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| import gradio as gr | |
| import src.srf_bot as sb | |
| import prompts.system_prompts as sp | |
| from langchain_core.messages import HumanMessage | |
| # Initialize the chatbot | |
| chatbot = sb.SRFChatbot() | |
| # Dictionary to store passages with identifiers | |
| retrieved_passages = {} | |
| # Define the respond function | |
| def respond(query, history): | |
| formatted_query = [HumanMessage(content=query)] | |
| # Invoke the chatbot | |
| result = chatbot.graph.invoke({"messages": formatted_query}, chatbot.config) | |
| # Extract the assistant's response | |
| response = result["messages"][-1].content | |
| # Retrieve passages from your vector database based on the query | |
| # For the example, we'll use dummy passages | |
| passages = [ | |
| "This is the full text of Passage 1.", | |
| "This is the full text of Passage 2.", | |
| "This is the full text of Passage 3." | |
| ] | |
| # Store passages with identifiers | |
| passage_ids = [] | |
| for idx, passage in enumerate(passages): | |
| identifier = f"Passage {idx+1}" | |
| retrieved_passages[identifier] = passage | |
| passage_ids.append(identifier) | |
| # Reference passages in the response | |
| linked_response = f"{response}\n\nReferences:" | |
| for pid in passage_ids: | |
| linked_response += f" [{pid}]" | |
| # Append to history | |
| history.append((query, linked_response)) | |
| return history, "" | |
| # Function to get passage content based on selection | |
| def get_passage_content(passage_id): | |
| return retrieved_passages.get(passage_id, "Passage not found.") | |
| # Function to update the system prompt | |
| def update_system_prompt(selected_prompt): | |
| # Update the chatbot's system prompt | |
| chatbot.reset_system_prompt(selected_prompt) | |
| # Update the displayed system prompt text | |
| return sp.system_prompt_templates[selected_prompt] | |
| # Gradio interface | |
| with gr.Blocks() as demo: | |
| gr.Markdown("# SRF Chatbot") | |
| with gr.Row(): | |
| with gr.Column(scale=4): | |
| # Chatbot interface | |
| chatbot_output = gr.Chatbot() | |
| user_input = gr.Textbox(placeholder="Type your question here...", label="Your Question") | |
| submit_button = gr.Button("Submit") | |
| with gr.Column(scale=1): | |
| # Dropdown to select system prompts | |
| system_prompt_dropdown = gr.Dropdown( | |
| choices=list(sp.system_prompt_templates.keys()), | |
| label="Select Chatbot Instructions", | |
| value=list(sp.system_prompt_templates.keys())[0] | |
| ) | |
| # Display the selected system prompt | |
| system_prompt_display = gr.Textbox( | |
| value=sp.system_prompt_templates[list(sp.system_prompt_templates.keys())[0]], | |
| label="Current Chatbot Instructions", | |
| lines=5, | |
| interactive=False | |
| ) | |
| # Update system prompt display when a new prompt is selected | |
| system_prompt_dropdown.change( | |
| fn=update_system_prompt, | |
| inputs=[system_prompt_dropdown], | |
| outputs=[system_prompt_display] | |
| ) | |
| # Passage selection and display | |
| gr.Markdown("### References") | |
| passage_selector = gr.Dropdown(label="Select a passage to view", choices=[]) | |
| passage_display = gr.Markdown() | |
| # Update the chatbot when the submit button is clicked | |
| submit_button.click( | |
| fn=respond, | |
| inputs=[user_input, chatbot_output], | |
| outputs=[chatbot_output, user_input] | |
| ) | |
| # Update the passage selector options when the chatbot output changes | |
| def update_passage_selector(chat_history): | |
| # Get the latest passages | |
| choices = list(retrieved_passages.keys()) | |
| return gr.update(choices=choices) | |
| chatbot_output.change( | |
| fn=update_passage_selector, | |
| inputs=[chatbot_output], | |
| outputs=[passage_selector] | |
| ) | |
| # Display the selected passage | |
| passage_selector.change( | |
| fn=get_passage_content, | |
| inputs=[passage_selector], | |
| outputs=[passage_display] | |
| ) | |
| demo.launch() | |