dekun
cee641ba5d
Aggregate four-account trades via hub_ai module and /api/hub/trades/today; store sessions in JSON; default OpenAI config matches instances. Co-authored-by: Cursor <cursoragent@cursor.com>
89 lines
2.6 KiB
Python
89 lines
2.6 KiB
Python
"""中控 AI：单会话聊天（直到用户点击新开）。"""
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from __future__ import annotations
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from typing import Any
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from hub_ai.client import generate_text, model_label
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from hub_ai.config import CHAT_MAX_HISTORY_TURNS, CHAT_TEMPERATURE
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from hub_ai.context import build_daily_context, format_chat_context_brief
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from hub_ai.prompts import CHAT_SYSTEM, build_chat_user_prompt
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from hub_ai.store import (
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append_chat_message,
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create_new_session,
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ensure_active_session,
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get_active_session,
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load_chat_store,
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summary_excerpt_for_chat,
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)
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def _history_lines(messages: list[dict], max_turns: int = CHAT_MAX_HISTORY_TURNS) -> str:
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rows = [m for m in (messages or []) if m.get("role") in ("user", "assistant")]
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rows = rows[-max_turns * 2 :]
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lines = []
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for m in rows:
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role = "用户" if m.get("role") == "user" else "搭档"
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lines.append(f"{role}：{m.get('content') or ''}")
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return "\n".join(lines)
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def get_chat_state() -> dict[str, Any]:
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store = load_chat_store()
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session = get_active_session()
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return {
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"active_session_id": store.get("active_session_id"),
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"session": session,
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"model": model_label(),
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}
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def start_new_chat(*, trading_day: str) -> dict:
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session = create_new_session(trading_day=trading_day)
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return {"ok": True, "session": session, "model": model_label()}
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def send_chat_message(
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exchanges: list[dict],
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message: str,
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*,
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trading_day: str | None = None,
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) -> dict[str, Any]:
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text = (message or "").strip()
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if not text:
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return {"ok": False, "msg": "消息不能为空"}
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ctx = build_daily_context(exchanges, trading_day=trading_day)
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day = ctx["trading_day"]
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session = ensure_active_session(trading_day=day)
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sid = session["id"]
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history = _history_lines(session.get("messages") or [])
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append_chat_message(sid, "user", text)
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brief_ctx = format_chat_context_brief(ctx)
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excerpt = summary_excerpt_for_chat(day)
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user_prompt = build_chat_user_prompt(
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context_text=brief_ctx,
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trading_day=day,
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summary_excerpt=excerpt,
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history_lines=history,
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user_message=text,
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)
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reply = generate_text(
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system=CHAT_SYSTEM,
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user=user_prompt,
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temperature=CHAT_TEMPERATURE,
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)
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if reply.startswith("AI 调用失败"):
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return {"ok": False, "msg": reply, "session_id": sid}
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session = append_chat_message(sid, "assistant", reply)
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return {
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"ok": True,
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"trading_day": day,
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"session": session,
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"reply": reply,
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"model": model_label(),
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}
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