revert to correct usage of ModelDetails (without api)

app.py

@@ -289,7 +289,7 @@ with demo:
             with gr.Row():
                 with gr.Column():
                     model_api = gr.Dropdown(
-                        choices=[a.value.api for a in ModelAPI],
+                        choices=[a.value.name for a in ModelAPI],
                         label="Model API",
                         multiselect=False,
                         value="hf",

src/display/utils.py

@@ -59,13 +59,12 @@ class ModelDetails:
     name: str
     display_name: str = ""
     symbol: str = "" # emoji
-    api: str = "hf"
 
 
 class ModelAPI(Enum):
-    hf = ModelDetails(name="", api="hf")
-    openai = ModelDetails(name="", api="openai-chat-completions")
-    anthropic = ModelDetails(name="", api="anthropic-chat-completions")
+    hf = ModelDetails(name="hf")
+    openai = ModelDetails(name="openai-chat-completions")
+    anthropic = ModelDetails(name="anthropic-chat-completions")
 
 
 class ModelType(Enum):

src/leaderboard/read_evals.py

@@ -109,6 +109,7 @@ class EvalResult:
 
     def to_dict(self):
         """Converts the Eval Result to a dict compatible with our dataframe display"""
+        print([v for v in self.results.values() if v is not None])
         average = sum([v for v in self.results.values() if v is not None]) / len(Tasks)
         data_dict = {
             "eval_name": self.eval_name,  # not a column, just a save name,
@@ -125,6 +126,7 @@ class EvalResult:
             AutoEvalColumn.params.name: self.num_params,
             AutoEvalColumn.still_on_hub.name: self.still_on_hub,
         }
+        print(data_dict)
 
         for task in Tasks:
             data_dict[task.value.col_name] = self.results[task.value.benchmark]
@@ -157,14 +159,11 @@ def get_request_file_for_model(requests_path, model_name, precision):
 def get_raw_eval_results(results_path: str, requests_path: str) -> list[EvalResult]:
     """From the path of the results folder root, extract all needed info for results"""
     model_result_filepaths = []
-    print("Files in dir:")
-    print(os.listdir("."))
 
     for root, _, files in os.walk(results_path):
         # We should only have json files in model results
         if len(files) == 0 or any([not f.endswith(".json") for f in files]):
             continue
-        print(f"root: {root}, files: {[file for file in files]}")
 
         # Sort the files by date
         try:
@@ -175,7 +174,6 @@ def get_raw_eval_results(results_path: str, requests_path: str) -> list[EvalResu
         for file in files:
             model_result_filepaths.append(os.path.join(root, file))
 
-    print(f"Model results: {model_result_filepaths}")
 
     eval_results = {}
     for model_result_filepath in model_result_filepaths: