Update app.py

app.py

@@ -30,7 +30,7 @@ async def predict(model: UploadFile = File(...), data: str = None):
         raise HTTPException(status_code=500, detail=str(e))
 
 @app.post("/retrain")
-async def retrain(model: UploadFile = File(...), data: UploadFile = File(...)):
+async def retrain(model: UploadFile = File(...), data: str = None):
     try:
         # Save the uploaded model and data to temporary files
         with tempfile.NamedTemporaryFile(delete=False, suffix=".h5") as temp_model_file:
@@ -43,7 +43,7 @@ async def retrain(model: UploadFile = File(...), data: UploadFile = File(...)):
 
         # Load the model and data
         model = load_model(temp_model_path, compile=False)
-        dataset = np.load(temp_data_path)
+        dataset = np.array(eval(data)).reshape(1, 12, 1)
 
         # Normalize the data
         scaler = MinMaxScaler()