Update app.py

app.py

@@ -1481,59 +1481,123 @@ files_list = [
     "178041_000197000852_V2.pdf"
 ]
 
+def generate_table_html(responses):
+    # HTML structure for the table
+    table_html = """
+    <h2>Top 3 Responses</h2>
+    <table style="width:100%; border-collapse: collapse; border: 1px solid black;">
+        <tr>
+            <th style="border: 1px solid black; padding: 8px;">Container (Document Name)</th>
+            <th style="border: 1px solid black; padding: 8px;">Page Number</th>
+            <th style="border: 1px solid black; padding: 8px;">Response</th>
+            <th style="border: 1px solid black; padding: 8px;">Metadata</th>
+        </tr>
+    """
 
+    for response in responses[:3]:  # Limiting to top 3 responses
+        document_name = response.get("document_name", "Unknown")
+        page_number = response.get("page_number", "Unknown")
+        content = response.get("content", "No content available")
+        metadata = response.get("metadata", "No metadata available")
+
+        # Adding rows dynamically to the table
+        table_html += f"""
+        <tr>
+            <td style="border: 1px solid black; padding: 8px;">{document_name}</td>
+            <td style="border: 1px solid black; padding: 8px;">{page_number}</td>
+            <td style="border: 1px solid black; padding: 8px;">{content}</td>
+            <td style="border: 1px solid black; padding: 8px;">{metadata}</td>
+        </tr>
+        """
 
+    # Closing the table
+    table_html += "</table>"
+    return table_html
 
 
-with gr.Blocks(theme='gradio/soft') as demo:
+def generate_bot_response_with_table(history, choice, retrieval_mode, model_choice):
+    if not history:
+        return
+
+    # Select the model
+    selected_model = chat_model if model_choice == "LM-1" else (chat_model1 if model_choice == "LM-3" else phi_pipe)
+
+    response, addresses = generate_answer(history[-1][0], choice, retrieval_mode, selected_model)
+
+    # Extract relevant information from the response to create table content
+    responses = []
+    for doc in response[:3]:  # Limiting to top 3 results
+        responses.append({
+            "document_name": doc.get("document_name", "Unknown"),
+            "page_number": doc.get("page_number", "Unknown"),
+            "content": doc.get("content", "No content available"),
+            "metadata": doc.get("metadata", "No metadata available")
+        })
+
+    # Generate the HTML for the table
+    table_html = generate_table_html(responses)
+
+    history[-1][1] = ""
+
+    for character in response:
+        history[-1][1] += character
+        yield history, table_html  # Yielding history and table HTML for real-time updates
+
+    yield history, table_html  # Final yield with the complete response and table
+
+
+
+
+
+# with gr.Blocks(theme='gradio/soft') as demo:
 
    
-    with gr.Row():
-        with gr.Column():
-            state = gr.State()
+#     with gr.Row():
+#         with gr.Column():
+#             state = gr.State()
 
-            # File dropdown
-            # file_dropdown = gr.Dropdown(label="Select Document", choices=files_list, value=None)
+#             # File dropdown
+#             # file_dropdown = gr.Dropdown(label="Select Document", choices=files_list, value=None)
 
-            chatbot = gr.Chatbot([], elem_id="RADAR:Channel 94.1", bubble_full_width=False)
-            choice = gr.Radio(label="Select Style", choices=["Details", "Conversational"], value="Conversational",interactive=False,visible=False)
-            retrieval_mode = gr.Radio(label="Retrieval Mode", choices=["VDB", "KGF"], value="VDB",interactive=False,visible=False)
-            model_choice = gr.Dropdown(label="Choose Model", choices=["LM-2"], value="LM-2")
+#             chatbot = gr.Chatbot([], elem_id="RADAR:Channel 94.1", bubble_full_width=False)
+#             choice = gr.Radio(label="Select Style", choices=["Details", "Conversational"], value="Conversational",interactive=False,visible=False)
+#             retrieval_mode = gr.Radio(label="Retrieval Mode", choices=["VDB", "KGF"], value="VDB",interactive=False,visible=False)
+#             model_choice = gr.Dropdown(label="Choose Model", choices=["LM-2"], value="LM-2")
 
