Update app.py

app.py

@@ -3,7 +3,6 @@ import os
 import openai
 import gradio as gr
 import json
-import csv
 
 # Set the OpenAI API key
 openai.api_key = os.getenv("OPENAI_API_KEY")
@@ -49,21 +48,6 @@ def CustomChatGPT(category, user_input):
     # Return the model's message
     return ChatGPT_reply
 
-# Function to save flagged data to a Hugging Face Dataset using a token
-class HuggingFaceDatasetSaver:
-    def __init__(self, dataset_name, huggingface_token):
-        self.dataset_name = dataset_name
-        self.huggingface_token = huggingface_token
-
-    def save_flagged_data(self, data):
-        from datasets import Dataset, FileSystemDataset
-
-        dataset = Dataset.from_dict(data)
-
-        # Write the dataset to Hugging Face using the provided token
-        fs_dataset = FileSystemDataset(self.dataset_name, data_files={self.dataset_name: dataset}, token=self.huggingface_token)
-        fs_dataset.save_to_disk()
-
 # Define the Gradio interface
 iface = gr.Interface(
     fn=CustomChatGPT, 
@@ -151,7 +135,8 @@ iface = gr.Interface(
     favicon_path="https://assets.bigcartel.com/theme_images/101321509/IMG_6002.png",  # Favicon image URL
     allow_flagging="manual",  # Enable flagging with manual control
     flagging_options=["Incorrect", "Ambiguous"],  # Specify flagging options
-    flagging_callback=HuggingFaceDatasetSaver("CannaTech/Flagged", os.getenv("HF_TOKEN")).save_flagged_data  # Save flagged data to Hugging Face Dataset using token
+    flagging_callback=hf_writer
+    
 )
 
 # Launch the interface with authentication