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Update app.py
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app.py
CHANGED
@@ -65,14 +65,8 @@ rag_chain = (
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| StrOutputParser()
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# Simple logic to generate follow-up questions dynamically
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# You can replace this with a more sophisticated model-based approach
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return [
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f"What more can you tell me about {response.split()[0]}?",
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f"Can you elaborate on {response.split()[-1]}?",
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]
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@@ -81,28 +75,13 @@ def rag_chain_response(messages, user_message):
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# Generate a response using the RAG chain
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response = rag_chain.invoke(user_message)
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# Generate follow-up questions based on the response
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follow_ups = generate_follow_ups(response)
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# Append the user's message and the response to the chat
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messages.append((user_message, response))
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# Return the updated chat
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return messages,
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# Function to handle follow-up clicks
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def follow_up_click(messages, follow_up_question):
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# Treat the follow-up question as the user query
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response = rag_chain.invoke(follow_up_question)
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# Generate new follow-ups based on the new response
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follow_ups = generate_follow_ups(response)
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# Append the follow-up question and response to the chat
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messages.append((follow_up_question, response))
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# Return the updated chat and follow-up questions
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return messages, follow_ups
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@@ -113,25 +92,17 @@ with gr.Blocks(theme="rawrsor1/Everforest") as app:
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chatbot = gr.Chatbot([], elem_id="RADAR", bubble_full_width=False)
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question_input = gr.Textbox(label="Ask a Question", placeholder="Type your question here...")
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submit_btn = gr.Button("Submit")
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follow_up_btns = gr.ButtonGroup(label="Follow-Up Questions", buttons=[""] * 2)
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# Set up interaction for both Enter key and Submit button
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question_input.submit(
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rag_chain_response, # Function to handle input and generate response
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inputs=[chatbot, question_input], # Pass current conversation state and user input
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outputs=[chatbot,
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)
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submit_btn.click(
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rag_chain_response, # Function to handle input and generate response
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inputs=[chatbot, question_input], # Pass current conversation state and user input
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outputs=[chatbot,
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)
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# Handle follow-up button clicks
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follow_up_btns.click(
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follow_up_click,
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inputs=[chatbot, follow_up_btns],
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outputs=[chatbot, follow_up_btns]
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)
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# Launch the Gradio app
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| StrOutputParser()
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)
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# Generate a response using the RAG chain
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response = rag_chain.invoke(user_message)
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# Append the user's message and the response to the chat
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messages.append((user_message, response))
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# Return the updated chat and clear the input box
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return messages, ""
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chatbot = gr.Chatbot([], elem_id="RADAR", bubble_full_width=False)
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question_input = gr.Textbox(label="Ask a Question", placeholder="Type your question here...")
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submit_btn = gr.Button("Submit")
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# Set up interaction for both Enter key and Submit button
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question_input.submit(
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rag_chain_response, # Function to handle input and generate response
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inputs=[chatbot, question_input], # Pass current conversation state and user input
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outputs=[chatbot, question_input] # Update conversation state and clear the input
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)
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submit_btn.click(
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rag_chain_response, # Function to handle input and generate response
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inputs=[chatbot, question_input], # Pass current conversation state and user input
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outputs=[chatbot, question_input] # Update conversation state and clear the input
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)
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# Launch the Gradio app
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