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app.py

@@ -52,13 +52,13 @@ def predict_sales_batch():
     input_data = pd.read_csv(file)
 
     # Make predictions for the batch data and convert raw predictions into a readable format
-    predictions = [model.predict(input_data.drop("Product_Id",axis=1)).tolist()]
+    predictions = model.predict(input_data.drop("Product_Id",axis=1)).tolist()
 
     prod_id_list = input_data.Product_Id.values.tolist()
     output_dict = dict(zip(prod_id_list, predictions))
 
-    return output_dict
+    return jsonify(output_dict)
 
 # Run the Flask app in debug mode
 if __name__ == '__main__':
-    app.run(debug=True)
+    sales_forecast_api.run(debug=True, host="0.0.0.0", port=7860)

requirements.txt

@@ -7,5 +7,3 @@ Werkzeug==2.2.2
 flask==2.2.2
 gunicorn==20.1.0
 requests==2.28.1
-uvicorn[standard]
-streamlit==1.43.2