Mattral commited on
Commit
bd7b4bf
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1 Parent(s): 6ddaa62

Update app.py

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Files changed (1) hide show
  1. app.py +5 -4
app.py CHANGED
@@ -21,6 +21,9 @@ system_prompt_text = (
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  # Function to transcribe audio input
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  def transcribe(audio):
 
 
 
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  sr, y = audio
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  # Convert to mono if stereo
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  if y.ndim > 1:
@@ -72,7 +75,7 @@ def check_rand(inp, val):
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  else:
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  return gr.Slider(label="Seed", minimum=1, maximum=1111111111111111, value=int(val))
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- with gr.Blocks() as app: # Add auth here
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  gr.HTML("""<center><h1 style='font-size:xx-large;'>PTT Chatbot</h1><br><h3>running on Huggingface Inference</h3><br><h7>EXPERIMENTAL</center>""")
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  with gr.Row():
@@ -98,11 +101,9 @@ with gr.Blocks() as app: # Add auth here
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  top_p = gr.Slider(label="Top-P", step=0.01, minimum=0.01, maximum=1.0, value=0.9)
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  rep_p = gr.Slider(label="Repetition Penalty", step=0.1, minimum=0.1, maximum=2.0, value=1.0)
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- hid1 = gr.Number(value=1, visible=False)
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-
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  def handle_chat(audio_input, chat_history, seed, temp, tokens, top_p, rep_p):
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  user_message = transcribe(audio_input) # Transcribe audio to text
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- if not user_message: # Check for empty or error in recognition
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  return chat_history, "Sorry, I couldn't understand that."
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  response_gen = chat_inf(user_message, chat_history, seed, temp, tokens, top_p, rep_p)
 
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  # Function to transcribe audio input
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  def transcribe(audio):
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+ if audio is None:
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+ return None # Handle case where audio input is None
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+
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  sr, y = audio
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  # Convert to mono if stereo
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  if y.ndim > 1:
 
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  else:
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  return gr.Slider(label="Seed", minimum=1, maximum=1111111111111111, value=int(val))
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+ with gr.Blocks() as app:
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  gr.HTML("""<center><h1 style='font-size:xx-large;'>PTT Chatbot</h1><br><h3>running on Huggingface Inference</h3><br><h7>EXPERIMENTAL</center>""")
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  with gr.Row():
 
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  top_p = gr.Slider(label="Top-P", step=0.01, minimum=0.01, maximum=1.0, value=0.9)
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  rep_p = gr.Slider(label="Repetition Penalty", step=0.1, minimum=0.1, maximum=2.0, value=1.0)
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  def handle_chat(audio_input, chat_history, seed, temp, tokens, top_p, rep_p):
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  user_message = transcribe(audio_input) # Transcribe audio to text
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+ if user_message is None or user_message == "": # Check for empty or error in recognition
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  return chat_history, "Sorry, I couldn't understand that."
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  response_gen = chat_inf(user_message, chat_history, seed, temp, tokens, top_p, rep_p)