356 lines
13 KiB
Python
356 lines
13 KiB
Python
"""Function Calling 工具定义和执行器
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让 AI 可以主动调用现有 API 获取市场数据：
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- get_market_dashboard: 市场看板
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- get_theme_history: 题材热点历史
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- get_active_core_stocks: 核心股追踪
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- get_stock_quote: 个股实时行情
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- get_fund_flow: 资金流向
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"""
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import json
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from services.ai_config import AI_API_BASE, AI_API_KEY, AI_MODEL, AI_MAX_TOKENS, AI_TEMPERATURE
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TOOLS = [
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{
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"type": "function",
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"function": {
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"name": "get_market_dashboard",
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"description": "获取A股市场看板数据，包含主要指数行情、全市场涨跌统计（涨跌家数/涨停/跌停/炸板率/成交额）、市场温度评分与竞价信号、行业强度榜、概念热度、板块主力资金流、两融余额、海外主要指数与国内期货主力合约（globalMarkets字段）、完整连板梯队（limitLadder字段，含涨停原因与封单金额）、事件情报（热门股/龙虎榜/飙升/异动）",
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"parameters": {"type": "object", "properties": {}, "required": []}
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}
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},
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{
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"type": "function",
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"function": {
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"name": "get_theme_history",
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"description": "获取指定交易日的题材涨幅排行前20",
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"parameters": {
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"type": "object",
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"properties": {
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"date": {"type": "string", "description": "交易日 YYYY-MM-DD"}
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},
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"required": ["date"]
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}
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}
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},
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{
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"type": "function",
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"function": {
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"name": "get_active_core_stocks",
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"description": "获取活跃核心股列表，包含最近10日涨幅矩阵和所属题材",
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"parameters": {"type": "object", "properties": {}, "required": []}
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}
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},
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{
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"type": "function",
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"function": {
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"name": "get_consecutive_core_stocks",
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"description": "获取连续上榜的核心股列表（近3日及以上连续上榜），用于识别持续活跃的热点股",
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"parameters": {
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"type": "object",
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"properties": {
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"min_days": {"type": "integer", "description": "最小连续天数，默认3"}
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},
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"required": []
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}
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}
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},
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{
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"type": "function",
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"function": {
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"name": "get_stock_quote",
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"description": "获取单只股票实时行情（价格、涨跌幅、成交量、换手率等）",
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"parameters": {
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"type": "object",
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"properties": {
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"code": {"type": "string", "description": "6位股票代码，如 600519"}
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},
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"required": ["code"]
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}
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}
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},
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{
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"type": "function",
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"function": {
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"name": "get_fund_flow",
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"description": "获取个股资金流向数据（主力净流入、超大单/大单/中单/小单流入流出）",
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"parameters": {
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"type": "object",
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"properties": {
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"code": {"type": "string", "description": "6位股票代码"},
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"name": {"type": "string", "description": "股票名称"},
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"days": {"type": "integer", "description": "获取天数，默认30"}
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},
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"required": ["code", "name"]
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}
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}
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},
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{
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"type": "function",
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"function": {
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"name": "get_news",
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"description": "获取最近的财经快讯（新浪7x24，含宏观/行业/公司/海外动态），用于重要消息面梳理",
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"parameters": {
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"type": "object",
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"properties": {
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"limit": {"type": "integer", "description": "获取条数，默认30，最大50"}
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},
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"required": []
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}
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}
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}
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]
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async def execute_tool(tool_name: str, arguments: dict) -> str:
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"""执行工具调用，返回 JSON 字符串"""
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try:
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if tool_name == "get_market_dashboard":
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return await _get_market_dashboard()
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elif tool_name == "get_theme_history":
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return await _get_theme_history(arguments.get("date", ""))
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elif tool_name == "get_active_core_stocks":
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return await _get_active_core_stocks()
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elif tool_name == "get_consecutive_core_stocks":
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return await _get_consecutive_core_stocks(arguments.get("min_days", 3))
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elif tool_name == "get_stock_quote":
