erroneous file

.py

@@ -1,99 +0,0 @@
-import gradio as gr
-import openai
-import examples as chatbot_examples
-
-# Define a function to get the AI's reply using the OpenAI API
-def get_ai_reply(model, system_message, message, history_state):
-    # Initialize the messages list with the system message
-    messages = [{"role": "system", "content": system_message}]
-    
-    # Add the conversation history to the messages list
-    messages += history_state
-    
-    # Add the user's message to the messages list
-    messages += [{"role": "user", "content": message}]
-    
-    # Make an API call to the OpenAI ChatCompletion endpoint with the model and messages
-    completion = openai.ChatCompletion.create(
-        model=model,
-        messages=messages
-    )
-    
-    # Extract and return the AI's response from the API response
-    return completion.choices[0].message.content
-
-# Define a function to handle the chat interaction with the AI model
-def chat(model, system_message, message, chatbot_messages, history_state):
-    # Initialize chatbot_messages and history_state if they are not provided
-    chatbot_messages = chatbot_messages or []
-    history_state = history_state or []
-    
-    # Try to get the AI's reply using the get_ai_reply function
-    try:
-        ai_reply = get_ai_reply(model, system_message, message, history_state)
-    except:
-        # If an error occurs, return None and the current chatbot_messages and history_state
-        return None, chatbot_messages, history_state
-    
-    # Append the user's message and the AI's reply to the chatbot_messages list
-    chatbot_messages.append((message, ai_reply))
-    
-    # Append the user's message and the AI's reply to the history_state list
-    history_state.append({"role": "user", "content": message})
-    history_state.append({"role": "assistant", "content": ai_reply})
-    
-    # Return None (empty out the user's message textbox), the updated chatbot_messages, and the updated history_state
-    return None, chatbot_messages, history_state
-
-# Define a function to launch the chatbot interface using Gradio
-def launch_chatbot(additional_examples=[], share=False):
-    # Load chatbot examples and merge with any additional examples provided
-    examples = chatbot_examples.load_examples(additional=additional_examples)
-    
-    # Define a function to get the names of the examples
-    def get_examples():
-        return [example["name"] for example in examples]
-
-    # Define a function to choose an example based on the index
-    def choose_example(index):
-        system_message = examples[index]["system_message"].strip()
-        user_message = examples[index]["message"].strip()
-        return system_message, user_message, [], []
-
-    # Create the Gradio interface using the Blocks layout
-    with gr.Blocks() as demo:
-        with gr.Tab("Conversation"):
-            with gr.Row():
-                with gr.Column():
-                    # Create a dropdown to select examples
-                    example_dropdown = gr.Dropdown(get_examples(), label="Examples", type="index")
-                    # Create a button to load the selected example
-                    example_load_btn = gr.Button(value="Load")
-                    # Create a textbox for the system message (prompt)
-                    system_message = gr.Textbox(label="System Message (Prompt)", value="You are a helpful assistant.")
-                with gr.Column():
-                    # Create a dropdown to select the AI model
-                    model_selector = gr.Dropdown(
-                        ["gpt-3.5-turbo", "gpt-4"],
-                        label="Model",
-                        value="gpt-3.5-turbo"
-                    )
-                    # Create a chatbot interface for the conversation
-                    chatbot = gr.Chatbot(label="Conversation")
-                    # Create a textbox for the user's message
-                    message = gr.Textbox(label="Message")
-                    # Create a state object to store the conversation history
-                    history_state = gr.State()
-                    # Create a button to send the user's message
-                    btn = gr.Button(value="Send")
-
-                # Connect the example load button to the choose_example function
-                example_load_btn.click(choose_example, inputs=[example_dropdown], outputs=[system_message, message, chatbot, history_state])
-                # Connect the send button to the chat function
-                btn.click(chat, inputs=[model_selector, system_message, message, chatbot, history_state], outputs=[message, chatbot, history_state])
-        # Launch the Gradio interface
-        demo.launch(share=share)
-        
-# Call the launch_chatbot function to start the chatbot interface using Gradio
-# Set the share parameter to False, meaning the interface will not be publicly accessible
-launch_chatbot(share=False)