kcz358 commited on
Commit
143845f
·
1 Parent(s): f3f60d0
Files changed (1) hide show
  1. app.py +2 -2
app.py CHANGED
@@ -2,6 +2,7 @@ import gradio as gr
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  from transformers import AutoModelForCausalLM, AutoProcessor, TextIteratorStreamer
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  import librosa
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  from threading import Thread
 
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  def split_audio(audio_arrays, chunk_limit=480000):
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  CHUNK_LIM = chunk_limit
@@ -24,7 +25,7 @@ def user(audio, text, chat_history):
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  return "", chat_history
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- # Placeholder for your actual LLM processing API call
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  def process_audio(audio, text, chat_history):
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  conversation = [
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  {
@@ -118,7 +119,6 @@ with gr.Blocks() as demo:
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  [
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  ["Please transcribe the audio for me", "./examples/elon_musk.mp3"],
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  ["Please transcribe the audio for me", "./examples/nvidia_conference.mp3"],
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- ["Please transcribe the audio for me", "./examples/nuggets.mp3"],
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  ["Please follow the instruction in the audio", "./examples/audio_instruction.wav"],
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  ["What is the primary instrument featured in the solo of this track?", "./examples/music_under.wav"],
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  ["What weather condition can be heard in the audio?", "./examples/audio_understand.wav"],
 
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  from transformers import AutoModelForCausalLM, AutoProcessor, TextIteratorStreamer
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  import librosa
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  from threading import Thread
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+ import spaces
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  def split_audio(audio_arrays, chunk_limit=480000):
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  CHUNK_LIM = chunk_limit
 
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  return "", chat_history
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+ @spaces.GPU
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  def process_audio(audio, text, chat_history):
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  conversation = [
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  {
 
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  [
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  ["Please transcribe the audio for me", "./examples/elon_musk.mp3"],
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  ["Please transcribe the audio for me", "./examples/nvidia_conference.mp3"],
 
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  ["Please follow the instruction in the audio", "./examples/audio_instruction.wav"],
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  ["What is the primary instrument featured in the solo of this track?", "./examples/music_under.wav"],
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  ["What weather condition can be heard in the audio?", "./examples/audio_understand.wav"],