generated from nhcarrigan/template
naomi
3c8a46e5a6
- Add Python backend structure with FastAPI for transcription/summarization - Add React UI with audio recording, transcript, and summary views - Configure Tauri to manage Python backend lifecycle - Set up Windows cross-compilation with cargo-xwin - Add Gitea CI workflow for lint, test, and multi-platform builds - Configure ESLint, Prettier, and Vitest for code quality Note: App scaffolding only - Python env and models not yet set up
90 lines
2.8 KiB
Python
90 lines
2.8 KiB
Python
"""Download required models for Chronara."""
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import os
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import sys
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from pathlib import Path
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from urllib.request import urlretrieve
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# Model download URLs
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MODELS = {
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"llama-3.2-1B": {
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"url": "https://huggingface.co/bartowski/Llama-3.2-1B-Instruct-GGUF/resolve/main/Llama-3.2-1B-Instruct-Q4_K_M.gguf",
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"filename": "llama-3.2-1B-instruct-Q4_K_M.gguf",
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"size": "1.2GB",
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},
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"llama-3.2-3B": {
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"url": "https://huggingface.co/bartowski/Llama-3.2-3B-Instruct-GGUF/resolve/main/Llama-3.2-3B-Instruct-Q4_K_M.gguf",
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"filename": "llama-3.2-3B-instruct-Q4_K_M.gguf",
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"size": "2.5GB",
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},
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}
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def download_with_progress(url: str, filepath: Path):
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"""Download file with progress bar."""
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def _progress(block_num, block_size, total_size):
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downloaded = block_num * block_size
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percent = min(downloaded * 100 / total_size, 100)
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progress = int(50 * percent / 100)
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sys.stdout.write(
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f"\r[{'=' * progress}{' ' * (50 - progress)}] {percent:.1f}%"
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)
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sys.stdout.flush()
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print(f"Downloading {filepath.name}...")
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urlretrieve(url, filepath, reporthook=_progress)
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print() # New line after progress bar
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def main():
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"""Download all required models."""
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# Get project root
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project_root = Path(__file__).parent.parent
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models_dir = project_root / "models"
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models_dir.mkdir(exist_ok=True)
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print("🤖 Chronara Model Downloader")
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print("=" * 50)
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# Ask which model to download
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print("\nWhich Llama model would you like to use?")
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print("1. Llama 3.2 1B (1.2GB) - Faster, good for basic summaries")
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print("2. Llama 3.2 3B (2.5GB) - Better quality summaries")
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print("3. Both models")
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choice = input("\nEnter your choice (1/2/3): ").strip()
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models_to_download = []
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if choice == "1":
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models_to_download = ["llama-3.2-1B"]
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elif choice == "2":
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models_to_download = ["llama-3.2-3B"]
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elif choice == "3":
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models_to_download = ["llama-3.2-1B", "llama-3.2-3B"]
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else:
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print("Invalid choice!")
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return
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# Download selected models
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for model_name in models_to_download:
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model_info = MODELS[model_name]
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filepath = models_dir / model_info["filename"]
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if filepath.exists():
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print(f"\n✓ {model_name} already downloaded")
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continue
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print(f"\n📥 Downloading {model_name} ({model_info['size']})...")
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try:
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download_with_progress(model_info["url"], filepath)
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print(f"✓ Downloaded {model_name} successfully!")
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except Exception as e:
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print(f"✗ Failed to download {model_name}: {e}")
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print("\n✨ Model download complete!")
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print("\nNote: WhisperX models will be downloaded automatically on first run.")
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if __name__ == "__main__":
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main() |