
+        if str(s.get("id")) == str(session_id):
+            target = s
+            break
+    if not target:
+        raise KeyError("session_not_found")
+    from datetime import datetime
+
+    msg = {
+        "role": "system",
+        "content": (content or "").strip(),
+        "at": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
+        "event_type": event_type,
+        "level": level,
+    }
+    target.setdefault("messages", []).append(msg)
+    target["updated_at"] = msg["at"]
+    save_chat_store(store)
+    return target
+
+
+def append_supervisor_ai_message(session_id: str, content: str) -> dict:
+    return append_chat_message(session_id, "assistant", content)
+
+
+def get_supervisor_session_state(trading_day: str) -> dict[str, Any]:
+    from hub_ai.client import model_label
+
+    session = ensure_supervisor_session(trading_day)
+    msgs = session.get("messages") or []
+    unread = sum(1 for m in msgs if m.get("role") == "system" and not m.get("read"))
+    return {
+        "ok": True,
+        "session": session,
+        "trading_day": trading_day,
+        "message_count": len(msgs),
+        "unread_system": unread,
+        "model": model_label(),
+    }