Fix FastAPI app with proper Pydantic models

app.py

@@ -1,10 +1,13 @@
 import pickle
+from typing import List
 
 import numpy as np
 from fastapi import FastAPI
+from pydantic import BaseModel
 
 app = FastAPI()
 
+# Load model and encoder
 with open("model.pkl", "rb") as f:
     model = pickle.load(f)
 
@@ -12,9 +15,23 @@ with open("label_encoder.pkl", "rb") as f:
     le = pickle.load(f)
 
 
-@app.post("/predict")
-def predict(embedding: np.ndarray):
-    embedding = embedding.reshape(1, -1)
+class EmbeddingInput(BaseModel):
+    embedding: List[float]
+
+
+class PredictionOutput(BaseModel):
+    result: str
+
+
+@app.post("/predict", response_model=PredictionOutput)
+def predict(data: EmbeddingInput):
+    embedding = np.array(data.embedding).reshape(1, -1)
     pred = model.predict(embedding)
     pred_class = le.inverse_transform(pred)[0]
     return {"result": pred_class}
+
+
+@app.get("/")
+def read_root():
+    return {"message": "OpenMP Loop Classifier API", "status": "running"}
+