Change names and tab order

app.py

@@ -59,37 +59,37 @@ def main():
 
     with gr.Blocks(css=css) as block:
         with gr.Tabs():
-            with gr.TabItem("🏆 Leaderboard Benchmark 2"):
-                gr.Markdown("# ViDoRe 2: A new visual Document Retrieval Benchmark 📚🔍")
-                gr.Markdown("### A harder dataset benchmark for visual document retrieval 👀")
+            with gr.TabItem("🏆 ViDoRe V1"):
+                gr.Markdown("# ViDoRe: The Visual Document Retrieval Benchmark 1 📚🔍")
+                gr.Markdown("### From the paper - ColPali: Efficient Document Retrieval with Vision Language Models 👀")
 
                 gr.Markdown(
                     """
-                Visual Document Retrieval Benchmark 2 leaderboard. To submit results, refer to the corresponding tab.  
+                Visual Document Retrieval Benchmark 1 leaderboard. To submit results, refer to the corresponding tab.  
 
-                Refer to the [ColPali paper](https://arxiv.org/abs/2407.01449) for details on metrics and models.
+                Refer to the [ColPali paper](https://arxiv.org/abs/2407.01449) for details on metrics, tasks and models.
                 """
                 )
-                datasets_columns_2 = list(data_benchmark_2.columns[3:])
+                datasets_columns_1 = list(data_benchmark_1.columns[3:])
 
                 with gr.Row():
-                    metric_dropdown_2 = gr.Dropdown(choices=METRICS, value=initial_metric, label="Select Metric")
-                    research_textbox_2 = gr.Textbox(
+                    metric_dropdown_1 = gr.Dropdown(choices=METRICS, value=initial_metric, label="Select Metric")
+                    research_textbox_1 = gr.Textbox(
                         placeholder="🔍 Search Models... [press enter]",
                         label="Filter Models by Name",
                     )
-                    column_checkboxes_2 = gr.CheckboxGroup(
-                        choices=datasets_columns_2, value=datasets_columns_2, label="Select Columns to Display"
+                    column_checkboxes_1 = gr.CheckboxGroup(
+                        choices=datasets_columns_1, value=datasets_columns_1, label="Select Columns to Display"
                     )
 
                 with gr.Row():
-                    datatype_2 = ["number", "markdown"] + ["number"] * (NUM_DATASETS_2 + 1)
-                    dataframe_2 = gr.Dataframe(data_benchmark_2, datatype=datatype_2, type="pandas")
+                    datatype_1 = ["number", "markdown"] + ["number"] * (NUM_DATASETS_1 + 1)
+                    dataframe_1 = gr.Dataframe(data_benchmark_1, datatype=datatype_1, type="pandas")
 
-                def update_data_2(metric, search_term, selected_columns):
+                def update_data_1(metric, search_term, selected_columns):
                     model_handler.get_vidore_data(metric)
-                    data = model_handler.compute_averages(metric, benchmark_version=2)
-                    data = add_rank_and_format(data, benchmark_version=2)
+                    data = model_handler.compute_averages(metric, benchmark_version=1)
+                    data = add_rank_and_format(data, benchmark_version=1)
                     data = filter_models(data, search_term)
                     # data = remove_duplicates(data)  # Add this line
                     if selected_columns:
@@ -97,44 +97,36 @@ def main():
                     return data
 
                 with gr.Row():
-                    refresh_button_2 = gr.Button("Refresh")
-                    refresh_button_2.click(
-                        get_refresh_function(model_handler, benchmark_version=2),
-                        inputs=[metric_dropdown_2],
-                        outputs=dataframe_2,
+                    refresh_button_1 = gr.Button("Refresh")
+                    refresh_button_1.click(
+                        get_refresh_function(model_handler, benchmark_version=1),
+                        inputs=[metric_dropdown_1],
+                        outputs=dataframe_1,
                         concurrency_limit=20,
                     )
 