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return await _get_stock_quote(arguments.get("code", ""))
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elif tool_name == "get_fund_flow":
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return await _get_fund_flow(
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arguments.get("code", ""),
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arguments.get("name", ""),
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arguments.get("days", 30)
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)
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elif tool_name == "get_news":
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return await _get_news(arguments.get("limit", 30))
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else:
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return json.dumps({"error": f"未知工具: {tool_name}"})
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except Exception as e:
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return json.dumps({"error": str(e)})
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async def _get_news(limit: int = 30) -> str:
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"""获取财经快讯"""
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from services.market_extra import fetch_news
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news = await fetch_news(limit)
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if not news:
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return json.dumps({"error": "快讯获取失败或暂无数据"}, ensure_ascii=False)
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return json.dumps({"count": len(news), "items": news}, ensure_ascii=False)
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async def _get_market_dashboard() -> str:
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"""获取市场看板数据"""
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from routes.market_dashboard import _build_dashboard
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data = await _build_dashboard()
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return json.dumps(data, ensure_ascii=False, default=str)
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async def _get_theme_history(date: str) -> str:
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"""获取指定交易日题材涨幅前20"""
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from database import get_connection
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conn = get_connection()
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try:
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rows = conn.execute(
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"SELECT * FROM daily_top_themes WHERE trade_date = ? ORDER BY rank ASC",
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(date,)
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).fetchall()
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items = [dict(r) for r in rows]
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return json.dumps({"date": date, "items": items}, ensure_ascii=False)
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finally:
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conn.close()
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async def _get_active_core_stocks() -> str:
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"""获取活跃核心股列表"""
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from database import get_connection
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from datetime import date as date_cls
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conn = get_connection()
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try:
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# 最近10个有数据的交易日
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rows = conn.execute(
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"SELECT DISTINCT trade_date FROM daily_core_stocks ORDER BY trade_date DESC LIMIT 10"
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).fetchall()
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dates = [r["trade_date"] for r in reversed(rows)]
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if not dates:
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return json.dumps({"dates": [], "stocks": []}, ensure_ascii=False)
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placeholders = ",".join("?" * len(dates))
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rows = conn.execute(
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f"""SELECT trade_date, stock_code, stock_name, f3, cover_count FROM daily_core_stocks
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WHERE trade_date IN ({placeholders})
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ORDER BY trade_date DESC, rank ASC""",
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dates,
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).fetchall()
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stock_days = {}
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for r in rows:
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code = r["stock_code"]
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s = stock_days.setdefault(code, {
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"stockCode": code,
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"stockName": r["stock_name"],
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"coverCount": r["cover_count"],
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"dailyGains": {},
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"appearCount": 0,
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"lastAppear": None,
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})
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s["dailyGains"][r["trade_date"]] = r["f3"]
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s["appearCount"] += 1
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if s["lastAppear"] is None or r["trade_date"] > s["lastAppear"]:
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s["lastAppear"] = r["trade_date"]
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# 只保留最近10日中出现次数最多的前25只（全量可达145KB，会把上下文撑爆）
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stocks = sorted(stock_days.values(), key=lambda x: -x["appearCount"])[:25]
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keep_codes = {s["stockCode"] for s in stocks}
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themes_rows = conn.execute(
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f"""SELECT stock_code, theme_code, theme_name FROM daily_core_stock_themes
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WHERE trade_date IN ({placeholders})""",
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dates,
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).fetchall()
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themes_by_stock = {}
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for t in themes_rows:
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if t["stock_code"] not in keep_codes:
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continue
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per = themes_by_stock.setdefault(t["stock_code"], {})
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per.setdefault(t["theme_code"], {"theme_code": t["theme_code"], "theme_name": t["theme_name"]})
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for s in stocks:
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s["themes"] = list(themes_by_stock.get(s["stockCode"], {}).values())[:5]
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latest = dates[-1] if dates else None
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for s in stocks:
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if s.get("lastAppear") and latest:
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try:
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d1 = date_cls.fromisoformat(latest)
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d2 = date_cls.fromisoformat(s["lastAppear"])
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s["daysSinceLastAppear"] = (d1 - d2).days
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except ValueError:
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s["daysSinceLastAppear"] = 0
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else:
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s["daysSinceLastAppear"] = 0
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return json.dumps({"dates": dates, "stocks": stocks}, ensure_ascii=False)
