src/cli/main.py

"""
Main CLI entry point for Voice Tools.

Provides command-line interface for voice extraction and profiling tasks.
"""

import logging

import click
from dotenv import load_dotenv

# Load environment variables from .env file
load_dotenv()

# Configure SSL context BEFORE any model-related imports
from src.config.ssl_config import configure_ssl_context

configure_ssl_context()

from .progress import (
    display_error,
    display_header,
    display_info,
    display_success,
    display_warning,
)

# Configure logging
logging.basicConfig(
    level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s"
)
logger = logging.getLogger(__name__)


@click.group()
@click.version_option(version="0.1.0", prog_name="voice-tools")
def cli():
    """
    Voice Tools - Extract and profile voices from audio files.

    This tool helps you extract specific voices from audio files using
    speaker diarization and voice matching. It can separate speech from
    nonverbal sounds and apply quality filtering.
    """
    pass


# Import and register commands
from .denoise import denoise
from .extract_speaker import extract_speaker
from .separate import separate

cli.add_command(separate)
cli.add_command(extract_speaker)
cli.add_command(denoise)


@cli.command()
@click.option("--host", default="0.0.0.0", help="Server hostname (default: 0.0.0.0)")
@click.option("--port", default=7860, type=int, help="Server port (default: 7860)")
@click.option("--share", is_flag=True, help="Create public share link")
def web(host: str, port: int, share: bool):
    """
    Launch the web interface.

    Opens a browser-based UI for voice extraction with file upload,
    configuration, and result download.

    Example:

    \b
    voice-tools web
    voice-tools web --port 8080 --share
    """
    from ..web.app import launch

    display_header("Voice Tools - Web Interface")
    display_info(f"Starting web server on http://{host}:{port}")

    if share:
        display_info("Creating public share link...")

    display_success("Server starting... Open the URL in your browser")

    try:
        launch(server_name=host, server_port=port, share=share, debug=False)
    except KeyboardInterrupt:
        display_info("Server stopped")
    except Exception as e:
        display_error(f"Failed to start server: {e}")
        raise click.Abort()


@cli.command()
def info():
    """
    Display information about Voice Tools.

    Shows configuration, model information, and system details.
    """
    import torch
    from rich.table import Table

    from ..services.model_manager import ModelManager
    from .progress import console

    display_header("Voice Tools - System Information")

    # Version info
    info_table = Table(title="Version", show_header=False)
    info_table.add_column("Key", style="cyan")
    info_table.add_column("Value", style="white")
    info_table.add_row("Version", "0.1.0")
    console.print(info_table)
    console.print()

    # Models info
    models_table = Table(title="Models", show_header=False)
    models_table.add_column("Component", style="cyan")
    models_table.add_column("Model", style="white")
    models_table.add_row("Speaker Diarization", "pyannote/speaker-diarization-3.1")
    models_table.add_row("Voice Embedding", "pyannote/embedding")
    models_table.add_row("Speech Classifier", "MIT/ast-finetuned-audioset-10-10-0.4593")
    models_table.add_row("VAD", "Silero VAD v4.0")
    console.print(models_table)
    console.print()

    # Environment info
    env_table = Table(title="Environment", show_header=False)
    env_table.add_column("Key", style="cyan")
    env_table.add_column("Value", style="white")
    env_table.add_row("PyTorch version", torch.__version__)
    env_table.add_row("CUDA available", "Yes" if torch.cuda.is_available() else "No")
    if torch.cuda.is_available():
        env_table.add_row("CUDA device", torch.cuda.get_device_name(0))
    console.print(env_table)
    console.print()

    # Check for HuggingFace token
    model_manager = ModelManager()
    token = model_manager.get_hf_token()
    if token:
        display_success("HuggingFace token: Configured")
    else:
        display_warning("HuggingFace token: Not configured")
        display_info("Some models require authentication. Set HF_TOKEN environment variable.")


def main():
    """Entry point for the CLI."""
    cli()


if __name__ == "__main__":
    main()