Spaces:
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"""Script to download and prepare models for HuggingFace Spaces."""
import os
import asyncio
import logging
from pathlib import Path
from huggingface_hub import HfApi, upload_file
from reasoning.model_manager import ModelManager
# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
async def download_and_prepare_models():
"""Download all models and prepare for Spaces."""
try:
# Initialize model manager
model_dir = os.path.join(os.getcwd(), "models")
manager = ModelManager(model_dir)
# Create models directory
os.makedirs(model_dir, exist_ok=True)
# Download all models
logger.info("Starting model downloads...")
await manager.initialize_all_models()
logger.info("All models downloaded successfully!")
return True
except Exception as e:
logger.error(f"Error downloading models: {e}")
return False
def upload_to_spaces(space_name: str = "agentic-system-models"):
"""Upload models to HuggingFace Spaces."""
try:
api = HfApi()
model_dir = os.path.join(os.getcwd(), "models")
# Create .gitattributes for LFS
gitattributes_path = os.path.join(model_dir, ".gitattributes")
with open(gitattributes_path, "w") as f:
f.write("*.gguf filter=lfs diff=lfs merge=lfs -text")
# Upload .gitattributes first
api.upload_file(
path_or_fileobj=gitattributes_path,
path_in_repo=".gitattributes",
repo_id=f"spaces/{space_name}",
repo_type="space"
)
# Upload each model file
for model_file in Path(model_dir).glob("*.gguf"):
logger.info(f"Uploading {model_file.name}...")
api.upload_file(
path_or_fileobj=str(model_file),
path_in_repo=f"models/{model_file.name}",
repo_id=f"spaces/{space_name}",
repo_type="space"
)
logger.info("All models uploaded to Spaces successfully!")
return True
except Exception as e:
logger.error(f"Error uploading to Spaces: {e}")
return False
if __name__ == "__main__":
# Download models
asyncio.run(download_and_prepare_models())
# Upload to Spaces
upload_to_spaces()
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