| """ |
| Upload model and data artifacts to a HuggingFace Hub model repository. |
| |
| Run this ONCE from your local machine before deploying the Space. |
| |
| Usage: |
| HF_REPO_ID=yourname/deepreads-artifacts python scripts/upload_artifacts.py |
| |
| Environment variables: |
| HF_REPO_ID — target HF model repo (will be created if it doesn't exist) |
| HF_TOKEN — your HF write token (from https://huggingface.co/settings/tokens) |
| """ |
|
|
| from __future__ import annotations |
|
|
| import os |
| import sys |
| from pathlib import Path |
|
|
| ROOT = Path(__file__).resolve().parent.parent |
|
|
| ARTIFACT_MAP: list[tuple[Path, str]] = [ |
| |
| |
| (ROOT / "models" / "two_tower.pt", "models/two_tower.pt"), |
| (ROOT / "models" / "item_embeddings.npy", "models/item_embeddings.npy"), |
| (ROOT / "models" / "item_index.pkl", "models/item_index.pkl"), |
| (ROOT / "models" / "naive_baseline.pkl", "models/naive_baseline.pkl"), |
| (ROOT / "models" / "naive_category.pkl", "models/naive_category.pkl"), |
| (ROOT / "models" / "lgbm_model.pkl", "models/lgbm_model.pkl"), |
| |
| (ROOT / "data" / "processed" / "item_features.parquet", "data/processed/item_features.parquet"), |
| (ROOT / "data" / "processed" / "user_features.parquet", "data/processed/user_features.parquet"), |
| (ROOT / "data" / "processed" / "train.parquet", "data/processed/train.parquet"), |
| (ROOT / "data" / "processed" / "feature_artifacts.pkl", "data/processed/feature_artifacts.pkl"), |
| (ROOT / "data" / "processed" / "item_encoder.pkl", "data/processed/item_encoder.pkl"), |
| (ROOT / "data" / "processed" / "user_encoder.pkl", "data/processed/user_encoder.pkl"), |
| ] |
|
|
|
|
| def main() -> None: |
| repo_id = os.environ.get("HF_REPO_ID", "") |
| if not repo_id: |
| print("ERROR: Set HF_REPO_ID, e.g.:") |
| print(" export HF_REPO_ID=yourname/deepreads-artifacts") |
| sys.exit(1) |
|
|
| token = os.environ.get("HF_TOKEN") or None |
| if not token: |
| print("WARNING: HF_TOKEN not set. Will try using cached credentials.") |
| print(" Get a write token at https://huggingface.co/settings/tokens") |
|
|
| try: |
| from huggingface_hub import HfApi |
| except ImportError: |
| print("ERROR: pip install huggingface-hub") |
| sys.exit(1) |
|
|
| api = HfApi(token=token) |
|
|
| |
| try: |
| api.create_repo(repo_id=repo_id, repo_type="model", exist_ok=True, private=False) |
| print(f"Repository ready: https://huggingface.co/{repo_id}") |
| except Exception as e: |
| print(f"ERROR creating repo: {e}") |
| sys.exit(1) |
|
|
| missing = [(local, repo_fn) for local, repo_fn in ARTIFACT_MAP if not local.exists()] |
| if missing: |
| print(f"WARNING: {len(missing)} local file(s) not found and will be skipped:") |
| for local, _ in missing: |
| print(f" {local}") |
|
|
| to_upload = [(local, repo_fn) for local, repo_fn in ARTIFACT_MAP if local.exists()] |
| total = len(to_upload) |
| print(f"\nUploading {total} file(s) to {repo_id} …\n") |
|
|
| for i, (local_path, repo_filename) in enumerate(to_upload, 1): |
| size_mb = local_path.stat().st_size / 1_048_576 |
| print(f" [{i}/{total}] {repo_filename} ({size_mb:.1f} MB)") |
| try: |
| api.upload_file( |
| path_or_fileobj=str(local_path), |
| path_in_repo=repo_filename, |
| repo_id=repo_id, |
| repo_type="model", |
| ) |
| except Exception as e: |
| print(f" ERROR: {e}") |
| sys.exit(1) |
|
|
| print(f"\nDone! All artifacts uploaded to:") |
| print(f" https://huggingface.co/{repo_id}") |
| print(f"\nNext: set HF_REPO_ID={repo_id} as a Space secret.") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
