Remove unused summarize_transcripts.py script

src/summarize_transcripts.py

@@ -1,135 +0,0 @@
-#!/usr/bin/env python3
-
-import os
-import sys
-from pathlib import Path
-import ollama
-import time
-import re
-from datetime import datetime
-
-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 load_prompt_template(template_name: str) -> str:
-    """Load a prompt template by name."""
-    prompt_dir = Path("prompts")
-    prompt_file = prompt_dir / f"{template_name}.md"
-    with open(prompt_file, 'r', encoding='utf-8') as f:
-        return f.read()
-
-def process_with_llama(prompt: str) -> str:
-    """Process text using LLaMA to generate content."""
-    response = ollama.chat(model='llama2', messages=[
-        {
-            'role': 'user',
-            'content': prompt
-        }
-    ])
-    return response['message']['content'].strip()
-
-def save_content(content: str, output_file: Path) -> None:
-    """Save content to a file."""
-    with open(output_file, 'w', encoding='utf-8') as f:
-        f.write(content)
-
-def count_words(text: str) -> int:
-    """Count the number of words in a text string."""
-    return len(text.split())
-
-def determine_content_type(transcript_text: str) -> str:
-    """Determine the type of content in the transcript."""
-    text = transcript_text.lower()
-    
-    if re.search(r'\bblog post\b', text) or re.search(r'\bdraft\b', text):
-        return "blog_post"
-    elif re.search(r'\bidea\b', text) and re.search(r'\bapp\b', text):
-        return "idea_app"
-    return "default"
-
-def generate_summary(transcript_text: str) -> str:
-    """Generate a summary of the transcript."""
-    prompt_template = load_prompt_template("summary")
-    prompt = prompt_template.format(transcript=transcript_text)
-    return process_with_llama(prompt)
-
-def generate_additional_content(content_type: str, transcript_text: str, summary: str) -> str:
-    """Generate additional content based on the content type."""
-    prompt_template = load_prompt_template(content_type)
-    prompt = prompt_template.format(transcript=transcript_text, summary=summary)
-    return process_with_llama(prompt)
-
-def main():
-    transcript_dir = Path("VoiceMemos/transcripts")
-    summary_dir = Path("VoiceMemos/summaries")
-    draft_dir = Path("VoiceMemos/drafts")
-    prompt_dir = Path("VoiceMemos/prompts")
-    
-    # Create necessary directories
-    for directory in [summary_dir, draft_dir, prompt_dir]:
-        directory.mkdir(parents=True, exist_ok=True)
-    
-    # Get list of all transcript files
-    transcript_files = list(transcript_dir.glob("*.txt"))
-    total_files = len(transcript_files)
-    
-    print(f"Found {total_files} transcript(s) to process")
-    
-    # Process all transcript files
-    for idx, transcript_file in enumerate(transcript_files, 1):
-        print(f"\nProcessing {transcript_file.name} ({idx}/{total_files})...")
-        
-        # Skip if summary already exists
-        summary_file = summary_dir / f"{transcript_file.stem}_summary.txt"
-        if summary_file.exists():
-            print("  Summary already exists, skipping...")
-            continue
-        
-        try:
-            # Read transcript
-            transcript_text = read_transcript(transcript_file)
-            word_count = count_words(transcript_text)
-            print(f"  Read transcript ({len(transcript_text)} characters, {word_count} words)")
-            
-            # Skip if transcript is too short
-            if word_count <= 210:
-                print("  Transcript is too short (≤210 words), skipping processing")
-                continue
-            
-            # Generate summary
-            print("  Generating summary...")
-            summary = generate_summary(transcript_text)
-            save_content(summary, summary_file)
-            print(f"  Summary saved to {summary_file}")
-            
-            # Determine content type and generate additional content if needed
-            content_type = determine_content_type(transcript_text)
-            if content_type != "default":
-                print(f"  Generating additional content for type: {content_type}")
-                additional_content = generate_additional_content(content_type, transcript_text, summary)
-                
-                # Save to appropriate directory with timestamp
-                timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
-                if content_type == "blog_post":
-                    output_file = draft_dir / f"{transcript_file.stem}_{timestamp}.md"
-                else:  # idea_app
-                    output_file = prompt_dir / f"{transcript_file.stem}_{timestamp}.md"
-                
-                save_content(additional_content, output_file)
-                print(f"  Additional content saved to {output_file}")
-            
-            # Add a small delay between files to avoid overloading
-            if idx < total_files:
-                time.sleep(1)
-                
-        except Exception as e:
-            print(f"  Failed to process {transcript_file.name}")
-            print(f"  Error: {str(e)}")
-            continue
-    
-    print("\nDone! All transcripts processed.")
-
-if __name__ == "__main__":
-    main()