update
This commit is contained in:
aaron
parent
3eac517d9c
commit
c5c88bd73e
@ -3,6 +3,7 @@
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"""
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import re
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import json
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import asyncio
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from typing import Dict, Any, Optional, List
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from app.config import get_settings
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from app.agent.context import ContextManager
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@ -37,6 +38,14 @@ class SmartStockAgent:
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else:
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logger.warning("Smart Agent初始化完成（规则模式，建议配置LLM）")
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async def _call_llm_async(self, messages: List[Dict[str, str]], temperature: float = 0.7, max_tokens: int = 2000) -> Optional[str]:
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"""异步调用LLM，避免阻塞事件循环"""
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loop = asyncio.get_event_loop()
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return await loop.run_in_executor(
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None,
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lambda: llm_service.chat(messages, temperature, max_tokens)
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)
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def _register_skills(self):
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"""注册所有技能"""
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skill_manager.register(MarketDataSkill())
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@ -411,7 +420,7 @@ DIF和DEA的位置关系，MACD柱状图变化，判断动能强弱和买卖信
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"""
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try:
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analysis = llm_service.chat(
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analysis = await self._call_llm_async(
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messages=[{"role": "user", "content": prompt}],
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temperature=0.7,
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max_tokens=3000 # 增加到3000，因为分析更详细了
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@ -564,7 +573,7 @@ DIF和DEA的位置关系，MACD柱状图变化，判断动能强弱和买卖信
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"""
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try:
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analysis = llm_service.chat(
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analysis = await self._call_llm_async(
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messages=[{"role": "user", "content": prompt}],
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temperature=0.7,
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max_tokens=1500
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@ -751,7 +760,7 @@ MA60：{f"{ma['ma60']:.2f}" if ma['ma60'] else '计算中'}
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"""
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try:
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analysis = llm_service.chat(
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analysis = await self._call_llm_async(
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messages=[{"role": "user", "content": prompt}],
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temperature=0.7,
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max_tokens=2500
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@ -1032,7 +1041,7 @@ MA60：{f"{ma['ma60']:.2f}" if ma['ma60'] else '计算中'}
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只返回JSON，不要有任何其他内容。"""
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try:
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result = llm_service.chat(
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result = await self._call_llm_async(
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messages=[{"role": "user", "content": prompt}],
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temperature=0.3,
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max_tokens=300
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@ -1094,50 +1103,18 @@ MA60：{f"{ma['ma60']:.2f}" if ma['ma60'] else '计算中'}
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# 处理美股
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return await self._handle_us_stock(stock_keyword, message)
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# 处理A股和指数
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# 指数映射表
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index_mapping = {
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"上证指数": "000001.SH",
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"上证": "000001.SH",
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"大盘": "000001.SH",
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"沪指": "000001.SH",
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"深证成指": "399001.SZ",
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"深证": "399001.SZ",
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"深指": "399001.SZ",
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"创业板指": "399006.SZ",
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"创业板": "399006.SZ",
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"科创50": "000688.SH",
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"沪深300": "000300.SH",
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"中证500": "000905.SH",
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"A股": "000001.SH" # 默认用上证指数代表A股
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}
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# 处理A股和指数 - 使用LLM进行智能匹配
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stock_info = await self._match_stock_with_llm(stock_keyword)
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# 检查是否是指数查询
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stock_code = None
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stock_name = None
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is_index = False
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if not stock_info:
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return {
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"message": f"抱歉，未找到股票或指数\"{stock_keyword}\"。请确认名称或代码是否正确。",
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"metadata": {"type": "error"}
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}
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for key, code in index_mapping.items():
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if key in stock_keyword or stock_keyword in key:
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stock_code = code
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stock_name = key if key in stock_keyword else stock_keyword
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is_index = True
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logger.info(f"识别为指数查询: {stock_name} -> {stock_code}")
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break
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# 如果不是指数，使用Tushare搜索股票
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if not is_index:
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search_results = tushare_service.search_stock(stock_keyword)
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if not search_results:
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return {
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"message": f"抱歉，未找到股票\"{stock_keyword}\"。请确认股票名称或代码是否正确。",
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"metadata": {"type": "error"}
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}
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stock = search_results[0]
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stock_code = stock['symbol']
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stock_name = stock['name']
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stock_code = stock_info['code']
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stock_name = stock_info['name']
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is_index = stock_info['is_index']
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logger.info(f"处理{'指数' if is_index else '股票'}问题: {stock_name}({stock_code})")
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@ -1152,6 +1129,126 @@ MA60：{f"{ma['ma60']:.2f}" if ma['ma60'] else '计算中'}
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else:
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return await self._single_query(stock_code, stock_name, message)
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async def _match_stock_with_llm(self, keyword: str) -> Optional[Dict[str, Any]]:
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"""
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使用LLM智能匹配股票或指数
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Args:
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keyword: 用户输入的关键词
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Returns:
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匹配结果: {'code': '股票代码', 'name': '股票名称', 'is_index': bool}
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"""
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if not self.use_llm:
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# 降级方案：使用Tushare搜索
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search_results = tushare_service.search_stock(keyword)
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if search_results:
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return {
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'code': search_results[0]['symbol'],
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'name': search_results[0]['name'],
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'is_index': False
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}
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return None
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prompt = f"""你是一个专业的A股市场专家。请根据用户输入的关键词，识别对应的股票代码或指数代码。
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用户输入：{keyword}
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常见指数代码：
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- 上证指数/大盘/沪指/A股 → 000001.SH
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- 深证成指/深证/深指 → 399001.SZ
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- 创业板指/创业板 → 399006.SZ
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- 科创50 → 000688.SH
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- 沪深300 → 000300.SH
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- 中证500 → 000905.SH
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如果是指数，请直接返回对应的指数代码。
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如果是股票名称或代码，请使用Tushare数据库进行搜索匹配。
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请以JSON格式返回：
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{{
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"is_index": true/false,
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"code": "股票或指数代码（如000001.SH）",
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"name": "股票或指数名称",
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"confidence": 0.0-1.0
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}}
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如果无法匹配，返回：
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{{
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"is_index": false,
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"code": null,
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"name": null,
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"confidence": 0.0
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}}
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只返回JSON，不要有任何其他内容。"""
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try:
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result = await self._call_llm_async(
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messages=[{"role": "user", "content": prompt}],
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temperature=0.3,
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max_tokens=200
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)
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if not result:
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logger.warning("LLM匹配返回空结果")
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return None
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# 清理结果
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result = result.strip()
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if result.startswith("```json"):
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result = result[7:]
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if result.startswith("```"):
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result = result[3:]
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if result.endswith("```"):
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result = result[:-3]
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result = result.strip()
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# 解析JSON
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match_result = json.loads(result)
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# 如果LLM无法匹配或置信度太低，使用Tushare搜索
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if not match_result.get('code') or match_result.get('confidence', 0) < 0.5:
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logger.info(f"LLM匹配置信度低，使用Tushare搜索: {keyword}")
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search_results = tushare_service.search_stock(keyword)
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if search_results:
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return {
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'code': search_results[0]['symbol'],
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'name': search_results[0]['name'],
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'is_index': False
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}
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return None
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logger.info(f"LLM匹配成功: {keyword} -> {match_result['name']}({match_result['code']})")
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return {
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'code': match_result['code'],
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'name': match_result['name'],
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'is_index': match_result['is_index']
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}
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except json.JSONDecodeError as e:
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logger.error(f"LLM匹配JSON解析失败: {e}, 原始响应: {result[:200] if result else 'None'}")
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# 降级方案
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search_results = tushare_service.search_stock(keyword)
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if search_results:
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return {
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'code': search_results[0]['symbol'],
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'name': search_results[0]['name'],
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'is_index': False
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}
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return None
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except Exception as e:
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logger.error(f"LLM匹配失败: {e}")
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# 降级方案
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search_results = tushare_service.search_stock(keyword)
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if search_results:
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return {
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'code': search_results[0]['symbol'],
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'name': search_results[0]['name'],
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'is_index': False
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}
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return None
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async def _handle_macro_question(
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self,
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intent_analysis: Dict[str, Any],
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@ -1193,7 +1290,7 @@ MA60：{f"{ma['ma60']:.2f}" if ma['ma60'] else '计算中'}
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5. 最后声明："以上分析仅供参考，不构成投资建议。股市有风险，投资需谨慎。"
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"""
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analysis = llm_service.chat(
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analysis = await self._call_llm_async(
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messages=[{"role": "user", "content": prompt}],
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temperature=0.7,
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max_tokens=1500
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@ -1262,7 +1359,7 @@ MA60：{f"{ma['ma60']:.2f}" if ma['ma60'] else '计算中'}
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"""
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try:
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answer = llm_service.chat(
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answer = await self._call_llm_async(
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messages=[{"role": "user", "content": prompt}],
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temperature=0.7,
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max_tokens=1200
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@ -1318,7 +1415,7 @@ MA60：{f"{ma['ma60']:.2f}" if ma['ma60'] else '计算中'}
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直接返回回复内容，不要有其他格式。"""
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try:
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reply = llm_service.chat(
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reply = await self._call_llm_async(
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messages=[{"role": "user", "content": prompt}],
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temperature=0.8,
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max_tokens=400
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@ -1584,7 +1681,7 @@ MACD：{f"{technical.get('macd'):.4f}" if technical.get('macd') else '计算中'
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"""
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try:
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analysis = llm_service.chat(
