from fastapi import FastAPI, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
from typing import List, Optional

# 1. Initialize the App
app = FastAPI(
    title="Sentinel AI Backend",
    description="API for Blockchain Monitoring and AI Analysis",
    version="1.0.0"
)

# 2. Enable CORS (Essential for React/Frontend to talk to this API)
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],  # In production, replace "*" with your frontend URL
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

# 3. Define Data Models (Schemas)
class AnalysisRequest(BaseModel):
    tx_hash: str
    network: str = "ethereum"

class AnalysisResponse(BaseModel):
    status: str
    risk_score: float
    threats: List[str]

# 4. Routes/Endpoints
@app.get("/")
async def root():
    return {"message": "Sentinel AI Engine is Online", "port": 7860}

@app.post("/analyze", response_model=AnalysisResponse)
async def analyze_transaction(request: AnalysisRequest):
    try:
        # Business logic goes here (e.g., calling an AI model or scanning a chain)
        return {
            "status": "completed",
            "risk_score": 0.12,
            "threats": []
        }
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))

# 5. Run configuration (For local testing)
if __name__ == "__main__":
    import uvicorn
    # Hugging Face Spaces and most cloud providers expect port 7860 or 8000
    uvicorn.run(app, host="0.0.0.0", port=7860)