167 lines
4.8 KiB
Python
167 lines
4.8 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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AI分析API端点
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"""
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from fastapi import APIRouter, HTTPException, Depends
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from fastapi.responses import JSONResponse
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from typing import Dict, Any
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import asyncio
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from datetime import datetime
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import logging
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from ai_service import AIService, get_ai_config
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from api import get_db_connection
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# 创建路由
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router = APIRouter(prefix="/api/ai", tags=["AI分析"])
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# 配置日志
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logger = logging.getLogger(__name__)
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@router.post("/analyze")
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async def analyze_production():
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"""
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分析生产数据
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返回AI生成的生产报表
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"""
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try:
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# 获取数据库连接
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conn = await get_db_connection()
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# 获取最近30天的数据
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query = """
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SELECT
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platform,
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ts_cn,
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batch,
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mac,
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note
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FROM audit_records
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WHERE ts_cn >= datetime('now', '-30 days')
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ORDER BY ts_cn DESC
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"""
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cursor = await conn.execute(query)
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rows = await cursor.fetchall()
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await conn.close()
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# 整理数据
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pdd_data = []
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yt_data = []
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for row in rows:
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record = {
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"ts_cn": row[1],
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"batch": row[2],
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"mac": row[3],
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"note": row[4]
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}
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if row[0] == "pdd":
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pdd_data.append(record)
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elif row[0] == "yt":
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yt_data.append(record)
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# 准备AI分析数据
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data = {
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"pdd": pdd_data,
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"yt": yt_data,
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"analysis_time": datetime.now().isoformat()
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}
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# 调用AI服务
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config = get_ai_config()
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async with AIService(config) as ai_service:
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result = await ai_service.analyze_production_data(data)
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# 添加元数据
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result["metadata"] = {
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"generated_at": datetime.now().isoformat(),
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"data_period": "最近30天",
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"total_records": len(pdd_data) + len(yt_data),
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"ai_provider": config.provider
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}
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return JSONResponse(content=result)
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except Exception as e:
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logger.error(f"AI分析失败: {str(e)}")
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raise HTTPException(status_code=500, detail=f"AI分析失败: {str(e)}")
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@router.get("/config")
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async def get_ai_config_info():
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"""获取AI配置信息（不包含敏感信息）"""
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try:
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config = get_ai_config()
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return {
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"provider": config.provider,
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"model": config.model,
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"configured": bool(config.api_key or config.provider == "local")
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}
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except Exception as e:
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raise HTTPException(status_code=500, detail=str(e))
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@router.post("/test")
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async def test_ai_connection():
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"""测试AI连接"""
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try:
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config = get_ai_config()
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# 测试数据
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test_data = {
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"pdd": [{"ts_cn": datetime.now().strftime("%Y-%m-%d %H:%M:%S"), "batch": "TEST", "mac": "TEST001", "note": "测试数据"}],
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"yt": []
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}
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async with AIService(config) as ai_service:
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result = await ai_service.analyze_production_data(test_data)
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return {
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"success": True,
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"message": "AI连接测试成功",
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"provider": config.provider,
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"model": config.model
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}
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except Exception as e:
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logger.error(f"AI连接测试失败: {str(e)}")
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return {
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"success": False,
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"message": f"AI连接测试失败: {str(e)}",
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"provider": config.provider if 'config' in locals() else "unknown"
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}
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@router.get("/providers")
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async def get_supported_providers():
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"""获取支持的AI提供商列表"""
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return {
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"providers": [
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{
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"id": "openai",
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"name": "OpenAI",
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"models": ["gpt-3.5-turbo", "gpt-4", "gpt-4-turbo"],
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"description": "OpenAI GPT模型，需要API Key"
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},
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{
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"id": "qwen",
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"name": "通义千问",
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"models": ["qwen-turbo", "qwen-plus", "qwen-max"],
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"description": "阿里云通义千问，需要API Key"
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},
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{
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"id": "wenxin",
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"name": "文心一言",
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"models": ["ERNIE-Bot", "ERNIE-Bot-turbo", "ERNIE-Bot-4"],
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"description": "百度文心一言，需要API Key"
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},
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{
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"id": "local",
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"name": "本地模型",
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"models": ["llama2", "llama2:13b", "codellama", "qwen:7b"],
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"description": "本地部署的模型（如Ollama），无需API Key"
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}
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]
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}
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