removed run id

app.py

@@ -48,7 +48,7 @@ def init_leaderboard(dataframe):
             cant_deselect=[c.name for c in fields(AutoEvalColumn) if c.never_hidden],
             label="Select Columns to Display:",
         ),
-        search_columns=[AutoEvalColumn.run_id.name, AutoEvalColumn.technique.name],
+        search_columns=[AutoEvalColumn.technique.name],
         hide_columns=[c.name for c in fields(AutoEvalColumn) if c.hidden],
         filter_columns=[
             ColumnFilter(AutoEvalColumn.technique.name, type = "checkboxgroup", label = "technique"),

src/display/utils.py

@@ -17,9 +17,8 @@ class ColumnContent:
 
 ## Leaderboard columns
 # manually create class instead of using make_dataclass as our columns are not built dynamically, 
-# the given and known cols are the run id and technique, based on our results json file
+# the given and known cols are the techniques, based on our results json file
 class AutoEvalColumn:
-    run_id = ColumnContent("run_id", "str", True, never_hidden = True)
     technique = ColumnContent("technique", "str", True, never_hidden = True)
 
 # Column selection

src/leaderboard/read_evals.py

@@ -11,14 +11,14 @@ def get_raw_eval_results(results_path: str, requests_path: str) -> pd.DataFrame:
     """Reads all result json files in the leaderboard result file path, returns DataFrame
      The DataFrame contains rows, where each row is result from each run 
      Headers for each row:
-     run_id, technique, eval_method_1_results, eval_method_2_results, ..."""
+     technique, eval_method_1_results, eval_method_2_results, ..."""
     files = glob.glob(os.path.join(results_path, "**/*.json"), recursive = True)
     data_rows = []
 
     for file in files: # each json file has its own row in the data frame
         with open(file, 'r') as file_json:
             data = json.load(file_json)
-            row = {"run_id": data.get("run_id", None), "technique": data.get("technique_name", None)} # metric result is a nested dict
+            row = {"technique": data.get("technique_name", None)} # metric result is a nested dict
             for eval_method, result in data.get("metric_results", {}).items(): # used .get() to prevent KeyError
                 row[eval_method] = result.get('value') # multiple eval results under metric results
             data_rows.append(row)