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main.py

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+from fastapi import FastAPI, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel
+import httpx
+import os
+
+app = FastAPI(title="Phishing Detection API")
+
+# CORS
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["https://phishing-detector-frontend-eight.vercel.app"],  # Allow all origins for now
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# Configuration
+HF_TOKEN = os.getenv("HF_TOKEN")
+HF_MODEL_ID = os.getenv("HF_MODEL_ID", "swathi6016/phishing-detector1")
+HF_API_URL = f"https://api-inference.huggingface.co/models/{HF_MODEL_ID}"
+
+# Pydantic model for request validation
+class URLRequest(BaseModel):
+    url: str
+
+@app.get("/")
+async def root():
+    """Root endpoint"""
+    return {
+        "message": "Phishing Detection API",
+        "status": "running",
+        "model": "DistilBERT via HuggingFace",
+        "endpoints": {
+            "check": "POST /check",
+            "health": "GET /health",
+            "docs": "GET /docs"
+        }
+    }
+
+@app.get("/health")
+async def health():
+    """Health check"""
+    return {
+        "status": "healthy",
+        "model": HF_MODEL_ID,
+        "hf_token_set": bool(HF_TOKEN)
+    }
+
+@app.post("/check")
+async def check_url(request: URLRequest):
+    """Check if URL is phishing"""
+    
+    if not HF_TOKEN:
+        raise HTTPException(
+            status_code=500,
+            detail="HF_TOKEN not configured"
+        )
+    
+    url = request.url.strip()
+    if not url:
+        raise HTTPException(status_code=400, detail="URL is required")
+    
+    try:
+        headers = {"Authorization": f"Bearer {HF_TOKEN}"}
+        payload = {"inputs": url}
+        
+        async with httpx.AsyncClient(timeout=30.0) as client:
+            response = await client.post(HF_API_URL, headers=headers, json=payload)
+            
+            if response.status_code == 503:
+                raise HTTPException(
+                    status_code=503,
+                    detail="Model is loading. Please try again in 20 seconds."
+                )
+            
+            if response.status_code != 200:
+                raise HTTPException(
+                    status_code=response.status_code,
+                    detail=f"HuggingFace API error: {response.text}"
+                )
+            
+            result = response.json()
+            
+            # Parse response
+            if isinstance(result, list) and len(result) > 0:
+                predictions = result[0] if isinstance(result[0], list) else result
+                
+                phishing_score = 0.0
+                legitimate_score = 0.0
+                
+                for pred in predictions:
+                    label = str(pred.get("label", "")).lower()
+                    score = float(pred.get("score", 0.0))
+                    
+                    if "1" in label or "phishing" in label:
+                        phishing_score = score
+                    elif "0" in label or "legitimate" in label or "legit" in label:
+                        legitimate_score = score
+                
+                is_phishing = phishing_score > legitimate_score
+                confidence = max(phishing_score, legitimate_score)
+                
+                if phishing_score > 0.8:
+                    risk_level = "HIGH RISK"
+                elif phishing_score > 0.5:
+                    risk_level = "MEDIUM RISK"
+                else:
+                    risk_level = "LOW RISK"
+                
+                return {
+                    "url": url,
+                    "is_phishing": is_phishing,
+                    "phishing_probability": phishing_score,
+                    "legitimate_probability": legitimate_score,
+                    "confidence": confidence,
+                    "prediction": "PHISHING" if is_phishing else "LEGITIMATE",
+                    "risk_level": risk_level
+                }
+            else:
+                raise HTTPException(
+                    status_code=500,
+                    detail="Unexpected response format from model"
+                )
+    
+    except httpx.TimeoutException:
+        raise HTTPException(status_code=504, detail="Request timeout")
+    except httpx.RequestError as e:
+        raise HTTPException(status_code=500, detail=f"Connection error: {str(e)}")
+    except HTTPException:
+        raise
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Error: {str(e)}")
+
+if __name__ == "__main__":
+    import uvicorn
+    port = int(os.environ.get("PORT", 8000))
+    uvicorn.run(app, host="0.0.0.0", port=port)

requirements.txt

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+fastapi==0.104.1
+uvicorn[standard]==0.24.0
+httpx==0.25.1
+pydantic==2.5.0
+python-dotenv==1.0.0