-                with gr.Row():
-                    gr.Markdown(
-                        """
-                    **Note**: For now, all models were evaluated using the vidore-benchmark package and custom retrievers on our side. 
-                    Those numbers are not numbers obtained from the organisations that released those models.
-                    """
-                    )
-
                 # Automatically refresh the dataframe when the dropdown value changes
-                metric_dropdown_2.change(
-                    get_refresh_function(model_handler, benchmark_version=2),
-                    inputs=[metric_dropdown_2],
-                    outputs=dataframe_2,
+                metric_dropdown_1.change(
+                    get_refresh_function(model_handler, benchmark_version=1),
+                    inputs=[metric_dropdown_1],
+                    outputs=dataframe_1,
                 )
-                research_textbox_2.submit(
-                    lambda metric, search_term, selected_columns: update_data_2(metric, search_term, selected_columns),
-                    inputs=[metric_dropdown_2, research_textbox_2, column_checkboxes_2],
-                    outputs=dataframe_2,
+                research_textbox_1.submit(
+                    lambda metric, search_term, selected_columns: update_data_1(metric, search_term, selected_columns),
+                    inputs=[metric_dropdown_1, research_textbox_1, column_checkboxes_1],
+                    outputs=dataframe_1,
                 )
-                column_checkboxes_2.change(
-                    lambda metric, search_term, selected_columns: update_data_2(metric, search_term, selected_columns),
-                    inputs=[metric_dropdown_2, research_textbox_2, column_checkboxes_2],
-                    outputs=dataframe_2,
+                column_checkboxes_1.change(
+                    lambda metric, search_term, selected_columns: update_data_1(metric, search_term, selected_columns),
+                    inputs=[metric_dropdown_1, research_textbox_1, column_checkboxes_1],
+                    outputs=dataframe_1,
                 )
 
                 gr.Markdown(
                     f"""
-                - **Total Datasets**: {NUM_DATASETS_2}
-                - **Total Scores**: {NUM_SCORES_2}
-                - **Total Models**: {NUM_MODELS_2}
+                - **Total Datasets**: {NUM_DATASETS_1}
+                - **Total Scores**: {NUM_SCORES_1}
+                - **Total Models**: {NUM_MODELS_1}
                 """
                     + r"""
                 Please consider citing:
@@ -152,37 +144,37 @@ def main():
                 ```
                 """
                 )
-            with gr.TabItem("🏆 Leaderboard Benchmark 1"):
-                gr.Markdown("# ViDoRe: The Visual Document Retrieval Benchmark 1 📚🔍")
-                gr.Markdown("### From the paper - ColPali: Efficient Document Retrieval with Vision Language Models 👀")
+            with gr.TabItem("🏆 ViDoRe V2"):
+                gr.Markdown("# ViDoRe V2: A new visual Document Retrieval Benchmark 📚🔍")
+                gr.Markdown("### A harder dataset benchmark for visual document retrieval 👀")
 
                 gr.Markdown(
                     """
-                Visual Document Retrieval Benchmark 1 leaderboard. To submit results, refer to the corresponding tab.  
+                Visual Document Retrieval Benchmark 2 leaderboard. To submit results, refer to the corresponding tab.  
 
-                Refer to the [ColPali paper](https://arxiv.org/abs/2407.01449) for details on metrics, tasks and models.
+                Refer to the [ColPali paper](https://arxiv.org/abs/2407.01449) for details on metrics and models.
                 """
                 )
-                datasets_columns_1 = list(data_benchmark_1.columns[3:])
+                datasets_columns_2 = list(data_benchmark_2.columns[3:])
 
                 with gr.Row():
-                    metric_dropdown_1 = gr.Dropdown(choices=METRICS, value=initial_metric, label="Select Metric")
-                    research_textbox_1 = gr.Textbox(
+                    metric_dropdown_2 = gr.Dropdown(choices=METRICS, value=initial_metric, label="Select Metric")
+                    research_textbox_2 = gr.Textbox(
                         placeholder="🔍 Search Models... [press enter]",
                         label="Filter Models by Name",
                     )
-                    column_checkboxes_1 = gr.CheckboxGroup(
-                        choices=datasets_columns_1, value=datasets_columns_1, label="Select Columns to Display"
+                    column_checkboxes_2 = gr.CheckboxGroup(
+                        choices=datasets_columns_2, value=datasets_columns_2, label="Select Columns to Display"
                     )
 
                 with gr.Row():
-                    datatype_1 = ["number", "markdown"] + ["number"] * (NUM_DATASETS_1 + 1)
-                    dataframe_1 = gr.Dataframe(data_benchmark_1, datatype=datatype_1, type="pandas")
+                    datatype_2 = ["number", "markdown"] + ["number"] * (NUM_DATASETS_2 + 1)
+                    dataframe_2 = gr.Dataframe(data_benchmark_2, datatype=datatype_2, type="pandas")
 
