Create app.py

app.py

@@ -0,0 +1,28 @@
+from fastapi import FastAPI, HTTPException, Request
+from transformers import pipeline
+import os
+
+app = FastAPI()
+
+# Load your model
+classifier = pipeline('sentiment-analysis')
+
+# Define your API key (in a real application, use environment variables or a secret manager)
+API_KEY = os.getenv("API_KEY", "your-default-api-key")
+
+@app.middleware("http")
+async def api_key_middleware(request: Request, call_next):
+    api_key = request.headers.get("X-API-KEY")
+    if api_key != API_KEY:
+        raise HTTPException(status_code=403, detail="Could not validate API key")
+    response = await call_next(request)
+    return response
+
+@app.post("/predict")
+async def predict(text: str):
+    result = classifier(text)
+    return result
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=8000)