add radio button for selecting averaging method

app.py

@@ -19,38 +19,40 @@ local_path = Path(sys.path[0])
 test_cases = [ {"predictions":[1,2,3,4,5], "references":[1,2,5,4,3]} ] # configure this randomly using randint generator and feature names?
 
 # configure this based on the input type, etc. for launch_gradio_widget
-def compute(input_df: pd.DataFrame):
+def compute(input_df: pd.DataFrame, method: str):
+    
+    metric = FixedF1(average=method if method != "None" else None)
 
     cols = [col for col in input_df.columns]
-
     predicted = [int(num) for num in input_df[cols[0]].to_list()]
     references = [int(num) for num in input_df[cols[1]].to_list()]
 
     metric.add_batch(predictions=predicted, references=references)
-    
     outputs = metric.compute()
 
     f"Your metrics are as follows: \n {outputs}"
 
 space = gr.Interface(
     fn=compute,
-    inputs=gr.Dataframe(
+    inputs=[
+        gr.Dataframe(
         headers=feature_names,
         col_count=len(feature_names),
         row_count=5,
         datatype=json_to_string_type(gradio_input_types),
         ),
+        gr.Radio(
+            ["weighted", "micro", "macro", "None", "binary"], 
+            label="Averaging Method", 
+            info="Method for averaging the F1 score across labels. `Binary` only works if you are evaluating a binary classification model."
+        )
+    ],
     outputs=gr.Textbox(label=metric.name),
-    description=(
-        metric.info.description + "\nIf this is a text-based metric, make sure to wrap your input in double quotes."
-        " Alternatively you can use a JSON-formatted list as input."
-    ),
+    description=metric.info.description,
     title=f"Metric: {metric.name}",
     article=parse_readme(local_path / "README.md"),
-    # TODO: load test cases and use them to populate examples
     examples=[
-        # correct depth?
-        parse_test_cases(test_cases, feature_names, gradio_input_types)
+        [pd.DataFrame(parse_test_cases(test_cases, feature_names, gradio_input_types)[0]), "weighted"],
     ],
     cache_examples=False
     )