Create main.py

main.py

@@ -0,0 +1,90 @@
+from fastapi import FastAPI
+from fastapi.responses import JSONResponse, StreamingResponse
+from pydantic import BaseModel
+import types
+import json
+from pydantic import validator
+from endpoint_handler import EndpointHandler  # your handler file
+import base64
+
+app = FastAPI()
+
+handler = None
+
+@app.on_event("startup")
+async def load_handler():
+    global handler
+    handler = EndpointHandler()
+
+class PredictInput(BaseModel):
+    image: str       # base64-encoded image string
+    question: str
+    stream: bool = False
+
+    @validator("question")
+    def question_not_empty(cls, v):
+        if not v.strip():
+            raise ValueError("Question must not be empty")
+        return v
+
+    @validator("image")
+    def valid_base64_and_size(cls, v):
+        try:
+            decoded = base64.b64decode(v, validate=True)
+        except Exception:
+            raise ValueError("`image` must be valid base64")
+        if len(decoded) > 10 * 1024 * 1024:  # 10 MB limit
+            raise ValueError("Image exceeds 10 MB after decoding")
+        return v
+
+class PredictRequest(BaseModel):
+    inputs: PredictInput
+
+@app.get("/")
+async def root():
+    return {"message": "FastAPI app is running on Hugging Face"}
+
+@app.post("/predict")
+async def predict_endpoint(payload: PredictRequest):
+    """
+    Handles prediction requests by processing the input payload and returning the prediction result.
+    Args:
+        payload (PredictRequest): The request payload containing the input data for prediction, including image, question, and stream flag.
+    Returns:
+        JSONResponse: If a ValueError occurs, returns a JSON response with an error message and status code 400.
+        JSONResponse: If any other exception occurs, returns a JSON response with a generic error message and status code 500.
+        StreamingResponse: If the prediction result is a generator (streaming), returns a streaming response with event-stream media type, yielding prediction chunks as JSON.
+    Notes:
+        - Logs the received question for debugging purposes.
+        - Handles both standard and streaming prediction results.
+        - Structured JSON messages are sent to indicate the end of the stream or errors during streaming.
+    """
+    print(f"[Request] Received question: {payload.inputs.question}")
+    
+    data = {
+        "inputs": {
+            "image": payload.inputs.image,
+            "question": payload.inputs.question,
+            "stream": payload.inputs.stream
+        }
+    }
+    
+    try:
+        result = handler.predict(data)
+    except ValueError as ve:
+        return JSONResponse({"error": str(ve)}, status_code=400)
+    except Exception as e:
+        return JSONResponse({"error": "Internal server error"}, status_code=500)
+
+    if isinstance(result, types.GeneratorType):
+        def event_stream():
+            try:
+                for chunk in result:
+                    yield f"data: {json.dumps(chunk)}\n\n"
+                # Return structured JSON to indicate end of stream
+                yield f"data: {json.dumps({'end': True})}\n\n"
+            except Exception as e:
+                # Return structured JSON to indicate error
+                yield f"data: {json.dumps({'error': str(e)})}\n\n"
+    return StreamingResponse(event_stream(), media_type="text/event-stream")
+