Add key-level auto trade, AI analysis, and trading UX improvements.
Key monitors use 5m close triggers with WeChat alerts and box/convergence auto orders; add pending-order worker, structured WeChat notify, AI settings/messages, session clock, CTP margin sizing, and dual-layer position limits. Co-authored-by: Cursor <cursoragent@cursor.com>
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# Copyright (c) 2025-2026 马建军. All rights reserved.
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# 专有软件 — 未经授权禁止复制、传播、转售。
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# 严禁用于:带单/代客理财、向他人推荐期货品种或买卖建议、融资配资等业务。
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# 详见 LICENSE.zh-CN.txt 与 docs/软件购买与使用协议.md
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"""AI 消息存储与展示。"""
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from __future__ import annotations
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import json
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import sqlite3
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from datetime import datetime
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from typing import Any, Callable, Optional
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from zoneinfo import ZoneInfo
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TZ = ZoneInfo("Asia/Shanghai")
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CREATE_SQL = """
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CREATE TABLE IF NOT EXISTS ai_messages (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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kind TEXT NOT NULL,
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title TEXT,
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content TEXT NOT NULL,
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meta_json TEXT,
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created_at TEXT NOT NULL
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)
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"""
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def ensure_ai_messages_table(conn: sqlite3.Connection) -> None:
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conn.execute(CREATE_SQL)
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conn.execute(
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"CREATE INDEX IF NOT EXISTS idx_ai_messages_created ON ai_messages(created_at DESC)"
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)
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def insert_ai_message(
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conn: sqlite3.Connection,
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*,
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kind: str,
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title: str,
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content: str,
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meta: Optional[dict[str, Any]] = None,
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) -> int:
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ensure_ai_messages_table(conn)
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now = datetime.now(TZ).strftime("%Y-%m-%d %H:%M:%S")
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cur = conn.execute(
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"""INSERT INTO ai_messages (kind, title, content, meta_json, created_at)
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VALUES (?,?,?,?,?)""",
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(kind, title, content, json.dumps(meta or {}, ensure_ascii=False), now),
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)
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return int(cur.lastrowid)
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def list_ai_messages(conn: sqlite3.Connection, *, limit: int = 100) -> list[dict]:
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ensure_ai_messages_table(conn)
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rows = conn.execute(
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"SELECT * FROM ai_messages ORDER BY id DESC LIMIT ?",
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(max(1, min(500, int(limit))),),
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).fetchall()
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out = []
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for r in rows:
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item = dict(r)
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try:
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item["meta"] = json.loads(item.get("meta_json") or "{}")
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except Exception:
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item["meta"] = {}
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out.append(item)
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return out
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