requested_models.append(model_id)

app.py

@@ -16,8 +16,6 @@ leaderboard_df = pd.read_csv("leaderboard.csv")
 # Get already evaluated or requested models
 evaluated_models = leaderboard_df["model"].tolist()
 requested_models = eval_requests.get_requested_models()
-evaluated_or_requested_models = evaluated_models + requested_models
-print(evaluated_or_requested_models)
 
 # Format the dataframe
 for col in leaderboard_df.columns:
@@ -60,7 +58,11 @@ with gr.Blocks() as leaderboard_app:
                 with gr.Column():
                     md_submission_result = gr.Markdown()
                     btn_submitt = gr.Button(value="🚀 Request")
-                    btn_submitt.click(eval_requests.request_model, [model_id], md_submission_result)
+                    btn_submitt.click(
+                            fn=eval_requests.request_model,
+                            inputs=[model_id, evaluated_models, requested_models],
+                            outputs=md_submission_result,
+                        )
 
         with gr.TabItem("☢️ Evaluate", elem_id="od-benchmark-tab-table", id=3):
             with gr.Column():

utils/eval_requests.py

@@ -40,7 +40,7 @@ def is_model_on_hub(model_id):
         return "was not found on hub!"
 
 
-def request_model(model_id):
+def request_model(model_id, evaluated_models, requested_models):
 
     def styled_error(error):
         return f"<p style='color: red; font-size: 20px; text-align: center;'>{error}</p>"
@@ -48,20 +48,22 @@ def request_model(model_id):
     def styled_message(message):
         return f"<p style='color: green; font-size: 20px; text-align: center;'>{message}</p>"
     
-    # # Check if the model is on the hub
-    # error_msg = is_model_on_hub(model_id)
-    # if error_msg != None:
-    #     return styled_error(f"{model_id} {error_msg}")
+    # Check if the model is on the hub
+    error_msg = is_model_on_hub(model_id)
+    if error_msg != None:
+        return styled_error(f"{model_id} {error_msg}")
     
-    # # Check if the model was already requested
-    # with open("requested_models.txt", "r") as f:
-    #     requested_models_list = f.read().splitlines()
-    # if model_id in requested_models_list:
-    #     return styled_error(f"A request for {model_id} was already made.")
+    # Check if the model was already evaluated
+    if model_id in evaluated_models:
+        return styled_error(f"{model_id} has already been evaluated.")
     
-    # # Add the model to the local evaluation queue
-    # with open("requested_models.txt", "a") as f:
-    #     f.write(model_id + "\n")
+    # Check if the model was already requested
+    if model_id in requested_models:
+        return styled_error(f"A request for {model_id} was already made.")
+    
+    # Add the model to the local evaluation queue
+    with open("requested_models.txt", "a") as f:
+        f.write(model_id + "\n")
 
     # Push the request file to the private dataset repo
     unique_request_filename = str(uuid.uuid4()) + ".json"
@@ -76,6 +78,9 @@ def request_model(model_id):
             commit_message=f"{model_id} added to the evaluation queue.",
     )
 
+    # Record the request
+    requested_models.append(model_id)
+
     return styled_message("🤗 Your request has been submitted and will be evaluated as soon as possible!")