Configure HF Spaces deployment

upload_models.py

@@ -0,0 +1,75 @@
+"""
+One-time uploader: push all trained model artifacts to a Hugging Face Hub
+model repo so the deployed Streamlit Space can download them at runtime.
+
+The Space git repo stays tiny (code + small CSVs only); the ~436 MB of models
+live here instead. The app pulls them via snapshot_download when MODEL_REPO_ID
+is set (see app/predictor.py).
+
+Prerequisites:
+    pip install -U huggingface_hub
+    huggingface-cli login            # or: export HF_TOKEN=hf_xxx
+
+Usage:
+    python deploy/upload_models.py --repo-id <your-username>/indo-abusive-detector
+
+Uploads (from saved_models/):
+    indobert_finetuned/   -> indobert_finetuned/   (config + safetensors + tokenizer)
+    lr_model.pkl, lr_tfidf.pkl, nb_model.pkl, nb_tfidf.pkl, svm_model.pkl
+"""
+
+import argparse
+import os
+import sys
+
+from huggingface_hub import HfApi, create_repo
+
+ROOT  = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+SAVED = os.path.join(ROOT, "saved_models")
+CLASSICAL = [
+    "lr_model.pkl", "lr_tfidf.pkl",
+    "nb_model.pkl", "nb_tfidf.pkl",
+    "svm_model.pkl",
+]
+
+
+def main():
+    ap = argparse.ArgumentParser(description=__doc__)
+    ap.add_argument("--repo-id", required=True,
+                    help="Target Hub model repo, e.g. user/indo-abusive-detector")
+    ap.add_argument("--private", action="store_true",
+                    help="Create the repo as private (the Space then needs an HF token).")
+    args = ap.parse_args()
+
+    bert_dir = os.path.join(SAVED, "indobert_finetuned")
+    missing = [p for p in [bert_dir, *[os.path.join(SAVED, f) for f in CLASSICAL]]
+               if not os.path.exists(p)]
+    if missing:
+        sys.exit("Missing artifacts — train first:\n  " + "\n  ".join(missing))
+
+    api = HfApi()
+    create_repo(args.repo_id, repo_type="model", private=args.private, exist_ok=True)
+    print(f"Repo ready: {args.repo_id}  (private={args.private})")
+
+    print("Uploading indobert_finetuned/ ...")
+    api.upload_folder(
+        repo_id=args.repo_id,
+        folder_path=bert_dir,
+        path_in_repo="indobert_finetuned",
+        commit_message="Add fine-tuned IndoBERTweet",
+    )
+
+    for fname in CLASSICAL:
+        print(f"Uploading {fname} ...")
+        api.upload_file(
+            repo_id=args.repo_id,
+            path_or_fileobj=os.path.join(SAVED, fname),
+            path_in_repo=fname,
+            commit_message=f"Add {fname}",
+        )
+
+    print(f"\nDone. Set MODEL_REPO_ID={args.repo_id} on the Space.")
+
+
+if __name__ == "__main__":
+    main()