add temporary demo to test formatting

app.py

@@ -23,28 +23,46 @@ Try to use \t to write some code? \t or how does that work? </p>
 article = "<p style='text-align: center'> Check out the [original repo](https://github.com/johngrahamreynolds/FixedMetricsForHF) housing this code, and a quickly \
 trained [multilabel text classification model](https://github.com/johngrahamreynolds/RoBERTa-base-DReiFT/tree/main) that makes use of it during evaluation.</p>"
 
-def show_off(predictions: list[list]) -> str: 
+# def show_off(predictions: list[list]) -> str: 
 
-    # f1 = FixedF1(average=weighting_map["f1"])
-    # precision = FixedPrecision(average=weighting_map["precision"])
-    # recall = FixedRecall(average=weighting_map["recall"])
+#     # f1 = FixedF1(average=weighting_map["f1"])
+#     # precision = FixedPrecision(average=weighting_map["precision"])
+#     # recall = FixedRecall(average=weighting_map["recall"])
 
-    # combined = evaluate.combine([f1, recall, precision])
+#     # combined = evaluate.combine([f1, recall, precision])
 
-    # combined.add_batch(prediction=predictions, reference=references)
-    # outputs =  combined.compute()
-    outputs = predictions
+#     # combined.add_batch(prediction=predictions, reference=references)
+#     # outputs =  combined.compute()
+#     outputs = predictions
 
-    return "Your metrics are as follows: \n" + outputs
+#     return "Your metrics are as follows: \n" + outputs
 
 
-gr.Interface(
-    fn=show_off,
-    inputs=gr.Dataframe(type="array", datatype="number", row_count=5, col_count=1),
-    outputs="text",
-    title=title,
-    description=description,
-    article=article,
-    examples=[[1, 0, 2, 0, 1]],
-    cache_examples=False
+# gr.Interface(
+#     fn=show_off,
+#     inputs=gr.Dataframe(type="array", datatype="number", row_count=5, col_count=1),
+#     outputs="text",
+#     title=title,
+#     description=description,
+#     article=article,
+#     examples=[pd.DataFrame([1, 0, 2, 0, 1])],
+#     cache_examples=False
+# ).launch()
+
+def filter_records(records, gender):
+    return records[records["gender"] == gender]
+
+demo = gr.Interface(
+    filter_records,
+    [
+        gr.Dataframe(
+            headers=["name", "age", "gender"],
+            datatype=["str", "number", "str"],
+            row_count=5,
+            col_count=(3, "fixed"),
+        ),
+        gr.Dropdown(["M", "F", "O"]),
+    ],
+    "dataframe",
+    description="Enter gender as 'M', 'F', or 'O' for other.",
 ).launch()