Update app.py

app.py

@@ -1,33 +1,49 @@
-import gradio as gr
-from transformers import AutoConfig
+# Import necessary libraries
+import gradio as gr  # Gradio is used to create web interfaces for Python scripts.
+from transformers import AutoConfig  # AutoConfig is from the Hugging Face Transformers library, used to create configuration for various models.
 
-# Initialize with some common models
+# A list of model names to start with. These are names of popular models from the Hugging Face library.
 model_list = ["bert-base-uncased", "gpt2", "distilbert-base-uncased"]
 
+# Function to add a new model to the list.
 def add_model_to_list(new_model):
+    # Check if the new model is not already in the list and is not an empty string.
     if new_model and new_model not in model_list:
-        model_list.append(new_model)
+        model_list.append(new_model)  # Add the new model to the list.
     return model_list
-    allow_custom_value=True
 
+# Function to create a configuration for the selected model.
 def create_config(model_name, num_labels, use_cache):
+    # If the selected model is not in the list, add it (this is a safety check).
     if model_name not in model_list:
         model_list.append(model_name)
+    # Create a configuration for the selected model using AutoConfig.
     config = AutoConfig.from_pretrained(model_name, num_labels=num_labels, use_cache=use_cache)
-    return str(config)
+    return str(config)  # Return the configuration as a string.
 
+# Start building the Gradio interface
 with gr.Blocks() as demo:
-    gr.Markdown("## Config Class - Transformers")
-    with gr.Row():
-        model_dropdown = gr.Dropdown(label="Select a Model", choices=model_list, value=model_list[0],   allow_custom_value=True)
+    gr.Markdown("## Config Class - Transformers")  # Display a title for the web interface.
+    with gr.Row():  # Create a row in the interface to organize elements horizontally.
+        # Dropdown menu to select a model.
+        model_dropdown = gr.Dropdown(label="Select a Model", choices=model_list, value=model_list[0], allow_custom_value=True)
+        # Textbox for users to input a new model name.
         new_model_input = gr.Textbox(label="Add a New Model", placeholder="Enter model name")
+        # Button to add the new model to the dropdown list.
         add_model_button = gr.Button("Add Model")
+    # Numeric input for the number of labels (used in the model configuration).
     num_labels_input = gr.Number(label="Number of Labels", value=2)
+    # Checkbox for users to decide whether to use caching.
     use_cache_input = gr.Checkbox(label="Use Cache", value=True)
-    output_area = gr.Textbox(label="Config Output")  # Removed readonly=True
+    # Textbox to display the generated configuration.
+    output_area = gr.Textbox(label="Config Output")
+    # Button to create the configuration.
     submit_button = gr.Button("Create Config")
 
+    # When the "Add Model" button is clicked, call `add_model_to_list` function.
     add_model_button.click(fn=add_model_to_list, inputs=new_model_input, outputs=model_dropdown)
+    # When the "Create Config" button is clicked, call `create_config` function.
     submit_button.click(fn=create_config, inputs=[model_dropdown, num_labels_input, use_cache_input], outputs=output_area)
 
+# Launch the Gradio interface.
 demo.launch()