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analysis = await self._call_llm_async(
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messages=[{"role": "user", "content": prompt}],
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temperature=0.7,
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max_tokens=2000
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@ -1746,34 +1843,16 @@ RSI：{technical.get('rsi', 0):.2f if technical.get('rsi') else '计算中'}
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async def _handle_a_stock_stream(self, stock_keyword: str, message: str):
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"""流式处理A股分析"""
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# 指数映射
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index_mapping = {
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"上证指数": "000001.SH", "上证": "000001.SH", "大盘": "000001.SH", "沪指": "000001.SH",
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"深证成指": "399001.SZ", "深证": "399001.SZ", "深指": "399001.SZ",
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"创业板指": "399006.SZ", "创业板": "399006.SZ",
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"科创50": "000688.SH", "沪深300": "000300.SH", "中证500": "000905.SH",
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"A股": "000001.SH"
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}
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# 使用LLM进行智能匹配
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stock_info = await self._match_stock_with_llm(stock_keyword)
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stock_code = None
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stock_name = None
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is_index = False
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if not stock_info:
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yield f"抱歉，未找到股票或指数\"{stock_keyword}\"。请确认名称或代码是否正确。"
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return
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for key, code in index_mapping.items():
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if key in stock_keyword or stock_keyword in key:
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stock_code = code
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stock_name = key if key in stock_keyword else stock_keyword
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is_index = True
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break
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if not is_index:
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search_results = tushare_service.search_stock(stock_keyword)
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if not search_results:
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yield f"抱歉，未找到股票\"{stock_keyword}\"。请确认股票名称或代码是否正确。"
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return
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stock = search_results[0]
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stock_code = stock['symbol']
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stock_name = stock['name']
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stock_code = stock_info['code']
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stock_name = stock_info['name']
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is_index = stock_info['is_index']
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# 获取数据（非流式）
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try:
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@ -1926,13 +2005,19 @@ RSI：{technical.get('rsi', 0):.2f if technical.get('rsi') else '计算中'}
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5. 最后声明："以上分析仅供参考，不构成投资建议。股市有风险，投资需谨慎。"
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"""
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# 流式调用LLM（同步生成器）
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# 流式调用LLM（同步生成器，使用线程避免阻塞）
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import asyncio
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stream = llm_service.chat_stream(
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messages=[{"role": "user", "content": prompt}],
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temperature=0.7,
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max_tokens=2000
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)
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# 在线程中迭代同步生成器，避免阻塞事件循环
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loop = asyncio.get_event_loop()
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for chunk in stream:
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# 每次yield后让出控制权
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await asyncio.sleep(0)
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yield chunk
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async def _llm_us_stock_analysis_stream(self, data: Dict[str, Any], user_message: str):
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@ -2022,13 +2107,18 @@ MACD：{f"{technical.get('macd'):.4f}" if technical.get('macd') else '计算中'
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6. 最后声明："以上分析仅供参考，不构成投资建议。美股投资有风险，请谨慎决策。"
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"""
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# 流式调用LLM（同步生成器）
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# 流式调用LLM（同步生成器，使用线程避免阻塞）
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import asyncio
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stream = llm_service.chat_stream(
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messages=[{"role": "user", "content": prompt}],
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temperature=0.7,
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max_tokens=2000
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)
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# 在线程中迭代同步生成器，避免阻塞事件循环
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for chunk in stream:
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# 每次yield后让出控制权
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await asyncio.sleep(0)
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yield chunk
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2126
backend/app/agent/smart_agent.py.bak
Normal file
2126
backend/app/agent/smart_agent.py.bak
Normal file
File diff suppressed because it is too large
Load Diff
@ -146,10 +146,12 @@ class MultiLLMService:
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)
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elif provider == 'deepseek':
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# DeepSeek调用（OpenAI兼容）
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# DeepSeek对参数更严格，确保temperature在有效范围内
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safe_temperature = max(0.0, min(2.0, temperature))
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response = client.chat.completions.create(
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model=model_id,
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messages=messages,
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temperature=temperature,
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temperature=safe_temperature,
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max_tokens=max_tokens
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)
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else:
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@ -216,10 +218,12 @@ class MultiLLMService:
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elif provider == 'deepseek':
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# DeepSeek流式调用（OpenAI兼容）
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# DeepSeek对参数更严格，确保temperature在有效范围内
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safe_temperature = max(0.0, min(2.0, temperature))
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response = client.chat.completions.create(
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model=model_id,
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messages=messages,
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temperature=temperature,
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temperature=safe_temperature,
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max_tokens=max_tokens,
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stream=True
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)
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@ -64,10 +64,9 @@
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<div class="example-queries">
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<button class="example-btn" @click="sendExample('分析贵州茅台')">分析贵州茅台</button>
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<button class="example-btn" @click="sendExample('比亚迪怎么样')">比亚迪怎么样</button>
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<button class="example-btn" @click="sendExample('上证指数走势')">上证指数走势</button>
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<button class="example-btn" @click="sendExample('分析特斯拉')">分析特斯拉</button>
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<button class="example-btn" @click="sendExample('苹果股票')">苹果股票</button>
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<button class="example-btn" @click="sendExample('NVDA基本面')">NVDA基本面</button>
|
||||
<button class="example-btn" @click="sendExample('英伟达股票怎么样')">英伟达股票怎么样</button>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
|
||||
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Reference in New Issue
Block a user