Upload folder using huggingface_hub

app.py

@@ -40,7 +40,6 @@ def predict_nozzle():
 
     }
 
-
     # Convert the extracted data into a DataFrame
     input_data = pd.DataFrame([sample])
 
@@ -54,11 +53,11 @@ def predict_nozzle():
 # Define an endpoint for batch prediction (POST request)
 @nozzleselect_api.post('/v1/predictbatch')
 def predict_nozzle_batch():
-  
+
     This function handles POST requests to the '/v1/predictbatch' endpoint.
     It expects a CSV file containing property details for multiple properties
     and returns the predicted rental prices as a dictionary in the JSON response.
-    
+
     # Get the uploaded CSV file from the request
     file = request.files['file']
 

requirements.txt

@@ -4,12 +4,12 @@ scikit-learn==1.6.1
 seaborn==0.13.2
 joblib==1.4.2
 xgboost==2.1.4
-joblib==1.4.2
+joblib==1.5.2
 Werkzeug==2.2.2
 flask==2.2.2
 gunicorn==20.1.0
 requests==2.32.3
 uvicorn[standard]
-streamlit==1.43.2
+streamlit==1.49.1
 huggingface_hub==0.20.3
 hf_xet