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Update app.py
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app.py
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import gradio as gr
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import openai
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import whisper
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# Load the Whisper model
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model = whisper.load_model("base")
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# Function to process audio and generate transcription and summary
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def procesare_audio(file):
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# Transcribe audio
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result = model.transcribe(file.name)
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transcriere_text = result["text"]
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# Use OpenAI to summarize the transcription
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openai.api_key = "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"
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response = openai.ChatCompletion.create(
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model="gpt-3.5-turbo",
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messages=[
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{"role": "system", "content": "You are a helpful assistant that summarizes text."},
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{"role": "user", "content": f"Please summarize the following text: {transcriere_text}"}
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]
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)
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rezumat_text = response.choices[0].message.content.strip()
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return transcriere_text, rezumat_text
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# Define the Gradio interface
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interface = gr.Interface(
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fn=procesare_audio,
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inputs=gr.Audio(
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outputs=[
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gr.Textbox(label="Transcrierea textului:"),
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gr.Textbox(label="Rezumatul textului:")
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],
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title="Transcriere și Rezumat AI",
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description="Această aplicație transcrie fișiere audio și creează un rezumat al conținutului folosind AI.",
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theme="compact"
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)
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# Launch the Gradio app
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interface.launch(share=False, debug=True)
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import gradio as gr
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import openai
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import whisper
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# Load the Whisper model
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model = whisper.load_model("base")
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# Function to process audio and generate transcription and summary
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def procesare_audio(file):
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# Transcribe audio
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result = model.transcribe(file.name)
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transcriere_text = result["text"]
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# Use OpenAI to summarize the transcription
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openai.api_key = "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"
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response = openai.ChatCompletion.create(
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model="gpt-3.5-turbo",
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messages=[
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{"role": "system", "content": "You are a helpful assistant that summarizes text."},
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{"role": "user", "content": f"Please summarize the following text: {transcriere_text}"}
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]
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)
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rezumat_text = response.choices[0].message.content.strip()
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return transcriere_text, rezumat_text
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# Define the Gradio interface
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interface = gr.Interface(
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fn=procesare_audio,
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inputs=gr.Audio(type="file")
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outputs=[
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gr.Textbox(label="Transcrierea textului:"),
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gr.Textbox(label="Rezumatul textului:")
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],
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title="Transcriere și Rezumat AI",
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description="Această aplicație transcrie fișiere audio și creează un rezumat al conținutului folosind AI.",
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theme="compact"
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)
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# Launch the Gradio app
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interface.launch(share=False, debug=True)
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