aider/scripts/recording_audio.py
2025-03-14 18:49:10 -07:00

138 lines
4.3 KiB
Python
Executable file

#!/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 argparse
import os
import re
import sys
from pathlib import Path
import requests
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()