Create api.py

api.py

@@ -0,0 +1,32 @@
+from fastapi import FastAPI
+from pydantic import BaseModel
+from inference import predict
+
+app = FastAPI(title="Your Model API", version="1.0.0")
+
+class PredictionRequest(BaseModel):
+    text: str
+
+class PredictionResponse(BaseModel):
+    prediction: dict
+    status: str
+
+@app.get("/")
+def read_root():
+    return {"message": "Your Model API is running!"}
+
+@app.post("/predict", response_model=PredictionResponse)
+async def predict_endpoint(request: PredictionRequest):
+    try:
+        result = predict(request.text)
+        return PredictionResponse(
+            prediction=result,
+            status="success"
+        )
+    except Exception as e:
+        return PredictionResponse(
+            prediction={},
+            status=f"error: {str(e)}"
+        )
+
+# Run with: uvicorn api:app --host 0.0.0.0 --port 8000