Update app.py

app.py

@@ -18,12 +18,39 @@ pipe = pipeline(
     device=device,
 )
 
+@spaces.GPU
+def respond_to_question(transcript, question):
+    # Optionally, use OpenAI API to generate a response to the user's question
+    # based on the transcript
+    response = ""
+    # Replace this with your OpenAI API key
+    openai.api_key = os.environ["OPENAI_API_KEY"]
+    response = openai.Completion.create(
+        engine="gpt-4o-mini",
+        prompt=f"Transcript: {transcript}\n\nUser: {question}\n\nAI:",
+        temperature=0.3,
+        max_tokens=60,
+        top_p=1,
+        frequency_penalty=0,
+        presence_penalty=0
+    ).choices[0].text
+    return response
+    
+@spaces.GPU
+def audio_transcribe(inputs):
+    if inputs is None:
+        raise gr.Error("No audio file submitted! Please upload or record an audio file before submitting your request.")
+
+    text = pipe(inputs, batch_size=BATCH_SIZE, return_timestamps=True)["text"]
+
+    return  text
+
 with gr.Blocks() as transcriberUI:
     gr.Markdown(
         """
         # Ola!
-        Clicar no botao abaixo para selecionar o Audio a ser transcrito!
-        Ambiente Demo disponivel 24x7. Running on ZeroGPU with openai/whisper-large-v3
+        Clique no botao abaixo para selecionar o Audio que deseja conversar!
+        Ambiente disponivel 24x7. Running on ZeroGPU with openai/whisper-large-v3
         """
     )
     inp = gr.File(label="Arquivo de Audio", show_label=True, type="filepath", file_count="single", file_types=["mp3"])
@@ -32,33 +59,6 @@ with gr.Blocks() as transcriberUI:
     response_output = gr.Textbox(label="Response", visible=True)
     submit_question = gr.Button("Submit question", visible=True)
 
-    @spaces.GPU
-    def respond_to_question(transcript, question):
-        # Optionally, use OpenAI API to generate a response to the user's question
-        # based on the transcript
-        response = ""
-        # Replace this with your OpenAI API key
-        openai.api_key = os.environ["OPENAI_API_KEY"]
-        response = openai.Completion.create(
-            engine="gpt-4o-mini",
-            prompt=f"Transcript: {transcript}\n\nUser: {question}\n\nAI:",
-            temperature=0.3,
-            max_tokens=60,
-            top_p=1,
-            frequency_penalty=0,
-            presence_penalty=0
-        ).choices[0].text
-        return response
-        
-    @spaces.GPU
-    def audio_transcribe(inputs):
-        if inputs is None:
-            raise gr.Error("No audio file submitted! Please upload or record an audio file before submitting your request.")
-
-        text = pipe(inputs, batch_size=BATCH_SIZE, return_timestamps=True)["text"]
-    
-        return  text
-
     def ask_question_callback(transcription,question):
         if ask_question:
             response = respond_to_question(transcription, question)