100 lines
3.0 KiB
Python
100 lines
3.0 KiB
Python
#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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"""
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API路由模块，为前端提供REST API接口
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"""
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import os
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from fastapi import APIRouter, Depends, HTTPException, status, Body
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from typing import Dict, Any, List, Optional
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from pydantic import BaseModel
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import json
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import logging
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from cryptoai.api.deepseek_api import DeepSeekAPI
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from cryptoai.utils.config_loader import ConfigLoader
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from fastapi.responses import StreamingResponse
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from cryptoai.routes.user import get_current_user
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import requests
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from datetime import datetime
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from cryptoai.utils.db_manager import get_db_manager
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# 创建路由
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router = APIRouter()
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class ChatRequest(BaseModel):
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user_prompt: str
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agent_id: str
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@router.get("/list")
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async def get_agents(current_user: Dict[str, Any] = Depends(get_current_user)):
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"""
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获取所有代理
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"""
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return [
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{
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"id": "1",
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"name": "加密货币交易助手",
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"hello_prompt": "您好，我是加密货币交易助手，为您提供专业的数字货币交易分析和建议",
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"description": "帮你分析做加密货币技术分析",
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},
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{
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"id": "2",
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"name": "美股交易助手",
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"hello_prompt": "您好，我是美股交易助手，您可以直接输入股票名称，比如AAPL，然后我会为您提供专业的股票交易分析和建议",
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"description": "帮你分析做美股股票技术分析",
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},
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# {
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# "id": "3",
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# "name": "期货交易助手",
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# "hello_prompt": "您好，我是期货交易助手，为您提供专业的期货交易分析和建议",
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# "description": "帮你分析做期货技术分析",
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# }
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]
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@router.post("/chat")
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async def chat(request: ChatRequest,current_user: Dict[str, Any] = Depends(get_current_user)):
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"""
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聊天接口
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"""
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if request.agent_id == "1":
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token = "app-vhJecqbcLukf72g0uxAb9tcz"
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elif request.agent_id == "2":
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token = "app-FLIYXrCbbQIkwgXx02Y1Mxjg"
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else:
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raise HTTPException(status_code=400, detail="Invalid agent ID")
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inputs = {}
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if request.agent_id == "2":
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inputs = {
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"current_date": datetime.now().strftime("%Y-%m-%d")
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}
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url = "https://mate.aimateplus.com/v1/chat-messages"
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headers = {
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"Authorization": f"Bearer {token}",
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"Content-Type": "application/json"
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}
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data = {
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"inputs" : inputs,
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"query" : request.user_prompt,
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"response_mode" : "streaming",
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"user" : current_user["mail"]
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}
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# 保存用户提问
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get_db_manager().save_user_question(current_user["id"], request.agent_id, request.user_prompt)
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response = requests.post(url, headers=headers, json=data, stream=True)
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#获取response 的 stream
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def stream_response():
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for chunk in response.iter_content(chunk_size=1024):
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if chunk:
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yield chunk
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return StreamingResponse(stream_response(), media_type="text/plain")
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