yama commited on
Commit
7943b58
·
1 Parent(s): 6006f4b

Update app.py

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Files changed (1) hide show
  1. app.py +20 -2
app.py CHANGED
@@ -26,6 +26,7 @@ import wave
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  import contextlib
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  from transformers import pipeline
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  import psutil
 
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  whisper_models = ["tiny", "base", "small", "medium", "large-v1", "large-v2"]
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  source_languages = {
@@ -351,6 +352,22 @@ def speech_to_text(video_file_path, selected_source_lang, whisper_model, num_spe
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  raise RuntimeError("Error Running inference with local model", e)
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  # ---- Gradio Layout -----
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  # Inspiration from https://huggingface.co/spaces/RASMUS/Whisper-youtube-crosslingual-subtitles
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  video_in = gr.Video(label="Video file", mirror_webcam=False)
@@ -375,7 +392,7 @@ openai_prompt_in = gr.TextArea(label="openai_prompt", value="""会議の文字
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  - 会議の目的
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  - 会議の内容
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  - 会議の結果""")
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- transcription_summary = gr.Textbox(label="summary")
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  title = "Whisper speaker diarization"
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  demo = gr.Blocks(title=title)
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  demo.encrypt = False
@@ -445,7 +462,8 @@ with demo:
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  transcription_df.render()
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  openai_key_in.render()
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  openai_prompt_in.render()
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- transcription_summary.render()
 
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  system_info.render()
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  gr.Markdown(
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  '''<center><img src='https://visitor-badge.glitch.me/badge?page_id=WhisperDiarizationSpeakers' alt='visitor badge'><a href="https://opensource.org/licenses/Apache-2.0"><img src='https://img.shields.io/badge/License-Apache_2.0-blue.svg' alt='License: Apache 2.0'></center>''')
 
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  import contextlib
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  from transformers import pipeline
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  import psutil
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+ import openai
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  whisper_models = ["tiny", "base", "small", "medium", "large-v1", "large-v2"]
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  source_languages = {
 
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  raise RuntimeError("Error Running inference with local model", e)
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+ def create_transcription_summary(openai_key, prompt):
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+ openai.api_key = openai_key
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+ system_template = prompt
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+
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+ transcript_text = ""
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+ completion = openai.ChatCompletion.create(
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+ model="gpt-3.5-turbo",
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+ messages=[
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+ {"role": "system", "content": system_template},
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+ {"role": "user", "content": transcript_text}
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+ ]
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+ )
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+ transcript_summary = completion.choices[0].message.content
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+ return transcript_summary
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+
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+
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  # ---- Gradio Layout -----
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  # Inspiration from https://huggingface.co/spaces/RASMUS/Whisper-youtube-crosslingual-subtitles
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  video_in = gr.Video(label="Video file", mirror_webcam=False)
 
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  - 会議の目的
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  - 会議の内容
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  - 会議の結果""")
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+ transcription_summary_out = gr.Textbox(label="transcription_summary")
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  title = "Whisper speaker diarization"
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  demo = gr.Blocks(title=title)
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  demo.encrypt = False
 
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  transcription_df.render()
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  openai_key_in.render()
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  openai_prompt_in.render()
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+ transcription_summary_btn = gr.Button("Evaluate and analyze transcription content")
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+ transcription_summary_out.render()
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  system_info.render()
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  gr.Markdown(
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  '''<center><img src='https://visitor-badge.glitch.me/badge?page_id=WhisperDiarizationSpeakers' alt='visitor badge'><a href="https://opensource.org/licenses/Apache-2.0"><img src='https://img.shields.io/badge/License-Apache_2.0-blue.svg' alt='License: Apache 2.0'></center>''')