import evaluate from evaluate.utils import launch_gradio_widget from pathlib import Path import sys import os from .logging import get_logger logger = get_logger(__name__) ### def launch_gradio_widget(metric): """Launches `metric` widget with Gradio.""" try: import gradio as gr except ImportError as error: logger.error("To create a metric widget with Gradio make sure gradio is installed.") raise error local_path = Path(sys.path[0]) # if there are several input types, use first as default. if isinstance(metric.features, list): (feature_names, feature_types) = zip(*metric.features[0].items()) else: (feature_names, feature_types) = zip(*metric.features.items()) gradio_input_types = infer_gradio_input_types(feature_types) def compute(data): return metric.compute(**parse_gradio_data(data, gradio_input_types)) iface = gr.Interface( fn=compute, inputs=gr.Dataframe( headers=feature_names, col_count=len(feature_names), row_count=1, datatype=json_to_string_type(gradio_input_types), ), outputs=gr.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." ), title=f"Metric: {metric.name}", article=parse_readme(local_path / "README.md"), # TODO: load test cases and use them to populate examples # examples=[parse_test_cases(test_cases, feature_names, gradio_input_types)] ) iface.launch() ### module = evaluate.load("saicharan2804/my_metric") launch_gradio_widget(module)