-            # Link the dropdown change to handle_model_choice_change
-            model_choice.change(fn=handle_model_choice_change, inputs=model_choice, outputs=[retrieval_mode, choice, choice])
+#             # Link the dropdown change to handle_model_choice_change
+#             model_choice.change(fn=handle_model_choice_change, inputs=model_choice, outputs=[retrieval_mode, choice, choice])
 
-            # gr.Markdown("<h1 style='color: red;'>Talk to RADAR</h1>", elem_id="voice-markdown")
+#             # gr.Markdown("<h1 style='color: red;'>Talk to RADAR</h1>", elem_id="voice-markdown")
 
-            chat_input = gr.Textbox(show_copy_button=True, interactive=True, show_label=False, label="ASK Radar !!!")
-            tts_choice = gr.Radio(label="Select TTS System", choices=["Alpha", "Beta"], value="Alpha")
+#             chat_input = gr.Textbox(show_copy_button=True, interactive=True, show_label=False, label="ASK Radar !!!")
+#             tts_choice = gr.Radio(label="Select TTS System", choices=["Alpha", "Beta"], value="Alpha")
         
-            retriever_button = gr.Button("Retriever")
+#             retriever_button = gr.Button("Retriever")
 
-            clear_button = gr.Button("Clear")
-            clear_button.click(lambda: [None, None], outputs=[chat_input, state])
+#             clear_button = gr.Button("Clear")
+#             clear_button.click(lambda: [None, None], outputs=[chat_input, state])
 
-            # gr.Markdown("<h1 style='color: red;'>Radar Map</h1>", elem_id="Map-Radar")
-            # location_output = gr.HTML()
-            audio_output = gr.Audio(interactive=False, autoplay=True)
+#             # gr.Markdown("<h1 style='color: red;'>Radar Map</h1>", elem_id="Map-Radar")
+#             # location_output = gr.HTML()
+#             audio_output = gr.Audio(interactive=False, autoplay=True)
 
-            def stop_audio():
-                audio_output.stop()
-                return None
+#             def stop_audio():
+#                 audio_output.stop()
+#                 return None
 
                
     
            
 
-            retriever_sequence = (
-                retriever_button.click(fn=stop_audio, inputs=[], outputs=[audio_output], api_name="api_stop_audio_recording")
-                .then(fn=add_message, inputs=[chatbot, chat_input], outputs=[chatbot, chat_input], api_name="api_addprompt_chathistory")
-                # First, generate the bot response
-                .then(fn=generate_bot_response, inputs=[chatbot, choice, retrieval_mode, model_choice], outputs=[chatbot], api_name="api_generate_bot_response")
-                # Then, generate the TTS response based on the bot's response
-                .then(fn=generate_tts_response, inputs=[chatbot, tts_choice], outputs=[audio_output], api_name="api_generate_tts_response")
-                .then(fn=clear_textbox, inputs=[], outputs=[chat_input], api_name="api_clear_textbox")
-            )
+#             retriever_sequence = (
+#                 retriever_button.click(fn=stop_audio, inputs=[], outputs=[audio_output], api_name="api_stop_audio_recording")
+#                 .then(fn=add_message, inputs=[chatbot, chat_input], outputs=[chatbot, chat_input], api_name="api_addprompt_chathistory")
+#                 # First, generate the bot response
+#                 .then(fn=generate_bot_response, inputs=[chatbot, choice, retrieval_mode, model_choice], outputs=[chatbot], api_name="api_generate_bot_response")
+#                 # Then, generate the TTS response based on the bot's response
+#                 .then(fn=generate_tts_response, inputs=[chatbot, tts_choice], outputs=[audio_output], api_name="api_generate_tts_response")
+#                 .then(fn=clear_textbox, inputs=[], outputs=[chat_input], api_name="api_clear_textbox")
+#             )
 
 
 
@@ -1542,17 +1606,17 @@ with gr.Blocks(theme='gradio/soft') as demo:
 
             
 
