Update 38 prevent runtime self-rebuild commits

CHANGELOG.md

@@ -1,5 +1,10 @@
 # Changelog
 
+## Update ke-38 - 2026-05-02
+- Cegah Space melakukan commit runtime ke repo Space yang sama secara default.
+- Tambah guard `HF_ALLOW_SPACE_RUNTIME_COMMITS` untuk menghindari rebuild otomatis yang menyebabkan HTTP 503 setelah training.
+- Minor update dinaikkan ke-38.
+
 ## Update ke-37 - 2026-05-01
 - Perbaiki training yang berhenti pada tahap `preparing_dataset`.
 - Persiapan dataset, pseudo-label, training YOLO, penyimpanan `best.pt`, grafik PNG, confusion matrix, log, dan sync artefak kini berjalan dalam background worker sejak awal.

README.md

@@ -115,10 +115,12 @@ Opsional environment variable:
 - `HF_AUTOSYNC_INCLUDE_GLOBS` - pola file yang ingin disync (default `*.py,*.md,requirements.txt,.gitignore`)
 - `HF_AUTOSYNC_MAX_FILE_MB` - batas ukuran file yang di-sync (default `200` MB)
 - `HF_AUTOSYNC_IGNORE_GLOBS` - daftar pola file/folder yang diabaikan (dipisah koma)
+- `HF_ALLOW_SPACE_RUNTIME_COMMITS` - default `false`; aktifkan hanya jika benar-benar ingin app melakukan commit ke repo Space yang sedang berjalan
 
 Catatan sync otomatis setelah training:
 - Jika `HF_MODEL_REPO` terisi, aplikasi akan upload `best.pt` ke `HF_MODEL_FILE`.
 - Jika tidak terisi, training tetap jalan normal dan hanya menyimpan `best.pt` lokal.
+- Jika `HF_MODEL_REPO` menunjuk ke Space yang sama, upload runtime dinonaktifkan secara default agar Space tidak rebuild sendiri dan memunculkan 503.
 
 Catatan auto-save hasil deteksi:
 - Setelah inferensi sukses, aplikasi menyimpan gambar anotasi ke `evaluation_outputs/` lokal.

app.py

@@ -24,7 +24,7 @@ from ultralytics import YOLO
 CM_INIT = {"tp": 0, "fp": 0, "fn": 0, "tn": 0, "person": 0, "not_person": 0}
 EVAL_CLASSES = ["Person", "Not Person/Background"]
 APP_VERSION = os.getenv("APP_VERSION", "v0.9.0")
-APP_MINOR_UPDATE = os.getenv("APP_MINOR_UPDATE", "37")
+APP_MINOR_UPDATE = os.getenv("APP_MINOR_UPDATE", "38")
 
 
 # Gradio/Spaces can trigger noisy asyncio cleanup traces ("Invalid file descriptor: -1")
@@ -995,14 +995,16 @@ def _prepare_training_dataset(
 def sync_best_to_hf(best_model_path: Path) -> str:
     hf_repo = os.getenv("HF_MODEL_REPO", "").strip()
     hf_file = os.getenv("HF_MODEL_FILE", "best.pt").strip() or "best.pt"
-    hf_repo_type = os.getenv("HF_MODEL_REPO_TYPE", "space").strip() or "space"
-    hf_token = os.getenv("HF_TOKEN", "").strip() or None
-
-    if not hf_repo:
-        return "HF sync dilewati: set HF_MODEL_REPO untuk upload otomatis."
-
-    try:
-        api = HfApi(token=hf_token)
+    hf_repo_type = os.getenv("HF_MODEL_REPO_TYPE", "space").strip() or "space"
+    hf_token = os.getenv("HF_TOKEN", "").strip() or None
+
+    if not hf_repo:
+        return "HF sync dilewati: set HF_MODEL_REPO untuk upload otomatis."
+    if _skip_runtime_commit_to_current_space(hf_repo, hf_repo_type):
+        return "HF sync dilewati: commit runtime ke Space yang sama dinonaktifkan agar Space tidak rebuild sendiri."
+
+    try:
+        api = HfApi(token=hf_token)
         api.upload_file(
             path_or_fileobj=str(best_model_path),
             path_in_repo=hf_file,
@@ -1232,10 +1234,12 @@ def sync_training_artifacts_to_hf(
     repo_dir = os.getenv("HF_TRAINING_DIR", "space_training_archive").strip().strip("/")
     run_name = run_name or datetime.now().strftime("training_%Y%m%d_%H%M%S")
 
-    if not hf_repo:
-        return "HF training artifact sync dilewati: set HF_MODEL_REPO."
-
-    upload_items: list[tuple[Path | None, str]] = [
+    if not hf_repo:
+        return "HF training artifact sync dilewati: set HF_MODEL_REPO."
+    if _skip_runtime_commit_to_current_space(hf_repo, hf_repo_type):
+        return "HF training artifact sync dilewati: commit runtime ke Space yang sama dinonaktifkan agar Space tidak rebuild sendiri."
+
+    upload_items: list[tuple[Path | None, str]] = [
         (results_csv, f"{repo_dir}/{run_name}/results.csv"),
         (log_file, f"{repo_dir}/{run_name}/training.log"),
         (chart_file, f"{repo_dir}/{run_name}/training_curve.png"),
@@ -1264,11 +1268,20 @@ def sync_training_artifacts_to_hf(
         return f"HF training artifact sync gagal: {err}"
 
 
-def _env_true(var_name: str, default: bool = False) -> bool:
+def _env_true(var_name: str, default: bool = False) -> bool:
     val = os.getenv(var_name)
     if val is None:
         return default
-    return val.strip().lower() in {"1", "true", "yes", "on"}
+    return val.strip().lower() in {"1", "true", "yes", "on"}
+
+
+def _skip_runtime_commit_to_current_space(repo_id: str, repo_type: str) -> bool:
+    if repo_type != "space":
+        return False
+    if _env_true("HF_ALLOW_SPACE_RUNTIME_COMMITS", default=False):
+        return False
+    current_space = os.getenv("SPACE_ID", "").strip() or os.getenv("HF_SPACE_ID", "").strip()
+    return bool(current_space and repo_id.strip() == current_space)
 
 
 def _parse_globs(raw_value: str) -> list[str]: