feat: Add OpenAI TTS audio generation and playback for recordings

scripts/recording_audio.py

@@ -0,0 +1,135 @@
+#!/usr/bin/env python3
+"""
+Generate TTS audio files for recording commentary using OpenAI's API.
+Usage: python scripts/recording_audio.py path/to/recording.md
+"""
+
+import os
+import re
+import sys
+import argparse
+import requests
+from pathlib import Path
+from dotenv import load_dotenv
+
+# Load environment variables from .env file
+load_dotenv()
+
+# Configuration
+OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY")
+OUTPUT_DIR = "aider/website/assets/audio"
+VOICE = "onyx"  # Options: alloy, echo, fable, onyx, nova, shimmer
+
+def extract_recording_id(markdown_file):
+    """Extract recording ID from the markdown file path."""
+    return Path(markdown_file).stem
+
+def extract_commentary(markdown_file):
+    """Extract commentary markers from markdown file."""
+    with open(markdown_file, 'r') as f:
+        content = f.read()
+    
+    # Find Commentary section
+    commentary_match = re.search(r'## Commentary\s+(.*?)(?=##|\Z)', content, re.DOTALL)
+    if not commentary_match:
+        print(f"No Commentary section found in {markdown_file}")
+        return []
+    
+    commentary = commentary_match.group(1).strip()
+    
+    # Extract timestamp-message pairs
+    markers = []
+    for line in commentary.split('\n'):
+        line = line.strip()
+        if line.startswith('- '):
+            line = line[2:]  # Remove the list marker
+            match = re.match(r'(\d+):(\d+)\s+(.*)', line)
+            if match:
+                minutes, seconds, message = match.groups()
+                time_in_seconds = int(minutes) * 60 + int(seconds)
+                markers.append((time_in_seconds, message))
+    
+    return markers
+
+def generate_audio_openai(text, output_file):
+    """Generate audio using OpenAI TTS API."""
+    if not OPENAI_API_KEY:
+        print("Error: OPENAI_API_KEY environment variable not set")
+        return False
+        
+    url = "https://api.openai.com/v1/audio/speech"
+    headers = {
+        "Authorization": f"Bearer {OPENAI_API_KEY}",
+        "Content-Type": "application/json"
+    }
+    data = {
+        "model": "tts-1",
+        "input": text,
+        "voice": VOICE
+    }
+    
+    try:
+        response = requests.post(url, headers=headers, json=data)
+        
+        if response.status_code == 200:
+            with open(output_file, 'wb') as f:
+                f.write(response.content)
+            return True
+        else:
+            print(f"Error: {response.status_code}, {response.text}")
+            return False
+    except Exception as e:
+        print(f"Exception during API call: {e}")
+        return False
+
+def main():
+    parser = argparse.ArgumentParser(description='Generate TTS audio for recording commentary.')
+    parser.add_argument('markdown_file', help='Path to the recording markdown file')
+    parser.add_argument('--voice', default=VOICE, help=f'OpenAI voice to use (default: {VOICE})')
+    parser.add_argument('--output-dir', default=OUTPUT_DIR, help=f'Output directory (default: {OUTPUT_DIR})')
+    parser.add_argument('--dry-run', action='store_true', help='Print what would be done without generating audio')
+    
+    args = parser.parse_args()
+    
+    # Update globals with any command line overrides
+    global VOICE
+    VOICE = args.voice
+    
+    recording_id = extract_recording_id(args.markdown_file)
+    print(f"Processing recording: {recording_id}")
+    
+    # Create output directory
+    output_dir = os.path.join(args.output_dir, recording_id)
+    if not args.dry_run:
+        os.makedirs(output_dir, exist_ok=True)
+    
+    # Extract commentary markers
+    markers = extract_commentary(args.markdown_file)
+    
+    if not markers:
+        print("No commentary markers found!")
+        return
+    
+    print(f"Found {len(markers)} commentary markers")
+    
+    # Generate audio for each marker
+    for time_sec, message in markers:
+        minutes = time_sec // 60
+        seconds = time_sec % 60
+        timestamp = f"{minutes:02d}-{seconds:02d}"
+        filename = f"{timestamp}.mp3"
+        output_file = os.path.join(output_dir, filename)
+        
+        print(f"Marker at {minutes}:{seconds:02d} - {message}")
+        if args.dry_run:
+            print(f"  Would generate: {output_file}")
+        else:
+            print(f"  Generating: {output_file}")
+            success = generate_audio_openai(message, output_file)
+            if success:
+                print(f"  ✓ Generated audio file")
+            else:
+                print(f"  ✗ Failed to generate audio")
+
+if __name__ == "__main__":
+    main()