dekun
a5f5239be9
Replace pipe-separated account lines with a structured table from stats_snapshot, including exchange icons and position remarks. Co-authored-by: Cursor <cursoragent@cursor.com>
72 lines
2.4 KiB
Python
72 lines
2.4 KiB
Python
"""中控 AI：今日总结生成。"""
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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.context import build_daily_context, format_account_remark
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from hub_ai.prompts import SUMMARY_SYSTEM, build_summary_user_prompt
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from hub_ai.store import append_summary, get_latest_summary, list_summaries
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def generate_daily_summary(
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exchanges: list[dict],
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*,
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trading_day: str | None = None,
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force: bool = False,
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) -> dict[str, Any]:
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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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if not force:
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latest = get_latest_summary(day)
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if latest and latest.get("context_hash") == ctx.get("context_hash"):
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return {
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"ok": True,
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"cached": True,
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"trading_day": day,
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"summary": latest,
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"model": latest.get("model") or model_label(),
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}
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system = SUMMARY_SYSTEM.replace("{trading_day}", day)
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user = build_summary_user_prompt(ctx["text"], day)
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content = generate_text(system=system, user=user, temperature=0.15)
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if content.startswith("AI 调用失败"):
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return {"ok": False, "msg": content, "trading_day": day}
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stats_snapshot = {
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"totals": ctx.get("totals"),
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"by_account": {
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str(ac.get("key") or ac.get("id")): {
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"key": ac.get("key"),
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"name": ac.get("name"),
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"status": ac.get("status"),
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"pnl_u": (ac.get("trade_stats") or {}).get("total_pnl_u"),
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"closed_count": (ac.get("trade_stats") or {}).get("closed_count"),
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"float_pnl_u": ac.get("float_pnl_u"),
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"remark": format_account_remark(ac),
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"issues": ac.get("issues") or [],
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}
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for ac in ctx.get("accounts") or []
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},
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}
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row = append_summary(
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trading_day=day,
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content_md=content,
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model=model_label(),
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context_hash=ctx.get("context_hash") or "",
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stats_snapshot=stats_snapshot,
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)
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return {
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"ok": True,
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"cached": False,
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"trading_day": day,
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"summary": row,
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"model": model_label(),
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"context": ctx,
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}
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def summary_list(trading_day: str | None = None) -> list[dict]:
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return list_summaries(trading_day=trading_day)
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