app fixed

app.py

@@ -1,6 +1,7 @@
 import json
 from pathlib import Path
 from typing import List, Dict
+import os
 
 import gradio as gr
 from pydantic import BaseModel, Field, field_validator
@@ -8,6 +9,20 @@ from pydantic import BaseModel, Field, field_validator
 # --------------- Configuration ---------------
 LEADERBOARD_PATH = Path("leaderboard_data.json")
 
+# Initialize with default data
+DEFAULT_DATA = [{
+    "model_name": "example/model",
+    "bleu": 0.5,
+    "llm_pass_1": 0.5,
+    "llm_pass_5": 0.5,
+    "llm_pass_10": 0.5,
+    "metrics": {
+        "readability": 5, "relevance": 5, "explanation_clarity": 5,
+        "problem_identification": 5, "actionability": 5, "completeness": 5,
+        "specificity": 5, "contextual_adequacy": 5, "consistency": 5, "brevity": 5
+    }
+}]
+
 # --------------- Data models ---------------
 class Metrics(BaseModel):
     readability: int
@@ -49,20 +64,8 @@ def _load_leaderboard() -> List[Dict]:
     """Load leaderboard data with persistent storage support."""
     if not LEADERBOARD_PATH.exists():
         # Create default example data
-        default_data = [{
-            "model_name": "example/model",
-            "bleu": 0.5,
-            "llm_pass_1": 0.5,
-            "llm_pass_5": 0.5,
-            "llm_pass_10": 0.5,
-            "metrics": {
-                "readability": 5, "relevance": 5, "explanation_clarity": 5,
-                "problem_identification": 5, "actionability": 5, "completeness": 5,
-                "specificity": 5, "contextual_adequacy": 5, "consistency": 5, "brevity": 5
-            }
-        }]
-        _save_leaderboard(default_data)
-        return default_data
+        _save_leaderboard(DEFAULT_DATA)
+        return DEFAULT_DATA
     
     try:
         with LEADERBOARD_PATH.open("r", encoding="utf-8") as f:
@@ -85,9 +88,10 @@ def _save_leaderboard(data: List[Dict]):
 
 # --------------- Table data functions ---------------
 
-def _table_data() -> List[List]:
+def _table_data(data: List[Dict] = None) -> List[List]:
     """Get main metrics table data."""
-    data = _load_leaderboard()
+    if data is None:
+        data = _load_leaderboard()
     if not data:
         return []
     data.sort(key=lambda x: x["llm_pass_1"], reverse=True)
@@ -105,9 +109,10 @@ def _table_data() -> List[List]:
     return table_rows
 
 
-def _multimetric_table_data() -> List[List]:
+def _multimetric_table_data(data: List[Dict] = None) -> List[List]:
     """Get multi-metric table data."""
-    data = _load_leaderboard()
+    if data is None:
+        data = _load_leaderboard()
     if not data:
         return []
     data.sort(key=lambda x: x["llm_pass_1"], reverse=True)
@@ -134,6 +139,7 @@ def _multimetric_table_data() -> List[List]:
 # --------------- Gradio callbacks ---------------
 
 def submit_model(
+    current_data: List[Dict],
     model_name: str,
     bleu: float,
     llm_pass_1: float,
@@ -172,15 +178,16 @@ def submit_model(
             },
         )
     except Exception as e:
-        return _table_data(), _multimetric_table_data(), f"❌ Submission failed: {e}"
+        return current_data, _table_data(current_data), _multimetric_table_data(current_data), f"❌ Submission failed: {e}"
 
-    data = _load_leaderboard()
+    # Use current data from state
+    data = current_data.copy() if current_data else []
     # Replace existing model entry if any
     data = [d for d in data if d["model_name"] != entry.model_name]
     data.append(entry.dict())
     _save_leaderboard(data)
 
-    return _table_data(), _multimetric_table_data(), "✅ Submission recorded!"
+    return data, _table_data(data), _multimetric_table_data(data), "✅ Submission recorded!"
 
 
 # --------------- Interface ---------------
@@ -188,8 +195,12 @@ with gr.Blocks(title="CodeReview Leaderboard") as demo:
     gr.Markdown("""# 🏆 CodeReview Leaderboard\nSubmit your model results below. Leaderboard is sorted by **Pass@1**. """)
 
     # Initialize table data
-    initial_data = _table_data()
-    initial_multimetric_data = _multimetric_table_data()
+    initial_leaderboard_data = _load_leaderboard()
+    initial_data = _table_data(initial_leaderboard_data)
+    initial_multimetric_data = _multimetric_table_data(initial_leaderboard_data)
+    
+    # State to store leaderboard data
+    leaderboard_state = gr.State(value=initial_leaderboard_data)
     
     leaderboard_df = gr.Dataframe(
         headers=["Model", "BLEU", "Pass@1", "Pass@5", "Pass@10"],
@@ -234,6 +245,7 @@ with gr.Blocks(title="CodeReview Leaderboard") as demo:
         submit_btn.click(
             fn=submit_model,
             inputs=[
+                leaderboard_state,
                 model_name_inp,
                 bleu_inp,
                 pass1_inp,
@@ -250,7 +262,7 @@ with gr.Blocks(title="CodeReview Leaderboard") as demo:
                 consistency_inp,
                 brevity_inp,
             ],
-            outputs=[leaderboard_df, multimetric_df, status_markdown],
+            outputs=[leaderboard_state, leaderboard_df, multimetric_df, status_markdown],
             api_name="submit_model",
         )