Refactor submit_gradio_module to improve layout and enhance model submission functionality

app.py

@@ -72,7 +72,7 @@ def search_leaderboard(model_name, columns_to_show):
 def main():
     global df, original_columns_order
     df = load_retrieval_results()
-    df[["Model"]] = df[["Model"]].applymap(lambda x: f'<a href="https://huggingface.co/{x}" target="_blank">{x}</a>')
+    df[["Model"]] = df[["Model"]].map(lambda x: f'<a href="https://huggingface.co/{x}" target="_blank">{x}</a>')
     df.drop(columns=["Revision", "Precision", "Task"], inplace=True)
     df.sort_values("Web Search Dataset (Overall Score)", ascending=False, inplace=True)
 
@@ -117,7 +117,8 @@ def main():
                             outputs=retrieval_leaderboard
                         )
                         
-                    submit_gradio_module("Retriever")
+                    with gr.Tab("Submit Retriever"):
+                        submit_gradio_module("Retriever")
 
             with gr.Tab("Reranking"):
                 with gr.Tabs():
@@ -141,7 +142,10 @@ def main():
                             inputs=search_box_reranker,
                             outputs=reranker_leaderboard
                         )
-                    submit_gradio_module("Reranker")
+
+                    with gr.Tab("Submit Reranker"):
+                        submit_gradio_module("Reranker")
+
                     
             # with gr.Tab("LLM Context Answering"):
             #     with gr.Tabs():

utils.py

@@ -185,87 +185,84 @@ def load_requests(status_folder):
 
 def submit_gradio_module(task_type):
     var = gr.State(value=task_type)
-    with gr.Tab(f"Submit {task_type}") as submitter_tab: 
-        with gr.Row(equal_height=True):
-            model_name_input = gr.Textbox(
-                label="Model", 
-                placeholder="Enter the full model name from HuggingFace Hub (e.g., intfloat/multilingual-e5-large-instruct)",
-                scale=4,
-            )
-            fetch_data_button = gr.Button(value="Auto Fetch Model Info", variant="secondary")
-        
-        with gr.Row():
-            precision_input = gr.Dropdown(
-                choices=["F16", "F32", "BF16", "I8", "U8", "I16"], 
-                label="Precision",
-                value="F16"
-            )
-            license_input = gr.Textbox(
-                label="License", 
-                placeholder="Enter the license type (Generic one is 'Open' in case no License is provided)", 
-                value="Open"
-            )
-            revision_input = gr.Textbox(
-                label="Revision", 
-                placeholder="main", 
-                value="main"
-            )
-        
-        with gr.Row():
-            params_input = gr.Textbox(
-                label="Params (in Millions)",
-                interactive=False,
-            )
-            num_downloads_input = gr.Textbox(
-                label="Number of Downloads",
-                interactive=False,
-            )
-            num_likes_input = gr.Textbox(
-                label="Number of Likes",
-                interactive=False,
-            )
-        
-        submit_button = gr.Button("Submit Model", variant="primary")
-        submission_result = gr.Markdown()
-        fetch_outputs = [precision_input, license_input, params_input, num_downloads_input, num_likes_input]
-
-        fetch_data_button.click(
-            fetch_model_information,
-            inputs=[model_name_input],
-            outputs=fetch_outputs
+    with gr.Row(equal_height=True):
+        model_name_input = gr.Textbox(
+            label="Model", 
+            placeholder="Enter the full model name from HuggingFace Hub (e.g., intfloat/multilingual-e5-large-instruct)",
+            scale=4,
+        )
+        fetch_data_button = gr.Button(value="Auto Fetch Model Info", variant="secondary")
+    
+    with gr.Row():
+        precision_input = gr.Dropdown(
+            choices=["F16", "F32", "BF16", "I8", "U8", "I16"], 
+            label="Precision",
+            value="F16"
+        )
+        license_input = gr.Textbox(
+            label="License", 
+            placeholder="Enter the license type (Generic one is 'Open' in case no License is provided)", 
+            value="Open"
+        )
+        revision_input = gr.Textbox(
+            label="Revision", 
+            placeholder="main", 
+            value="main"
+        )
+    
+    with gr.Row():
+        params_input = gr.Textbox(
+            label="Params (in Millions)",
+            interactive=False,
         )
-        model_name_input.submit(
-            fetch_model_information,
-            inputs=[model_name_input],
-            outputs=fetch_outputs
+        num_downloads_input = gr.Textbox(
+            label="Number of Downloads",
+            interactive=False,
         )
-        submit_button.click(
-            submit_model,
-            inputs=[model_name_input, revision_input, precision_input, params_input, license_input, var],
-            outputs=submission_result
+        num_likes_input = gr.Textbox(
+            label="Number of Likes",
+            interactive=False,
         )
-        
-        # Load pending, finished, and failed requests
-        df_pending = load_requests('pending')
-        df_finished = load_requests('finished')
-        df_failed = load_requests('failed')
+    
+    submit_button = gr.Button("Submit Model", variant="primary")
+    submission_result = gr.Markdown()
+    fetch_outputs = [precision_input, license_input, params_input, num_downloads_input, num_likes_input]
 
-        # Display the tables
-        gr.Markdown("## Evaluation Status")
-        with gr.Accordion(f"Pending Evaluations ({len(df_pending)})", open=False):
-            if not df_pending.empty:
-                gr.Dataframe(df_pending)
-            else:
-                gr.Markdown("No pending evaluations.")
-        with gr.Accordion(f"Finished Evaluations ({len(df_finished)})", open=False):
-            if not df_finished.empty:
-                gr.Dataframe(df_finished)
-            else:
-                gr.Markdown("No finished evaluations.")
-        with gr.Accordion(f"Failed Evaluations ({len(df_failed)})", open=False):
-            if not df_failed.empty:
-                gr.Dataframe(df_failed)
-            else:
-                gr.Markdown("No failed evaluations.")
+    fetch_data_button.click(
+        fetch_model_information,
+        inputs=[model_name_input],
+        outputs=fetch_outputs
+    )
+    model_name_input.submit(
+        fetch_model_information,
+        inputs=[model_name_input],
+        outputs=fetch_outputs
+    )
+    submit_button.click(
+        submit_model,
+        inputs=[model_name_input, revision_input, precision_input, params_input, license_input, var],
+        outputs=submission_result
+    )
+    
+    # Load pending, finished, and failed requests
+    df_pending = load_requests('pending')
+    df_finished = load_requests('finished')
+    df_failed = load_requests('failed')
 
-    return submitter_tab
+    # Display the tables
+    gr.Markdown("## Evaluation Status")
+    with gr.Accordion(f"Pending Evaluations ({len(df_pending)})", open=False):
+        if not df_pending.empty:
+            gr.Dataframe(df_pending)
+        else:
+            gr.Markdown("No pending evaluations.")
+    with gr.Accordion(f"Finished Evaluations ({len(df_finished)})", open=False):
+        if not df_finished.empty:
+            gr.Dataframe(df_finished)
+        else:
+            gr.Markdown("No finished evaluations.")
+    with gr.Accordion(f"Failed Evaluations ({len(df_failed)})", open=False):
+        if not df_failed.empty:
+            gr.Dataframe(df_failed)
+        else:
+            gr.Markdown("No failed evaluations.")