Update app.py

app.py

@@ -649,73 +649,6 @@ def transcribe_function_whisper(audio):
 
 
 
-# with gr.Blocks(theme='Pijush2023/scikit-learn-pijush') 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")
-            
-#             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 !!!", placeholder="After Prompt, click Retriever Only")
-#             chat_msg = chat_input.submit(add_message, [chatbot, chat_input], [chatbot, chat_input], api_name="voice_query")
-#             tts_choice = gr.Radio(label="Select TTS System", choices=["Alpha", "Beta", "Gamma"], value="Alpha")
-#             retriever_button = gr.Button("Retriever")
-
-           
-            
-#             gr.Markdown("<h1 style='color: red;'>Radar Map</h1>", elem_id="Map-Radar")
-#             location_output = gr.HTML()
-#             retriever_button.click(fn=add_message, inputs=[chatbot, chat_input], outputs=[chatbot, chat_input]).then(
-#                 fn=bot, inputs=[chatbot, choice, tts_choice, state], outputs=[chatbot, gr.Audio(interactive=False, autoplay=True)], api_name="Ask_Retriever").then(
-#                 fn=show_map_if_details, inputs=[chatbot, choice], outputs=[location_output, location_output], api_name="map_finder").then(
-#                 fn=clear_state_and_textbox, inputs=[], outputs=[chat_input])
-            
-#             bot_msg = chat_msg.then(bot, [chatbot, choice, tts_choice], [chatbot], api_name="generate_voice_response")
-#             bot_msg.then(lambda: gr.Textbox(value="", interactive=True, placeholder="Ask Radar!!!...", show_label=False), None, [chat_input])
-#             chatbot.like(print_like_dislike, None, None)
-#             clear_button = gr.Button("Clear")
-#             clear_button.click(fn=clear_textbox, inputs=None, outputs=chat_input)
-            
-#             # Recorder section
-            
-#             gr.Markdown("<h2>Hey Radar</h2>")
-#             audio_input = gr.Audio(sources=["microphone"], type='numpy')
-#             transcribe_button = gr.Button("Transcribe")
-#             transcribe_button.click(fn=transcribe_and_update_textbox, inputs=[audio_input], outputs=[chat_input],api_name="voice_to_text")
-
-            
-
-#             # Streaming ASR component
-#             gr.Markdown("<h2>Hey Radar ASR</h2>")
-#             stream_audio_input = gr.Audio(sources=["microphone"], type='numpy', streaming=True)
-#             stream_transcription = gr.State(None)  # Initialize stream state
-#             stream_audio_input.change(transcribe_function, inputs=[stream_transcription, stream_audio_input], outputs=[stream_transcription, chat_input])
-
-            
-
-            
-
-#         # with gr.Column():
-#         #      weather_output = gr.HTML(value=fetch_local_weather())
-#         #      news_output = gr.HTML(value=fetch_local_news())
-#         #      news_output = gr.HTML(value=fetch_local_events())
-           
-#         with gr.Column():
-#             image_output_1 = gr.Image(value=generate_image(hardcoded_prompt_1), width=400, height=400)
-#             image_output_2 = gr.Image(value=generate_image(hardcoded_prompt_2), width=400, height=400)
-#             image_output_3 = gr.Image(value=generate_image(hardcoded_prompt_3), width=400, height=400)
-
-#             refresh_button = gr.Button("Refresh Images")
-#             refresh_button.click(fn=update_images, inputs=None, outputs=[image_output_1, image_output_2, image_output_3])
-#             # location_output = gr.HTML()
-#             bot_msg.then(show_map_if_details, [chatbot, choice], [location_output, location_output], api_name="map_finder")
-    
-# demo.queue()
-# demo.launch(share=True)
-
 def clear_stream_transcription():
     return None, ""