52 lines
2.0 KiB
Python
52 lines
2.0 KiB
Python
"""AI意图分析模块"""
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import json
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import re
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import logging
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from typing import Dict
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logger = logging.getLogger(__name__)
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class AIAnalyzer:
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def __init__(self, claude_client):
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self.claude_client = claude_client
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self.model = "claude-sonnet-4-20250514"
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async def analyze_intent(self, user_input: str) -> Dict:
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prompt = f"""分析Telegram群组搜索需求，生成3-5个搜索建议。
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用户输入："{user_input}"
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可用命令：/search /text /human /topchat
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返回JSON：{{"explanation":"说明","suggestions":[{{"command":"/text","keyword":"关键词","description":"描述","icon":"💬"}}]}}"""
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try:
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response = self.claude_client.messages.create(
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model=self.model,
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max_tokens=1000,
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messages=[{"role": "user", "content": prompt}]
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)
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ai_response = response.content[0].text.strip()
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json_match = re.search(r'```json\s*(.*?)\s*```', ai_response, re.DOTALL)
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if json_match:
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ai_response = json_match.group(1)
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analysis = json.loads(ai_response)
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return self._validate(analysis, user_input)
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except Exception as e:
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logger.error(f"AI分析失败: {e}")
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return self._fallback(user_input)
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def _validate(self, analysis, user_input):
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if 'suggestions' not in analysis:
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raise ValueError("缺少suggestions")
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return analysis
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def _fallback(self, user_input):
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return {
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"explanation": f"为您搜索「{user_input}」",
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"suggestions": [
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{"command": "/search", "keyword": user_input, "description": f"按名称:{user_input}", "icon": "🔍"},
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{"command": "/text", "keyword": user_input, "description": f"按内容:{user_input}", "icon": "💬"},
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{"command": "/topchat", "keyword": "", "description": "浏览热门", "icon": "🔥"}
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]
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}
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