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finally:
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conn.close()
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async def _get_consecutive_core_stocks(min_days: int = 3) -> str:
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"""获取连续上榜的核心股列表"""
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from database import get_connection
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conn = get_connection()
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try:
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# 最近30个有数据的交易日
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rows = conn.execute(
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"SELECT DISTINCT trade_date FROM daily_core_stocks ORDER BY trade_date DESC LIMIT 30"
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).fetchall()
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all_dates = [r["trade_date"] for r in reversed(rows)]
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if not all_dates:
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return json.dumps({"dates": [], "stocks": []}, ensure_ascii=False)
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# 查询所有上榜记录
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placeholders = ",".join("?" * len(all_dates))
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rows = conn.execute(
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f"""SELECT trade_date, stock_code, stock_name, f3, cover_count
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FROM daily_core_stocks
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WHERE trade_date IN ({placeholders})
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ORDER BY stock_code, trade_date""",
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all_dates,
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).fetchall()
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# 按股票分组，记录上榜日期
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stock_dates: dict[str, dict] = {}
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for r in rows:
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code = r["stock_code"]
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s = stock_dates.setdefault(code, {
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"stockCode": code,
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"stockName": r["stock_name"],
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"dates": [],
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"dailyGains": {},
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})
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s["dates"].append(r["trade_date"])
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s["dailyGains"][r["trade_date"]] = r["f3"]
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# 计算连续上榜天数（从最新交易日往回数）
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results = []
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for code, s in stock_dates.items():
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dates_list = sorted(s["dates"])
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# 从最新的日期往回数连续天数
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consecutive = 0
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last_n = []
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for i in range(len(dates_list) - 1, -1, -1):
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if i == len(dates_list) - 1:
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consecutive = 1
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last_n.append(dates_list[i])
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else:
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# 检查是否连续（允许间隔1天非交易日）
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prev_idx = all_dates.index(dates_list[i + 1]) if dates_list[i + 1] in all_dates else -1
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curr_idx = all_dates.index(dates_list[i]) if dates_list[i] in all_dates else -1
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if prev_idx - curr_idx <= 2: # 允许间隔1天
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consecutive += 1
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last_n.append(dates_list[i])
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else:
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break
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if consecutive >= min_days:
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results.append({
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"stockCode": code,
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"stockName": s["stockName"],
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"consecutiveDays": consecutive,
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"recentDates": last_n,
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"dailyGains": {d: s["dailyGains"].get(d) for d in last_n},
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})
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# 按连续天数降序排列
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results.sort(key=lambda x: -x["consecutiveDays"])
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return json.dumps({
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"minDays": min_days,
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"stocks": results[:30],
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}, ensure_ascii=False)
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finally:
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conn.close()
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async def _get_stock_quote(code: str) -> str:
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"""获取个股实时行情"""
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from services.tencent import fetch_quote
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data = await fetch_quote(code)
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if not data:
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return json.dumps({"error": f"未找到股票 {code} 的数据"})
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return json.dumps(data, ensure_ascii=False)
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async def _get_fund_flow(code: str, name: str, days: int) -> str:
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"""获取个股资金流向"""
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from services.tencent import fetch_quote, get_market_prefix
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from database import get_connection
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# 先尝试从本地数据库获取历史资金流向
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conn = get_connection()
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try:
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rows = conn.execute(
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"SELECT * FROM cache WHERE key LIKE ? AND expires_at > datetime('now','localtime')",
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(f"fund_flow:{code}%",)
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).fetchall()
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if rows:
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return rows[0]["value"]
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finally:
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conn.close()
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# 降级：通过腾讯获取基础行情数据
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quote = await fetch_quote(code)
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if not quote:
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return json.dumps({"error": f"未找到股票 {code} 的数据"})
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return json.dumps({
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"code": code,
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"name": name or quote.get("name", ""),
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"currentPrice": quote.get("currentPrice", 0),
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"changePercent": quote.get("changePercent", 0),
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"volume": quote.get("volume", 0),
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"amount": quote.get("amount", 0),
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"note": "资金流向详细数据需通过东方财富API获取"
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}, ensure_ascii=False)
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