Update app.py

app.py

@@ -82,61 +82,61 @@ def transcribe(inputs, task):
     text = asr_pl(asr_inputs, batch_size=BATCH_SIZE, generate_kwargs={"task": task}, return_timestamps=True)["text"]
     return  text
 
-demo = gr.Blocks()
-audio_input = gr.Audio(sources="microphone", type="filepath", label="Audio: from microphone") #gr.Audio(sources="upload", type="filepath", label="Audio: from file")
-audio_input_choice = gr.Radio(["audio file", "microphone"], label="Audio", value="audio file")
-task_input_choice = gr.Radio(["transcribe", "translate"], label="Task", value="transcribe")
-
-transcribe_interface = gr.Interface(
-    fn=transcribe,
-    inputs=[
-        audio_input,
-        audio_input_choice,
-        task_input_choice,
-    ],
-    outputs="text",
-    title=application_title,
-    description=application_description,
-    allow_flagging="never",
-)
-
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-
-chatbot_sys_output = gr.Textbox(value="You are a friendly Chatbot.", label="System message")
-chatbot_max_tokens = gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens")
-chatbot_temperature = gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature")
-chatbot_top_p = gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        )
-
-chat_interface = gr.ChatInterface(
-    respond,
-    title=application_title,
-    description=application_description,
-    additional_inputs=[
-        chatbot_sys_output,
-        chatbot_max_tokens,
-        chatbot_temperature,
-        chatbot_top_p,
-    ],
-)
-
 def update_audio_input(audio_input_choice):
     if audio_input_choice == "audio file":
         return gr.Audio(sources="upload", type="filepath", label="Audio: from file")
     elif audio_input_choice == "microphone":
         return gr.Audio(sources="microphone", type="filepath", label="Audio: from microphone")
 
-audio_input_choice.change(update_audio_input, audio_input_choice, audio_input)
-with demo:
+
+with gr.Blocks() as demo:
+    audio_input = gr.Audio(sources="microphone", type="filepath", label="Audio: from microphone") #gr.Audio(sources="upload", type="filepath", label="Audio: from file")
+    audio_input_choice = gr.Radio(["audio file", "microphone"], label="Audio", value="audio file")
+    task_input_choice = gr.Radio(["transcribe", "translate"], label="Task", value="transcribe")
+    
+    transcribe_interface = gr.Interface(
+        fn=transcribe,
+        inputs=[
+            audio_input,
+            audio_input_choice,
+            task_input_choice,
+        ],
+        outputs="text",
+        title=application_title,
+        description=application_description,
+        allow_flagging="never",
+    )
+    
+    
+    """
+    For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
+    """
+    
+    chatbot_sys_output = gr.Textbox(value="You are a friendly Chatbot.", label="System message")
+    chatbot_max_tokens = gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens")
+    chatbot_temperature = gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature")
+    chatbot_top_p = gr.Slider(
+                minimum=0.1,
+                maximum=1.0,
+                value=0.95,
+                step=0.05,
+                label="Top-p (nucleus sampling)",
+            )
+    
+    chat_interface = gr.ChatInterface(
+        respond,
+        title=application_title,
+        description=application_description,
+        additional_inputs=[
+            chatbot_sys_output,
+            chatbot_max_tokens,
+            chatbot_temperature,
+            chatbot_top_p,
+        ],
+    )
+
     gr.TabbedInterface([transcribe_interface, chat_interface], ["Step 1: Transcribe", "Step 2: Extract"])
+    audio_input_choice.change(update_audio_input, audio_input_choice, audio_input)
 
 if __name__ == "__main__":
     demo.queue().launch() #demo.launch()