tr_weekly.py

import os
import json
import whisper
import openai
import sys
from scribe import send_notes
from dotenv import load_dotenv

load_dotenv()

openai.api_key = os.getenv("OPENAI_API_KEY")

def main():
    if len(sys.argv) < 2:
        print("Usage: python tr_weekly.py <video_name.mp4>")
        return
    
    meeting = sys.argv[1]

    transcript = transcribe(meeting)

    res = summarize(transcript)
    with open('result.txt', 'w') as file:
        file.write(res)

    send_notes(res)

# Load medium english only model and transcribe
def transcribe(recording):
    model = whisper.load_model("medium.en")
    result = model.transcribe(recording)

    return result["text"]

def summarize(transcript):

    # Grab system prompt from system.txt
    with open('context/system.txt') as f:
        system_prompt = f.read()

    # Grab sample i/o; Disabled for now since response has mixed results
    f = open('context/sample.json')
    sample_data = json.load(f)

    response = openai.ChatCompletion.create(   
        model="gpt-3.5-turbo-16k",
        messages=[
                {"role": "system", "content": system_prompt},
                # {"role": "user", "content": sample_data['input']},
                # {"role": "assistant", "content": sample_data['output']},
                {"role": "user", "content": transcript}
            ]
        )
    return response['choices'][0]['message']['content']

if __name__ == "__main__":
    main()