Update app.py

app.py

@@ -104,17 +104,21 @@ def launch_gradio_widget(metric):
         (feature_names, feature_types) = zip(*metric.features.items())
     gradio_input_types = infer_gradio_input_types(feature_types)
 
-    def compute(prediction, reference):
+    def compute(summary, article):
         data = {
-            "predictions": [prediction], 
-            "references":[reference]
+            "summaries": [summary], 
+            "articles":[article]
         }
         return metric.compute(**data)
         # return metric.compute(**parse_gradio_data(data, gradio_input_types))
 
     iface = gr.Interface(
         fn=compute, 
-        inputs=["text", "text"], 
+        # inputs=["text", "text"], 
+        inputs=[
+            gr.components.Textbox(label="Summary"), 
+            gr.components.Textbox(label="Article")
+        ]
         # inputs=gr.components.Dataframe(
         #     headers=feature_names,
         #     col_count=len(feature_names),
@@ -122,10 +126,7 @@ def launch_gradio_widget(metric):
         #     datatype=json_to_string_type(gradio_input_types),
         # ),
         outputs=gr.components.Textbox(label=metric.name),
-        description=(
-            metric.info.description + "\nIf this is a text-based metric, make sure to wrap you input in double quotes."
-            " Alternatively you can use a JSON-formatted list as input."
-        ),
+        description="", 
         title=f"Metric: {metric.name}",
         article=parse_readme(local_path / "README.md"),
         # TODO: load test cases and use them to populate examples