Enhance model submission function to include task parameter and update evaluation checks

utils.py

@@ -44,11 +44,11 @@ def fetch_model_information(model_name):
         return
     return gr.update(choices=supported_precisions, value=supported_precisions[0]), num_parameters, license
 
-def submit_model(model_name, revision, precision, params, license):
+def submit_model(model_name, revision, precision, params, license, task):
     # Load existing evaluations
     df_retrieval = load_retrieval_results()
     
-    existing_models_results = df_retrieval[['Model', 'Revision', 'Precision']]
+    existing_models_results = df_retrieval[['Model', 'Revision', 'Precision', "Task"]]
 
     # Handle 'Missing' precision
     if precision == 'Missing':
@@ -63,33 +63,37 @@ def submit_model(model_name, revision, precision, params, license):
     # Check if model is already evaluated
     model_exists_in_results = ((existing_models_results['Model'] == model_name) &
                                (existing_models_results['Revision'] == revision) &
-                               (existing_models_results['Precision'] == precision)).any()
+                               (existing_models_results['Precision'] == precision) &
+                               (existing_models_results['Task'] == task)).any()
     if model_exists_in_results:
-        return f"**Model '{model_name}' with revision '{revision}' and precision '{precision}' has already been evaluated.**"
+        return gr.Info(f"Model '{model_name}' with revision '{revision}' and precision '{precision}' for task '{task}' has already been evaluated.")
 
     # Check if model is in pending requests
     if not df_pending.empty:
         existing_models_pending = df_pending[['model_name', 'revision', 'precision']]
         model_exists_in_pending = ((existing_models_pending['model_name'] == model_name) &
                                    (existing_models_pending['revision'] == revision) &
-                                   (existing_models_pending['precision'] == precision)).any()
+                                   (existing_models_pending['precision'] == precision) &
+                                      (existing_models_pending['task'] == task)).any()
         if model_exists_in_pending:
-            return f"**Model '{model_name}' with revision '{revision}' and precision '{precision}' is already in the pending evaluations.**"
+            return gr.Info(f"Model '{model_name}' with revision '{revision}' and precision '{precision}' for task '{task}' is already in the evaluation queue.")
 
     # Check if model is in finished requests
     if not df_finished.empty:
         existing_models_finished = df_finished[['model_name', 'revision', 'precision']]
         model_exists_in_finished = ((existing_models_finished['model_name'] == model_name) &
                                     (existing_models_finished['revision'] == revision) &
-                                    (existing_models_finished['precision'] == precision)).any()
+                                    (existing_models_finished['precision'] == precision) &
+                                    (existing_models_finished['task'] == task)).any()
         if model_exists_in_finished:
-            return f"**Model '{model_name}' with revision '{revision}' and precision '{precision}' has already been evaluated.**"
+            return gr.Info(f"Model '{model_name}' with revision '{revision}' and precision '{precision}' for task '{task}' has already been evaluated.")
 
     # Check if model exists on HuggingFace Hub
     try:
         api.model_info(model_name)
     except Exception as e:
-        return f"**Error: Could not find model '{model_name}' on HuggingFace Hub. Please ensure the model name is correct and the model is public.**"
+        print(f"Error fetching model info: {e}")
+        return gr.Error(f"**Error: Model '{model_name}' not found on HuggingFace Hub.**")
 
     # Proceed with submission
     status = "PENDING"
@@ -173,7 +177,6 @@ def load_requests(status_folder):
 
 
 def submit_gradio_module(type):
-
     with gr.Tab(f"Submit {type}") as submitter_tab: 
         with gr.Row(equal_height=True):
             model_name_input = gr.Textbox(