Update src/main.py

src/main.py

@@ -1,3 +1,7 @@
+# import streamlit as st
+# st.write("hello")
+
+
 import os
 import json
 import uuid
@@ -8,10 +12,8 @@ from typing import Any, Dict, List, Tuple
 import streamlit as st
 import pandas as pd
 from PIL import Image
-from huggingface_hub import HfApi, hf_hub_download, CommitScheduler
+from huggingface_hub import HfApi, hf_hub_download
 from huggingface_hub.utils import HfHubHTTPError
-from pathlib import Path
-
 
 # =========================
 # CONFIG
@@ -27,6 +29,8 @@ st.set_page_config(
 #Set this to the private dataset repo that acts as the "database"
 DB_REPO_ID = os.getenv("DB_REPO_ID", "NidhiS09/VizWiz-submissions-db")
 DB_REPO_TYPE = "dataset"
+# print(DB_REPO_ID)
+
 
 # This must exist as a Space Secret in the PUBLIC UI Space
 SUBMISSIONS_TOKEN = os.getenv("SUBMISSIONS_TOKEN", "")
@@ -44,25 +48,6 @@ CHALLENGE_TYPES = ["Object Detection", "Instance Segmentation"]
 LEADERBOARD_METRICS = ["bbox_mAP", "bbox_AP50", "segm_mAP", "segm_AP50"]
 DEFAULT_SORT_METRIC = "segm_AP50"
 
-# =========================
-# COMMIT SCHEDULER SETUP
-# =========================
-
-# Local folder for scheduler to watch
-SCHEDULER_FOLDER = Path("submissions_queue")
-SCHEDULER_FOLDER.mkdir(exist_ok=True)
-
-# Initialize CommitScheduler
-scheduler = CommitScheduler(
-    repo_id=DB_REPO_ID,
-    repo_type=DB_REPO_TYPE,
-    folder_path=SCHEDULER_FOLDER,
-    token=SUBMISSIONS_TOKEN,
-    path_in_repo="submissions",  # Where files go in the repo
-    every=5,  # Commit every 5 minutes
-)
-
-
 # =========================
 # HELPERS
 # =========================
@@ -120,14 +105,25 @@ def _validate_submission_json(obj: Any) -> Tuple[bool, str]:
     return True, "OK"
 
 
-def _save_json_to_scheduler(data: Dict[str, Any] | List[Any], filename: str) -> None:
-    """
-    Save JSON to the scheduler folder.
-    The scheduler will automatically commit it to the repo.
-    """
-    file_path = SCHEDULER_FOLDER / filename
-    with open(file_path, "w") as f:
-        json.dump(data, f, ensure_ascii=False, indent=2)
+def _upload_json(api: HfApi, data: Dict[str, Any] | List[Any], path_in_repo: str) -> None:
+    with tempfile.NamedTemporaryFile(mode="w", suffix=".json", delete=False) as tmp:
+        json.dump(data, tmp, ensure_ascii=False)
+        tmp_path = tmp.name
+
+    try:
+        api.upload_file(
+            path_or_fileobj=tmp_path,
+            path_in_repo=path_in_repo,
+            repo_id=DB_REPO_ID,
+            repo_type=DB_REPO_TYPE,
+            token=SUBMISSIONS_TOKEN,
+            commit_message=f"Add {path_in_repo}",
+        )
+    finally:
+        try:
+            os.remove(tmp_path)
+        except OSError:
+            pass
 
 
 def _create_submission_record(
@@ -140,10 +136,11 @@ def _create_submission_record(
     original_filename: str,
 ) -> str:
     """
-    Writes pred/meta/status to the scheduler folder.
+    Writes pred/meta/status to the private DB dataset repo.
     Returns submission_id.
     """
     _require_token()
+    api = HfApi()
 
     submission_id = str(uuid.uuid4())
     ts = int(time.time())
@@ -160,10 +157,10 @@ def _create_submission_record(
 
     status = {"state": "queued", "timestamp": ts}
 
-    # Save to scheduler folder (will be auto-committed)
-    _save_json_to_scheduler(pred, f"{submission_id}_pred.json")
-    _save_json_to_scheduler(meta, f"{submission_id}_meta.json")
-    _save_json_to_scheduler(status, f"{submission_id}_status.json")
+    base = f"submissions/{submission_id}"
+    _upload_json(api, pred, f"{base}/pred.json")
+    _upload_json(api, meta, f"{base}/meta.json")
+    _upload_json(api, status, f"{base}/status.json")
 
     return submission_id
 
@@ -225,39 +222,7 @@ def _load_leaderboard_df() -> pd.DataFrame:
 # =========================
 # UI
 # =========================
-
-def render_overview():
-    with st.expander("ℹ️ Overview of the AI Benchmark Arena"):
-        st.markdown(
-            """
-
-**Note:** This Hugging Face Space queues submissions for evaluation and persists results in a private database repo.
-            """
-        )
-        # Keep this optional so missing image doesn't crash the Space
-        try:
-            overview_image = Image.open("src/overview_image.png").resize((600, 600))
-            st.image(overview_image, caption="Example of an object localization task")
-        except Exception:
-            st.info("Overview image not found at src/overview_image.png (optional).")
-
-
-def render_eval_details():
-    with st.expander("📐 How is the Score Calculated?"):
-        st.markdown(
-            """
-Your submission is evaluated offline by a private evaluator against hidden ground-truth annotations.
-The leaderboard reports:
-
-- bbox_mAP
-- bbox_AP50
-- segm_mAP
-- segm_AP50 (default ranking)
-
-Raw submissions are kept private; only scores and metadata are shown.
-            """
-        )
-
+#2 FUNCTIONS WERE HERE, RENDER_OVERVIEW AND RENDER EVAL
 
 def page_submit():
     st.header("🚀 Submit your Predictions")
@@ -375,6 +340,9 @@ def page_leaderboard():
 
 
 def main():
+
+    # st.write("✅ App booted and rendering UI")
+    
     st.sidebar.title("AI Benchmark Arena 🏆")
 
     # Warn early if DB repo isn't configured
@@ -396,6 +364,37 @@ def main():
     else:
         page_leaderboard()
 
+def render_overview():
+    with st.expander("ℹ️ Overview of the AI Benchmark Arena"):
+        st.markdown(
+            """
+        **Note:** This Hugging Face Space queues submissions for evaluation and persists results in a private database repo.
+            """
+        )
+        # Keep this optional so missing image doesn't crash the Space
+        try:
+            overview_image = Image.open("src/overview_image.png").resize((600, 600))
+            st.image(overview_image, caption="Example of an object localization task")
+        except Exception:
+            st.info("Overview image not found at src/overview_image.png (optional).")
+
+
+def render_eval_details():
+    with st.expander("📐 How is the Score Calculated?"):
+        st.markdown(
+            """
+        Your submission is evaluated offline by a private evaluator against hidden ground-truth annotations.
+        The leaderboard reports:
+
+        - bbox_mAP
+        - bbox_AP50
+        - segm_mAP
+        - segm_AP50 (default ranking)
+
+        Raw submissions are kept private; only scores and metadata are shown.
+            """
+        )
+
 
 if __name__ == "__main__":
     main()