Update app.py

app.py

@@ -128,6 +128,7 @@ def update_leaderboard_dataset_parallel(hivex_env, path):
 
     def process_model(model_id):
         meta = get_metadata(model_id)
+        # LOADED_MODEL_METADATA[model_id] = meta if meta is not None else ''
         if meta is None:
             return None
         user_id = model_id.split("/")[0]
@@ -137,20 +138,19 @@ def update_leaderboard_dataset_parallel(hivex_env, path):
         results = meta["model-index"][0]["results"][0]
         row["Task-ID"] = results["task"]["task-id"]
         row["Task"] = results["task"]["name"]
-        
         if "pattern-id" in results["task"] or "difficulty-id" in results["task"]:
             key = "Pattern" if "pattern-id" in results["task"] else "Difficulty"
             row[key] = (
                 pattern_map[results["task"]["pattern-id"]]
                 if "pattern-id" in results["task"]
-                else str(results["task"]["difficulty-id"])
+                else results["task"]["difficulty-id"]
             )
-    
+
         results_metrics = results["metrics"]
-    
+
         for result in results_metrics:
             row[result["name"]] = float(result["value"].split("+/-")[0].strip())
-    
+
         return row
 
     data = list(thread_map(process_model, model_ids, desc="Processing models"))
@@ -267,37 +267,17 @@ def filter_data(rl_env, task_id, selected_values, path):
     """
     data = get_data(rl_env, task_id, path)
     
-    # Determine which column to filter by
-    filter_column = None
-    if "Pattern" in data.columns:
-        filter_column = "Pattern"
-    elif "Difficulty" in data.columns:
-        filter_column = "Difficulty"
-
-    # If there are selected values and a filter column, filter the DataFrame
-    if selected_values and filter_column:
+    # If there are selected values, filter the DataFrame
+    if selected_values:
+        filter_column = "Pattern" if "Pattern" in data.columns else "Difficulty"
         data = data[data[filter_column].isin(selected_values)]
 
     return data
 
-
 def update_filtered_data(selected_values, rl_env, task_id, path):
     filtered_data = filter_data(rl_env, task_id, selected_values, path)
     return filtered_data
 
-
-def update_checkbox_group(rl_env, path):
-    dp_key, difficulty_pattern_ids = get_difficulty_pattern_ids_and_key(rl_env, path)
-    
-    # Debugging: Print to verify what's being returned
-    print(f"Updated dp_key: {dp_key}, difficulty_pattern_ids: {difficulty_pattern_ids}")
-    
-    if dp_key and difficulty_pattern_ids:
-        return {"choices": [str(dp_id) for dp_id in difficulty_pattern_ids], "label": dp_key}
-    else:
-        return {"choices": [], "label": "No Data Available"}
-        
-
 run_update_dataset()
 
 block = gr.Blocks(css=custom_css)  # Attach the custom CSS here
@@ -335,50 +315,49 @@ with block:
                 dp_key, difficulty_pattern_ids = get_difficulty_pattern_ids_and_key(
                     hivex_env["hivex_env"], path_
                 )
-        
-                if dp_key and difficulty_pattern_ids:
-                    selected_checkboxes = gr.CheckboxGroup(
-                        choices=[str(dp_id) for dp_id in difficulty_pattern_ids], label=dp_key
-                    )
-                else:
+
+                print(dp_key)
+                print(difficulty_pattern_ids)
+
+                # Check if dp_key is defined and difficulty_pattern_ids is not empty
+                if dp_key is not None and len(difficulty_pattern_ids) > 0:
                     selected_checkboxes = gr.CheckboxGroup(
-                        choices=[], label="No Data Available"
-                    )
-        
-                for task_id in range(0, hivex_env["task_count"]):
-                    task_title = convert_to_title_case(
-                        get_task(hivex_env["hivex_env"], task_id, path_)
+                        [str(dp_id) for dp_id in difficulty_pattern_ids], label=dp_key
                     )
-                    with gr.TabItem(f"Task {task_id}: {task_title}"):
-        
-                        # Display initial data
-                        data = get_data(hivex_env["hivex_env"], task_id, path_)
-                        row_count = len(data)
-        
-                        gr_dataframe = gr.DataFrame(
-                            value=data,
-                            headers=["User", "Model"],
-                            datatype=["markdown", "markdown"],
-                            row_count=(row_count, "fixed"),
-                        )
-        
-                        # Use gr.State to hold environment and task information
-                        rl_env_state = gr.State(value=hivex_env["hivex_env"])
-                        task_id_state = gr.State(value=task_id)
-                        path_state = gr.State(value=path_)
-        
-                        # Add a callback to update the DataFrame when checkboxes are changed
-                        selected_checkboxes.change(
-                            fn=lambda selected_values, rl_env, task_id, path: (
-                                update_filtered_data(selected_values, rl_env, task_id, path),
-                                update_checkbox_group(rl_env, path)
-                            ),
-                            inputs=[selected_checkboxes, rl_env_state, task_id_state, path_state],
-                            outputs=[gr_dataframe, selected_checkboxes],
+
+                    for task_id in range(0, hivex_env["task_count"]):
+                        task_title = convert_to_title_case(
+                            get_task(hivex_env["hivex_env"], task_id, path_)
                         )
+                        with gr.TabItem(f"Task {task_id}: {task_title}"):
+
+                            # Display initial data
+                            data = get_data(hivex_env["hivex_env"], task_id, path_)
+                            row_count = len(data)
+
+                            gr_dataframe = gr.DataFrame(
+                                value=data,
+                                headers=["User", "Model"],
+                                datatype=["markdown", "markdown"],
+                                row_count=(row_count, "fixed"),
+                            )
+
+                            # Use gr.State to hold environment and task information
+                            rl_env_state = gr.State(value=hivex_env["hivex_env"])
+                            task_id_state = gr.State(value=task_id)
+                            path_state = gr.State(value=path_)
+
+                            # Add a callback to update the DataFrame when checkboxes are changed
+                            selected_checkboxes.change(
+                                fn=update_filtered_data,
+                                inputs=[selected_checkboxes, rl_env_state, task_id_state, path_state],
+                                outputs=gr_dataframe,
+                            )
+                else:
+                    gr.HTML("<p>No difficulty or pattern data available for this environment.</p>")
 
 scheduler = BackgroundScheduler()
 scheduler.add_job(restart, "interval", seconds=86400)
 scheduler.start()
 
-block.launch()
+block.launch()