85 lines
2.1 KiB
Python
85 lines
2.1 KiB
Python
from fastapi import FastAPI, HTTPException, status
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from pydantic import BaseModel
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import uvicorn
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from datetime import datetime
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# Import your trading agents
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from service import enqueue_analysis
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from tradingagents.config import get_config
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config = get_config()
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# Create FastAPI app instance
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app = FastAPI(
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title="TradingAgents API",
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description="API for TradingAgents financial trading framework",
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version="0.1.0"
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)
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class TradingAnalyzeRequest(BaseModel):
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symbol: str
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date: str
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class TradingAnalyzeResponse(BaseModel):
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symbol: str
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date: str
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job_id: str
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timestamp: str
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status: str
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@app.get("/")
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async def root():
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"""Root endpoint"""
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return {"message": "Welcome to TradingAgents API"}
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@app.get("/ping")
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async def ping():
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"""Simple ping endpoint that returns pong"""
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return {"message": "pong"}
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@app.get("/health")
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async def health_check():
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"""Health check endpoint"""
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return {
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"status": "healthy",
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"timestamp": datetime.now().isoformat(),
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"service": "tradingagents-api"
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}
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@app.post("/v1/trading/analyze", response_model=TradingAnalyzeResponse, status_code=status.HTTP_202_ACCEPTED,)
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async def analyze_trading_decision(request: TradingAnalyzeRequest):
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"""
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Analyze trading decision for a given symbol and date
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Example usage:
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POST /trading/analyze
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{
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"symbol": "BTC/USDT",
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"date": "2024-05-10"
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}
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"""
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response = enqueue_analysis(request.symbol, request.date)
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print(f"INFO: Enqueue response: {response}")
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if response.status == "error":
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raise HTTPException(status_code=500, detail=response.message)
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return TradingAnalyzeResponse(
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symbol=request.symbol,
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date=request.date,
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job_id=response.job_id,
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timestamp=datetime.now().isoformat(),
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status=response.status
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)
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if __name__ == "__main__":
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# Run the server
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uvicorn.run(
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"webapp:app",
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host=config.get("APP_HOST", "localhost"),
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port=config.get("APP_PORT", 8000),
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reload=True,
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log_level="info"
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)
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