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main.py
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import streamlit as st
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import openai
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import tempfile
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import os
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# Set up the Streamlit app
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st.title("Triplet Audio Transcription and Journal Structuring App")
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# Make an image for the app with the triplet.png image
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st.image("triplet3.png", width=600)
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st.write("Upload an audio file, and we'll transcribe it and structure the output as a journal entry.")
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# Supported audio file formats
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SUPPORTED_FORMATS = ['flac', 'm4a', 'mp3', 'mp4', 'mpeg', 'mpga', 'oga', 'ogg', 'wav', 'webm']
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# Input field for OpenAI API key
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api_key = st.text_input("Enter your OpenAI API key:", type="password")
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st.write("Everything is open source, please clone and run locally. Bring your own API key. We are using base whisper and chat-gpt models from OpenAI. The app is built using Streamlit and Python. (Note: This app is for demonstration purposes only. Do not upload sensitive information.")
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if api_key:
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# Initialize OpenAI client with the API key
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client = openai.OpenAI(api_key=api_key)
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# Function to transcribe audio using OpenAI Whisper
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def transcribe_audio(file_path):
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try:
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with open(file_path, "rb") as audio_file:
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transcript = client.audio.transcriptions.create(
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file=audio_file,
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model="whisper-1",
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response_format="verbose_json"
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)
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transcription = transcript.text
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return transcription
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except Exception as e:
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st.error(f"Error in transcription: {e}")
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return None
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# Function to structure transcription as a journal entry using Chat-GPT
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def structure_as_journal(transcription):
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try:
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prompt = f"Structure the following transcription as a detailed journal entry:\n\n{transcription}"
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response = client.chat.completions.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."},
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{"role": "user", "content": prompt}
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],
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max_tokens=1024
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)
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journal_entry = response.choices[0].message.content
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return journal_entry
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except Exception as e:
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st.error(f"Error in structuring journal entry: {e}")
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return None
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# File uploader for audio files
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uploaded_file = st.file_uploader("Upload an audio file", type=SUPPORTED_FORMATS)
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if uploaded_file:
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# Save uploaded file temporarily
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with tempfile.NamedTemporaryFile(delete=False, suffix=os.path.splitext(uploaded_file.name)[1]) as temp_file:
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temp_file.write(uploaded_file.read())
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temp_file_path = temp_file.name
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# Transcribe audio
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st.write("Transcribing audio...")
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transcription = transcribe_audio(temp_file_path)
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if transcription:
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st.write("Transcription:")
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st.write(transcription)
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# Structure transcription as a journal entry
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st.write("Structuring as a journal entry...")
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journal_entry = structure_as_journal(transcription)
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if journal_entry:
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st.write("Journal Entry:")
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st.write(journal_entry)
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# Clean up temporary file
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os.remove(temp_file_path)
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else:
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st.warning("Please enter your OpenAI API key to proceed.")
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