Update main.py

main.py

@@ -1,5 +1,6 @@
 import base64
-from fastapi import FastAPI, HTTPException, Depends, Header
+import json
+from fastapi import FastAPI, HTTPException, Depends, Header, Request, Body
 from schemas import AudioInput, DetectionResult
 from model_service import get_model_service, ModelService
 
@@ -11,7 +12,8 @@ app = FastAPI(
 
 @app.on_event("startup")
 async def startup_event():
-    get_model_service()
+    # EXTREMELY IMPORTANT: Instant startup to prevent 504 Timeout
+    print("API is starting up...")
 
 API_KEY = "my_secret_key_123"
 
@@ -22,23 +24,52 @@ async def verify_api_key(x_api_key: str = Header(...)):
 
 @app.post("/detect", response_model=DetectionResult)
 async def detect_voice(
-    input_data: AudioInput, 
+    request: Request,
+    # This line ensures the "Request body" box appears in your /docs test page
+    payload: dict = Body(..., example={"audioBase64": "PASTE_BASE64_HERE"}),
     service: ModelService = Depends(get_model_service),
     api_key: str = Depends(verify_api_key)
 ):
     try:
-        audio_b64 = input_data.audio_base64
+        # 1. Flexible parsing for portal compatibility (audioBase64, audio_base_64, etc.)
+        body = await request.json()
+        audio_b64 = None
+        
+        # Check all possible key variants including camelCase for the portal
+        possible_keys = ["audioBase64", "audio_base_64", "audio_base64", "audio", "data", "file"]
+        for k in possible_keys:
+            if k in body and body[k]:
+                audio_b64 = body[k]
+                break
+        
+        # Fallback: search for any long string value
+        if not audio_b64:
+            for v in body.values():
+                if isinstance(v, str) and len(v) > 100:
+                    audio_b64 = v
+                    break
+        
         if not audio_b64:
              raise HTTPException(status_code=422, detail="No audio data found.")
+
+        # 2. Cleanup (Remove Data URI prefix like "data:audio/mp3;base64,")
         if "," in audio_b64:
             audio_b64 = audio_b64.split(",")[1]
+
+        # 3. Decode
         audio_bytes = base64.b64decode(audio_b64)
+        
     except Exception as e:
-        raise HTTPException(status_code=400, detail=f"Parsing error: {str(e)}")
+        raise HTTPException(status_code=400, detail=f"Request parsing error: {str(e)}")
 
     try:
+        # 4. AI Inference (Returns label: HUMAN/AI_GENERATED and score)
         label, confidence = service.predict(audio_bytes)
-        return DetectionResult(label=label, confidence=confidence, message="Analysis successful")
+        return DetectionResult(
+            label=label, 
+            confidence=confidence, 
+            message="Analysis successful"
+        )
     except Exception as e:
         raise HTTPException(status_code=500, detail=f"Model error: {str(e)}")