-                def update_data_1(metric, search_term, selected_columns):
+                def update_data_2(metric, search_term, selected_columns):
                     model_handler.get_vidore_data(metric)
-                    data = model_handler.compute_averages(metric, benchmark_version=1)
-                    data = add_rank_and_format(data, benchmark_version=1)
+                    data = model_handler.compute_averages(metric, benchmark_version=2)
+                    data = add_rank_and_format(data, benchmark_version=2)
                     data = filter_models(data, search_term)
                     # data = remove_duplicates(data)  # Add this line
                     if selected_columns:
@@ -190,36 +182,44 @@ def main():
                     return data
 
                 with gr.Row():
-                    refresh_button_1 = gr.Button("Refresh")
-                    refresh_button_1.click(
-                        get_refresh_function(model_handler, benchmark_version=1),
-                        inputs=[metric_dropdown_1],
-                        outputs=dataframe_1,
+                    refresh_button_2 = gr.Button("Refresh")
+                    refresh_button_2.click(
+                        get_refresh_function(model_handler, benchmark_version=2),
+                        inputs=[metric_dropdown_2],
+                        outputs=dataframe_2,
                         concurrency_limit=20,
                     )
 
+                with gr.Row():
+                    gr.Markdown(
+                        """
+                    **Note**: For now, all models were evaluated using the vidore-benchmark package and custom retrievers on our side. 
+                    Those numbers are not numbers obtained from the organisations that released those models.
+                    """
+                    )
+
                 # Automatically refresh the dataframe when the dropdown value changes
-                metric_dropdown_1.change(
-                    get_refresh_function(model_handler, benchmark_version=1),
-                    inputs=[metric_dropdown_1],
-                    outputs=dataframe_1,
+                metric_dropdown_2.change(
+                    get_refresh_function(model_handler, benchmark_version=2),
+                    inputs=[metric_dropdown_2],
+                    outputs=dataframe_2,
                 )
-                research_textbox_1.submit(
-                    lambda metric, search_term, selected_columns: update_data_1(metric, search_term, selected_columns),
-                    inputs=[metric_dropdown_1, research_textbox_1, column_checkboxes_1],
-                    outputs=dataframe_1,
+                research_textbox_2.submit(
+                    lambda metric, search_term, selected_columns: update_data_2(metric, search_term, selected_columns),
+                    inputs=[metric_dropdown_2, research_textbox_2, column_checkboxes_2],
+                    outputs=dataframe_2,
                 )
-                column_checkboxes_1.change(
-                    lambda metric, search_term, selected_columns: update_data_1(metric, search_term, selected_columns),
-                    inputs=[metric_dropdown_1, research_textbox_1, column_checkboxes_1],
-                    outputs=dataframe_1,
+                column_checkboxes_2.change(
+                    lambda metric, search_term, selected_columns: update_data_2(metric, search_term, selected_columns),
+                    inputs=[metric_dropdown_2, research_textbox_2, column_checkboxes_2],
+                    outputs=dataframe_2,
                 )
 
                 gr.Markdown(
                     f"""
-                - **Total Datasets**: {NUM_DATASETS_1}
-                - **Total Scores**: {NUM_SCORES_1}
-                - **Total Models**: {NUM_MODELS_1}
+                - **Total Datasets**: {NUM_DATASETS_2}
+                - **Total Scores**: {NUM_SCORES_2}
+                - **Total Models**: {NUM_MODELS_2}
                 """
                     + r"""
                 Please consider citing:
@@ -237,6 +237,7 @@ def main():
                 ```
                 """
                 )
+            
             with gr.TabItem("📚 Submit your model"):
                 gr.Markdown("# How to Submit a New Model to the Leaderboard")
                 gr.Markdown(