Files
vibeline/summarize_transcripts.py

67 lines
2.0 KiB
Python
Executable File

#!/usr/bin/env python3
import os
import sys
from pathlib import Path
import ollama
def read_transcript(transcript_file: Path) -> str:
"""Read the content of a transcript file."""
with open(transcript_file, 'r', encoding='utf-8') as f:
return f.read()
def process_transcript(transcript_text: str) -> str:
"""Process a transcript using LLaMA to generate a summary."""
prompt = f"""Please provide a concise summary of the following transcript.
Focus on the main topics, key points, and any action items or decisions mentioned.
Keep the summary clear and well-structured.
Transcript:
{transcript_text}
Summary:"""
# Use Ollama to generate the summary
response = ollama.chat(model='llama2', messages=[
{
'role': 'user',
'content': prompt
}
])
return response['message']['content']
def save_summary(summary: str, output_file: Path) -> None:
"""Save the summary to a file."""
with open(output_file, 'w', encoding='utf-8') as f:
f.write(summary)
def main():
transcript_dir = Path("VoiceMemos/transcripts")
summary_dir = Path("VoiceMemos/summaries")
# Create summaries directory if it doesn't exist
summary_dir.mkdir(parents=True, exist_ok=True)
# Process all transcript files
for transcript_file in transcript_dir.glob("*.txt"):
print(f"Processing {transcript_file.name}...")
# Read transcript
transcript_text = read_transcript(transcript_file)
# Generate summary
try:
summary = process_transcript(transcript_text)
# Save summary
summary_file = summary_dir / f"{transcript_file.stem}_summary.txt"
save_summary(summary, summary_file)
print(f"Summary saved to {summary_file}")
except Exception as e:
print(f"Error processing {transcript_file.name}: {str(e)}")
continue
if __name__ == "__main__":
main()