F

src/populate.py

@@ -50,16 +50,17 @@ def get_evaluation_queue_df(save_path: str, cols: list) -> list[pd.DataFrame]:
     all_evals = []
 
     for entry in entries:
-        file_path = os.path.join(save_path, entry, "eval_request.json")
-        with open(file_path) as fp:
-            data = json.load(fp)
+        if not ".txt" in entry:
+            file_path = os.path.join(save_path, entry, "eval_request.json")
+            with open(file_path) as fp:
+                data = json.load(fp)
 
-        data[EvalQueueColumn.model.name] = make_clickable_model(data["model"])
-        data[EvalQueueColumn.revision.name] = data.get("revision", "main")
-        data[EvalQueueColumn.output_format.name] = data.get("output_format")
-        data[EvalQueueColumn.dataset_version.name] = file_path.split("/")[-3]
+            data[EvalQueueColumn.model.name] = make_clickable_model(data["model"])
+            data[EvalQueueColumn.revision.name] = data.get("revision", "main")
+            data[EvalQueueColumn.output_format.name] = data.get("output_format")
+            data[EvalQueueColumn.dataset_version.name] = file_path.split("/")[-3]
 
-        all_evals.append(data)
+            all_evals.append(data)
 
     pending_list = [e for e in all_evals if e["status"] in ["PENDING", "RERUN"]]
     running_list = [e for e in all_evals if e["status"] == "RUNNING"]