Add inference_framework to the queue column

app.py

@@ -355,21 +355,21 @@ def block_launch():
                                 num_fin = gr.Number(len(finished_eval_queue_df), label="Number of finished evaluations", visible=True, interactive=False)
                                 with gr.Row():
                                     finished_eval_table = gr.components.Dataframe(
-                                        value=finished_eval_queue_df, headers=EVAL_COLS, datatype=EVAL_TYPES, row_count=5
+                                        value=finished_eval_queue_df, headers=EVAL_COLS, datatype=EVAL_TYPES, row_count=6
                                     )
                         with gr.Accordion(f"🔄 Running Evaluation Queue", open=False):
                             with gr.Column():
                                 num_run = gr.Number(len(running_eval_queue_df), label="Number of running evaluations", visible=True, interactive=False)
                                 with gr.Row():
                                     running_eval_table = gr.components.Dataframe(
-                                        value=running_eval_queue_df, headers=EVAL_COLS, datatype=EVAL_TYPES, row_count=5
+                                        value=running_eval_queue_df, headers=EVAL_COLS, datatype=EVAL_TYPES, row_count=6
                                     )
                         with gr.Accordion(f"⏳ Scheduled Evaluation Queue", open=False):
                             with gr.Column():
                                 num_sche = gr.Number(len(pending_eval_queue_df), label="Number of scheduled evaluations", visible=True, interactive=False)
                                 with gr.Row():
                                     pending_eval_table = gr.components.Dataframe(
-                                        value=pending_eval_queue_df, headers=EVAL_COLS, datatype=EVAL_TYPES, row_count=5
+                                        value=pending_eval_queue_df, headers=EVAL_COLS, datatype=EVAL_TYPES, row_count=6
                                     )
                         # refresh_button.click(fn=update_submit_tables, 
                         #                      outputs=[finished_eval_table, running_eval_table, pending_eval_table])

src/display/utils.py

@@ -111,6 +111,7 @@ class EvalQueueColumn:  # Queue column
     private = ColumnContent("private", "bool", True)
     precision = ColumnContent("precision", "str", True)
     weight_type = ColumnContent("weight_type", "str", "Original")
+    model_framework = ColumnContent("inference_framework", "str", True)
     status = ColumnContent("status", "str", True)
 
 

src/populate.py

@@ -97,6 +97,7 @@ def get_evaluation_queue_df(save_path: str, cols: list) -> tuple[pd.DataFrame, p
 
             data[EvalQueueColumn.model.name] = make_clickable_model(data["model"])
             data[EvalQueueColumn.revision.name] = data.get("revision", "main")
+            data[EvalQueueColumn.model_framework.name] = data.get("inference_framework", "-")
 
             all_evals.append(data)
         elif ".md" not in entry:
@@ -109,6 +110,7 @@ def get_evaluation_queue_df(save_path: str, cols: list) -> tuple[pd.DataFrame, p
 
                 data[EvalQueueColumn.model.name] = make_clickable_model(data["model"])
                 data[EvalQueueColumn.revision.name] = data.get("revision", "main")
+                data[EvalQueueColumn.model_framework.name] = data.get("inference_framework", "-")
                 all_evals.append(data)
 
     pending_list = [e for e in all_evals if e["status"] in ["PENDING", "RERUN"]]