fix: minor before refacto

app.py

@@ -149,19 +149,19 @@ def get_vidore_data():
 
                         with open(result_path) as f:
                             results = json.load(f)
-                        # keep only ndcg_at_5
+
                         for dataset in results:
                             results[dataset] = {key: value for key, value in results[dataset].items() if metric in key}
 
                         MODEL_INFOS[model_name] = {"meta":meta, "results": results}
-                    except:
+                    except Exception as e:  
+                        print(f"Error loading {model_name} - {e}")
                         continue
-
+    
     model_res = {}
     df = None
     if len(MODEL_INFOS) > 0:
         for model in MODEL_INFOS.keys():
-            print(model)
             res = MODEL_INFOS[model]["results"]
             dataset_res = {}
             for dataset in res.keys():
@@ -171,12 +171,11 @@ def get_vidore_data():
             model_res[model] = dataset_res
 
         df = pd.DataFrame(model_res).T
-
-        # add average
-        # df["average"] = df.mean(axis=1)
-        # df = df.sort_values(by="average", ascending=False)
-        # # round to 2 decimals
-        # df = df.round(2)
+        
+    #save model_infos
+    with open(model_infos_path, "w") as f:
+        json.dump(MODEL_INFOS, f)
+    
     return df
 
 
@@ -219,11 +218,6 @@ def get_refresh_function():
 
     return _refresh
 
-
-def get_refresh_overall_function():
-    return lambda: get_refresh_function()
-
-
 data = get_vidore_data()
 data = add_rank_and_format(data)
 
@@ -236,7 +230,7 @@ with gr.Blocks(css=css) as block:
     gr.Markdown("## From the paper - ColPali: Efficient Document Retrieval with Vision Language Models 👀")
 
     gr.Markdown(
-        f"""
+        """
     Visual Document Retrieval Benchmark leaderboard. To submit, refer to the <a href="https://github.com/tonywu71/vidore-benchmark/" target="_blank" style="text-decoration: underline">ViDoRe GitHub repository</a>.  Refer to the [ColPali paper](https://arxiv.org/abs/XXXX.XXXXX) for details on metrics, tasks and models.
     """
     )