import gradio as gr from huggingface_hub import ModelCard from compliance_checks import ( ComplianceSuite, ComplianceCheck, IntendedPurposeCheck, GeneralLimitationsCheck, ComputationalRequirementsCheck, ) checks = [ IntendedPurposeCheck(), GeneralLimitationsCheck(), ComputationalRequirementsCheck(), ] suite = ComplianceSuite(checks=checks) def status_emoji(status: bool): return "✅" if status else "🛑" def run_compliance_check(model_card: str): results = suite.run(model_card) return [ *[gr.Accordion.update(label=f"{r.name} - {status_emoji(r.status)}", open=not r.status) for r in results], *[gr.Markdown.update(value=r.to_string()) for r in results], ] def fetch_and_run_compliance_check(model_id: str): model_card = ModelCard.load(repo_id_or_path=model_id).content return run_compliance_check(model_card=model_card) def compliance_result(compliance_check: ComplianceCheck): accordion = gr.Accordion(label=f"{compliance_check.name}", open=False) with accordion: description = gr.Markdown("Run an evaluation to see results...") return accordion, description def read_file(file_obj): with open(file_obj.name) as f: return f.read() model_card_box = gr.TextArea(label="Model Card") with gr.Blocks(css="""\ #reverse-row { flex-direction: row-reverse; } #file-upload .boundedheight { max-height: 100px; } code { overflow: scroll; } """) as demo: gr.Markdown("""\ # RegCheck AI This Space uses [model cards’](https://huggingface.co/docs/hub/model-cards) information as a source of regulatory \ compliance with some provisions of the proposed \ [EU AI Act](https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex%3A52021PC0206). For the moment being, the \ demo is a **prototype** limited to specific provisions of Article 13 of the AI Act, related to “Transparency and \ provision of information to users”. **(DISCLAIMER: this is NOT a commercial or legal advice-related product)** To check a model card, first load it by doing any one of the following: - If the model is on the Hugging Face Hub, enter its model ID and click "Load model card". - If you have the model card on your computer as a Markdown file, select the "Upload your own card" tab and click \ "Upload a Markdown file". - Paste your model card's text directly into the "Model Card" text area. Once your card is loaded, click "Run validation checks" to receive your results. """) with gr.Row(elem_id="reverse-row"): with gr.Column(): submit_markdown = gr.Button(value="Run validation checks") with gr.Tab(label="Results"): with gr.Column(): compliance_results = [compliance_result(c) for c in suite.checks] compliance_accordions = [c[0] for c in compliance_results] compliance_descriptions = [c[1] for c in compliance_results] with gr.Column(): with gr.Tab(label="Load a card from the 🤗 Hugging Face Hub"): model_id_search = gr.Text(label="Model ID") gr.Examples( examples=[ "bigscience/bloom", "roberta-base", "openai/clip-vit-base-patch32", "distilbert-base-cased-distilled-squad", ], fn=lambda x: ModelCard.load(repo_id_or_path=x).content, inputs=[model_id_search], outputs=[model_card_box] # cache_examples=True, # TODO: Why does this break the app? ) submit_model_search = gr.Button(value="Load model card") with gr.Tab(label="Upload your own card"): file = gr.UploadButton(label="Upload a Markdown file", elem_id="file-upload") file.upload( fn=read_file, inputs=[file], outputs=[model_card_box] ) model_card_box.render() submit_model_search.click( fn=lambda x: ModelCard.load(repo_id_or_path=x).content, inputs=[model_id_search], outputs=[model_card_box] ) submit_markdown.click( fn=run_compliance_check, inputs=[model_card_box], outputs=[*compliance_accordions, *compliance_descriptions] ) demo.launch()