215 lines
6.5 KiB
Python
Executable File
215 lines
6.5 KiB
Python
Executable File
#!/usr/bin/env -S uv run --script
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# /// script
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# requires-python = ">=3.11"
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# dependencies = [
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# "python-dotenv",
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# ]
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# ///
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import argparse
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import json
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import os
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import random
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import subprocess
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import sys
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from pathlib import Path
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try:
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from dotenv import load_dotenv
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load_dotenv()
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except ImportError:
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pass # dotenv is optional
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def get_completion_messages():
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"""Return list of friendly completion messages."""
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return [
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"Work complete!",
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"All done!",
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"Task finished!",
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"Job complete!",
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"Ready for next task!",
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]
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def get_tts_script_path():
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"""
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Determine which TTS script to use based on available API keys.
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Priority order: ElevenLabs > OpenAI > pyttsx3
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"""
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# Get current script directory and construct utils/tts path
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script_dir = Path(__file__).parent
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tts_dir = script_dir / "utils" / "tts"
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# Check for ElevenLabs API key (highest priority)
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if os.getenv("ELEVENLABS_API_KEY"):
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elevenlabs_script = tts_dir / "elevenlabs_tts.py"
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if elevenlabs_script.exists():
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return str(elevenlabs_script)
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# Check for OpenAI API key (second priority)
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if os.getenv("OPENAI_API_KEY"):
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openai_script = tts_dir / "openai_tts.py"
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if openai_script.exists():
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return str(openai_script)
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# Fall back to pyttsx3 (no API key required)
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pyttsx3_script = tts_dir / "pyttsx3_tts.py"
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if pyttsx3_script.exists():
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return str(pyttsx3_script)
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return None
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def get_llm_completion_message():
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"""
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Generate completion message using available LLM services.
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Priority order: OpenAI > Anthropic > fallback to random message
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Returns:
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str: Generated or fallback completion message
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"""
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# Get current script directory and construct utils/llm path
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script_dir = Path(__file__).parent
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llm_dir = script_dir / "utils" / "llm"
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# Try OpenAI first (highest priority)
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if os.getenv("OPENAI_API_KEY"):
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oai_script = llm_dir / "oai.py"
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if oai_script.exists():
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try:
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result = subprocess.run(
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["uv", "run", str(oai_script), "--completion"],
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capture_output=True,
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text=True,
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timeout=10,
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)
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if result.returncode == 0 and result.stdout.strip():
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return result.stdout.strip()
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except (subprocess.TimeoutExpired, subprocess.SubprocessError):
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pass
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# Try Anthropic second
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if os.getenv("ANTHROPIC_API_KEY"):
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anth_script = llm_dir / "anth.py"
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if anth_script.exists():
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try:
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result = subprocess.run(
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["uv", "run", str(anth_script), "--completion"],
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capture_output=True,
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text=True,
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timeout=10,
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)
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if result.returncode == 0 and result.stdout.strip():
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return result.stdout.strip()
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except (subprocess.TimeoutExpired, subprocess.SubprocessError):
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pass
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# Fallback to random predefined message
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messages = get_completion_messages()
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return random.choice(messages)
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def announce_completion():
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"""Announce completion using the best available TTS service."""
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try:
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tts_script = get_tts_script_path()
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if not tts_script:
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return # No TTS scripts available
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# Get completion message (LLM-generated or fallback)
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completion_message = get_llm_completion_message()
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# Call the TTS script with the completion message
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subprocess.run(
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["uv", "run", tts_script, completion_message],
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capture_output=True, # Suppress output
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timeout=10, # 10-second timeout
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)
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except (subprocess.TimeoutExpired, subprocess.SubprocessError, FileNotFoundError):
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# Fail silently if TTS encounters issues
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pass
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except Exception:
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# Fail silently for any other errors
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pass
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def main():
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try:
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# Parse command line arguments
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parser = argparse.ArgumentParser()
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parser.add_argument(
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"--chat", action="store_true", help="Copy transcript to chat.json"
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)
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args = parser.parse_args()
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# Read JSON input from stdin
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input_data = json.load(sys.stdin)
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# Extract required fields
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session_id = input_data.get("session_id", "")
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stop_hook_active = input_data.get("stop_hook_active", False)
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# Ensure log directory exists
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log_dir = os.path.join(os.getcwd(), "logs")
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os.makedirs(log_dir, exist_ok=True)
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log_path = os.path.join(log_dir, "stop.json")
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# Read existing log data or initialize empty list
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if os.path.exists(log_path):
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with open(log_path) as f:
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try:
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log_data = json.load(f)
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except (json.JSONDecodeError, ValueError):
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log_data = []
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else:
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log_data = []
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# Append new data
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log_data.append(input_data)
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# Write back to file with formatting
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with open(log_path, "w") as f:
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json.dump(log_data, f, indent=2)
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# Handle --chat switch
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if args.chat and "transcript_path" in input_data:
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transcript_path = input_data["transcript_path"]
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if os.path.exists(transcript_path):
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# Read .jsonl file and convert to JSON array
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chat_data = []
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try:
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with open(transcript_path) as f:
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for line in f:
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line = line.strip()
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if line:
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try:
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chat_data.append(json.loads(line))
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except json.JSONDecodeError:
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pass # Skip invalid lines
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# Write to logs/chat.json
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chat_file = os.path.join(log_dir, "chat.json")
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with open(chat_file, "w") as f:
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json.dump(chat_data, f, indent=2)
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except Exception:
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pass # Fail silently
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# Announce completion via TTS
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announce_completion()
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sys.exit(0)
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except json.JSONDecodeError:
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# Handle JSON decode errors gracefully
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sys.exit(0)
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except Exception:
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# Handle any other errors gracefully
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sys.exit(0)
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if __name__ == "__main__":
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main()
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