Update app.py

app.py

@@ -625,6 +625,26 @@ pipe_asr = pipeline("automatic-speech-recognition", model=model, tokenizer=proce
 
 base_audio_drive = "/data/audio"
 
+# def transcribe_function(stream, new_chunk):
+#     try:
+#         sr, y = new_chunk[0], new_chunk[1]
+#     except TypeError:
+#         print(f"Error chunk structure: {type(new_chunk)}, content: {new_chunk}")
+#         return stream, "", None
+
+#     y = y.astype(np.float32) / np.max(np.abs(y))
+
+#     if stream is not None:
+#         stream = np.concatenate([stream, y])
+#     else:
+#         stream = y
+
+#     result = pipe_asr({"array": stream, "sampling_rate": sr}, return_timestamps=False)
+
+#     full_text = result.get("text")
+    
+#     return stream, full_text, result
+
 def transcribe_function(stream, new_chunk):
     try:
         sr, y = new_chunk[0], new_chunk[1]
@@ -836,8 +856,9 @@ with gr.Blocks(theme='Pijush2023/scikit-learn-pijush') as demo:
             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")
             retriver_button = gr.Button("Retriver")
+            # retriver_button.click(fn=add_message, inputs=[chatbot, chat_input], outputs=[chatbot, chat_input]).then(fn=bot, inputs=[chatbot, choice, tts_choice], outputs=[chatbot],api_name="Ask_Retriever")
             retriver_button.click(fn=add_message, inputs=[chatbot, chat_input], outputs=[chatbot, chat_input]).then(
-            fn=bot, inputs=[chatbot, choice, tts_choice], outputs=[chatbot],api_name="Ask_Retriever")
+                fn=bot, inputs=[chatbot, choice, tts_choice], outputs=[chatbot], api_name="Ask_Retriever")
             #gr.Audio(interactive=False, autoplay=True)]
 
             # voice_response_button = gr.Button("Voice Response")