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| # Import Gradio for UI, along with other necessary libraries | |
| import gradio as gr | |
| from rag_app.agents.react_agent import agent_executor | |
| from config import db | |
| # need to import the qa! | |
| db.create_new_session() | |
| def add_text(history, text): | |
| """Function to add a new input to the chat history | |
| Return: return_description | |
| """ | |
| # Append the new text to the history with a placeholder for the response | |
| history = history + [(text, None)] | |
| return history, "" | |
| def bot(history): | |
| """Function representing the bot's response mechanism | |
| """ | |
| # Obtain the response from the 'infer' function using the latest input | |
| response = infer(history[-1][0], history) | |
| #sources = [doc.metadata.get("source") for doc in response['source_documents']] | |
| #src_list = '\n'.join(sources) | |
| #print_this = response['result'] + "\n\n\n Sources: \n\n\n" + src_list | |
| #history[-1][1] = print_this #response['answer'] | |
| # Update the history with the bot's response | |
| history[-1][1] = response['output'] | |
| return history | |
| def infer(question, history): | |
| """Function to infer the response using the RAG model | |
| """ | |
| # Use the question and history to query the RAG model | |
| try: | |
| result = agent_executor.invoke( | |
| { | |
| "input": question, | |
| "chat_history": history | |
| } | |
| ) | |
| return result | |
| except Exception: | |
| raise gr.Error("Model is Overloaded, Please retry later!") | |
| # CSS styling for the Gradio interface | |
| css = """ | |
| #col-container {max-width: 700px; margin-left: auto; margin-right: auto;} | |
| """ | |
| # HTML content for the Gradio interface title | |
| title = """ | |
| <div style="text-align:left;"> | |
| <p>Hello, I BotTina 2.0, your intelligent AI assistant. I can help you explore Wuerttembergische Versicherungs products.<br /> | |
| </div> | |
| """ | |
| # Building the Gradio interface | |
| with gr.Blocks(theme=gr.themes.Soft()) as demo: | |
| with gr.Column(elem_id="col-container"): | |
| gr.HTML(title) # Add the HTML title to the interface | |
| chatbot = gr.Chatbot([], elem_id="chatbot", | |
| label="BotTina 2.0", | |
| bubble_full_width=False, | |
| avatar_images=(None, "https://dacodi-production.s3.amazonaws.com/store/87bc00b6727589462954f2e3ff6f531c.png"), | |
| height=680,) # Initialize the chatbot component | |
| clear = gr.Button("Clear") # Add a button to clear the chat | |
| # Create a row for the question input | |
| with gr.Row(): | |
| question = gr.Textbox(label="Question", placeholder="Type your question and hit Enter ") | |
| # Define the action when the question is submitted | |
| question.submit(add_text, [chatbot, question], [chatbot, question], queue=False).then( | |
| bot, chatbot, chatbot | |
| ) | |
| # Define the action for the clear button | |
| clear.click(lambda: None, None, chatbot, queue=False) | |
| # Launch the Gradio demo interface | |
| demo.launch(share=False, debug=True) |