Add Results tab

app.py

@@ -6,7 +6,17 @@ from huggingface_hub import HfFileSystem
 
 
 RESULTS_DATASET_ID = "datasets/open-llm-leaderboard/results"
-
+EXCLUDED_KEYS =  {
+    "pretty_env_info",
+    "chat_template",
+    "group_subtasks",
+}
+EXCLUDED_RESULTS_KEYS = {
+    "leaderboard",
+}
+EXCLUDED_RESULTS_LEADERBOARDS_KEYS = {
+    "leaderboard",
+}
 
 fs = HfFileSystem()
 
@@ -30,24 +40,73 @@ def get_result_path_from_model(model_id, result_path_per_model):
     return result_path_per_model[model_id]
 
 
-def load_result(result_path) -> pd.DataFrame:
+def load_data(result_path) -> pd.DataFrame:
     with fs.open(result_path, "r") as f:
         data = json.load(f)
+    return data
+    # model_name = data.get("model_name", "Model")
+    # df = pd.json_normalize([data])
+    # return df.iloc[0].rename_axis("Parameters").rename(model_name).to_frame()  # .reset_index()
+
+
+def load_result(model_id):
+    result_path = get_result_path_from_model(model_id, latest_result_path_per_model)
+    data = load_data(result_path)
     model_name = data.get("model_name", "Model")
-    df = pd.json_normalize([data])
+    result = [
+        to_vertical(to_dataframe_all(data), model_name),
+        to_vertical(to_dataframe_results(data), model_name)
+    ]
+    return result
+
+
+def to_dataframe(data):
+    return pd.DataFrame.from_records([data])
+
+
+def to_vertical(df, model_name):
     return df.iloc[0].rename_axis("Parameters").rename(model_name).to_frame()  # .reset_index()
 
 
-def render_result_1(model_id, results):
-    result_path = get_result_path_from_model(model_id, latest_result_path_per_model)
-    result = load_result(result_path)
-    return pd.concat([result, results.iloc[:, [0, 2]].set_index("Parameters")], axis=1).reset_index()
+def to_dataframe_all(data):
+    return pd.json_normalize([{key: value for key, value in data.items() if key not in EXCLUDED_KEYS}])
 
 
-def render_result_2(model_id, results):
-    result_path = get_result_path_from_model(model_id, latest_result_path_per_model)
-    result = load_result(result_path)
-    return pd.concat([results.iloc[:, [0, 1]].set_index("Parameters"), result], axis=1).reset_index()
+def to_dataframe_results(data):
+    dfs = {}
+    for key in data["results"]:
+        if key not in EXCLUDED_RESULTS_KEYS:  # key.startswith("leaderboard_"):
+            name = key[len("leaderboard_"):]
+            df = to_dataframe(
+                {
+                    key: value
+                    for key, value in data["results"][key].items()
+                    if key not in EXCLUDED_RESULTS_LEADERBOARDS_KEYS
+                }
+            )
+            # df.drop(columns=["alias"])
+            # df.columns = pd.MultiIndex.from_product([[name], df.columns])
+            df.columns = [f"{name}.{column}" for column in df.columns]
+            dfs[name] = df
+    return pd.concat(dfs.values(), axis="columns")
+
+
+def concat_result_1(result_1, results):
+    return pd.concat([result_1, results.iloc[:, [0, 2]].set_index("Parameters")], axis=1).reset_index()
+
+
+def concat_result_2(result_2, results):
+    return pd.concat([results.iloc[:, [0, 1]].set_index("Parameters"), result_2], axis=1).reset_index()
+
+
+def render_result_1(model_id, *results):
+    result = load_result(model_id)
+    return [concat_result_1(*result_args) for result_args in zip(result, results)]
+
+
+def render_result_2(model_id, *results):
+    result = load_result(model_id)
+    return [concat_result_2(*result_args) for result_args in zip(result, results)]
 
 
 # if __name__ == "__main__":
@@ -66,23 +125,32 @@ with gr.Blocks(fill_height=True) as demo:
             load_btn_2 = gr.Button("Load")
 
     with gr.Row():
-        compared_results = gr.Dataframe(
-            label="Results",
-            headers=["Parameters", "Result-1", "Result-2"],
-            interactive=False,
-            column_widths=["30%", "30%", "30%"],
-            wrap=True
-        )
+        with gr.Tab("All"):
+            compared_results_all = gr.Dataframe(
+                label="Results",
+                headers=["Parameters", "Model-1", "Model-2"],
+                interactive=False,
+                column_widths=["30%", "30%", "30%"],
+                wrap=True,
+            )
+        with gr.Tab("Results"):
+            compared_results_results = gr.Dataframe(
+                label="Results",
+                headers=["Parameters", "Model-1", "Model-2"],
+                interactive=False,
+                column_widths=["30%", "30%", "30%"],
+                wrap=True,
+            )
 
     load_btn_1.click(
         fn=render_result_1,
-        inputs=[model_id_1, compared_results],
-        outputs=compared_results,
+        inputs=[model_id_1, compared_results_all, compared_results_results],
+        outputs=[compared_results_all, compared_results_results],
     )
     load_btn_2.click(
         fn=render_result_2,
-        inputs=[model_id_2, compared_results],
-        outputs=compared_results,
+        inputs=[model_id_2, compared_results_all, compared_results_results],
+        outputs=[compared_results_all, compared_results_results],
     )
 
 demo.launch()