-            chat_input.submit(fn=stop_audio, inputs=[], outputs=[audio_output], api_name="api_stop_audio_recording").then(
-                fn=add_message, inputs=[chatbot, chat_input], outputs=[chatbot, chat_input], api_name="api_addprompt_chathistory"
-            ).then(
-                # First, generate the bot response
-                fn=generate_bot_response, inputs=[chatbot, choice, retrieval_mode, model_choice], outputs=[chatbot], api_name="api_generate_bot_response"
-            ).then(
-                # Then, generate the TTS response based on the bot's response
-                fn=generate_tts_response, inputs=[chatbot, tts_choice], outputs=[audio_output], api_name="api_generate_tts_response"
-            ).then(
-                fn=clear_textbox, inputs=[], outputs=[chat_input], api_name="api_clear_textbox"
-            )
+#             chat_input.submit(fn=stop_audio, inputs=[], outputs=[audio_output], api_name="api_stop_audio_recording").then(
+#                 fn=add_message, inputs=[chatbot, chat_input], outputs=[chatbot, chat_input], api_name="api_addprompt_chathistory"
+#             ).then(
+#                 # First, generate the bot response
+#                 fn=generate_bot_response, inputs=[chatbot, choice, retrieval_mode, model_choice], outputs=[chatbot], api_name="api_generate_bot_response"
+#             ).then(
+#                 # Then, generate the TTS response based on the bot's response
+#                 fn=generate_tts_response, inputs=[chatbot, tts_choice], outputs=[audio_output], api_name="api_generate_tts_response"
+#             ).then(
+#                 fn=clear_textbox, inputs=[], outputs=[chat_input], api_name="api_clear_textbox"
+#             )
 
 
 
@@ -1560,31 +1624,31 @@ with gr.Blocks(theme='gradio/soft') as demo:
 
 
 
-            audio_input = gr.Audio(sources=["microphone"], streaming=True, type='numpy', every=0.1)
-            audio_input.stream(transcribe_function, inputs=[state, audio_input], outputs=[state, chat_input], api_name="api_voice_to_text")
+#             audio_input = gr.Audio(sources=["microphone"], streaming=True, type='numpy', every=0.1)
+#             audio_input.stream(transcribe_function, inputs=[state, audio_input], outputs=[state, chat_input], api_name="api_voice_to_text")
             
-        #     gr.Markdown("<h1 style='color: red;'>Example Prompts</h1>", elem_id="Example-Prompts")
-        #     gr.Examples(examples=examples, fn=insert_prompt,inputs=chat_input, outputs=chat_input)
+#         #     gr.Markdown("<h1 style='color: red;'>Example Prompts</h1>", elem_id="Example-Prompts")
+#         #     gr.Examples(examples=examples, fn=insert_prompt,inputs=chat_input, outputs=chat_input)
 
-        # with gr.Column():
-        #     weather_output = gr.HTML(value=fetch_local_weather())
-        #     news_output = gr.HTML(value=fetch_local_news())
-        #     events_output = gr.HTML(value=fetch_local_events())
+#         # with gr.Column():
+#         #     weather_output = gr.HTML(value=fetch_local_weather())
+#         #     news_output = gr.HTML(value=fetch_local_news())
+#         #     events_output = gr.HTML(value=fetch_local_events())
 
-        # with gr.Column():
+#         # with gr.Column():
            
           
-        #     # Call update_images during the initial load to display images when the interface appears
-        #     initial_images = update_images()
+#         #     # Call update_images during the initial load to display images when the interface appears
+#         #     initial_images = update_images()
             
-        #     # Displaying the images generated using Flux API directly
-        #     image_output_1 = gr.Image(value=initial_images[0], label="Image 1", elem_id="flux_image_1", width=400, height=400)
-        #     image_output_2 = gr.Image(value=initial_images[1], label="Image 2", elem_id="flux_image_2", width=400, height=400)
-        #     image_output_3 = gr.Image(value=initial_images[2], label="Image 3", elem_id="flux_image_3", width=400, height=400)
+#         #     # Displaying the images generated using Flux API directly
+#         #     image_output_1 = gr.Image(value=initial_images[0], label="Image 1", elem_id="flux_image_1", width=400, height=400)
+#         #     image_output_2 = gr.Image(value=initial_images[1], label="Image 2", elem_id="flux_image_2", width=400, height=400)
+#         #     image_output_3 = gr.Image(value=initial_images[2], label="Image 3", elem_id="flux_image_3", width=400, height=400)
     
-        #     # Refresh button to update images
-        #     refresh_button = gr.Button("Refresh Images")
-        #     refresh_button.click(fn=update_images, inputs=None, outputs=[image_output_1, image_output_2, image_output_3])
+#         #     # Refresh button to update images
+#         #     refresh_button = gr.Button("Refresh Images")
+#         #     refresh_button.click(fn=update_images, inputs=None, outputs=[image_output_1, image_output_2, image_output_3])
             
 
 
@@ -1592,10 +1656,57 @@ with gr.Blocks(theme='gradio/soft') as demo:
 
            
 
-demo.queue()
-demo.launch(show_error=True)
+# demo.queue()
+# demo.launch(show_error=True)
+
+with gr.Blocks(theme='gradio/soft') as demo:
+
+    with gr.Row():
+        with gr.Column():
+            state = gr.State()
 
+            chatbot = gr.Chatbot([], elem_id="RADAR:Channel 94.1", bubble_full_width=False)
+            choice = gr.Radio(label="Select Style", choices=["Details", "Conversational"], value="Conversational",interactive=False,visible=False)
+            retrieval_mode = gr.Radio(label="Retrieval Mode", choices=["VDB", "KGF"], value="VDB",interactive=False,visible=False)
+            model_choice = gr.Dropdown(label="Choose Model", choices=["LM-2"], value="LM-2")
+
+            # Link the dropdown change to handle_model_choice_change
+            model_choice.change(fn=handle_model_choice_change, inputs=model_choice, outputs=[retrieval_mode, choice, choice])
+
+            chat_input = gr.Textbox(show_copy_button=True, interactive=True, show_label=False, label="ASK Radar !!!")
+            tts_choice = gr.Radio(label="Select TTS System", choices=["Alpha", "Beta"], value="Alpha")
 
+            retriever_button = gr.Button("Retriever")
+            clear_button = gr.Button("Clear")
+            clear_button.click(lambda: [None, None], outputs=[chat_input, state])
+
+            # HTML component for displaying the dynamic table
+            table_output = gr.HTML()
+
+            # Audio output for TTS
+            audio_output = gr.Audio(interactive=False, autoplay=True)
+
+            # Retriever sequence
+            retriever_sequence = (
+                retriever_button.click(fn=stop_audio, inputs=[], outputs=[audio_output], api_name="api_stop_audio_recording")
+                .then(fn=add_message, inputs=[chatbot, chat_input], outputs=[chatbot, chat_input], api_name="api_addprompt_chathistory")
+                .then(fn=generate_bot_response_with_table, inputs=[chatbot, choice, retrieval_mode, model_choice], outputs=[chatbot, table_output], api_name="api_generate_bot_response_with_table")
+                .then(fn=generate_tts_response, inputs=[chatbot, tts_choice], outputs=[audio_output], api_name="api_generate_tts_response")
+                .then(fn=clear_textbox, inputs=[], outputs=[chat_input], api_name="api_clear_textbox")
+            )
+
+            chat_input.submit(fn=stop_audio, inputs=[], outputs=[audio_output], api_name="api_stop_audio_recording").then(
+                fn=add_message, inputs=[chatbot, chat_input], outputs=[chatbot, chat_input], api_name="api_addprompt_chathistory"
+            ).then(
+                fn=generate_bot_response_with_table, inputs=[chatbot, choice, retrieval_mode, model_choice], outputs=[chatbot, table_output], api_name="api_generate_bot_response_with_table"
+            ).then(
+                fn=generate_tts_response, inputs=[chatbot, tts_choice], outputs=[audio_output], api_name="api_generate_tts_response"
+            ).then(
+                fn=clear_textbox, inputs=[], outputs=[chat_input], api_name="api_clear_textbox"
+            )
+
+demo.queue()
+demo.launch(show_error=True)