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import gradio as gr |
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from huggingface_hub import ModelCard |
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from compliance_checks import ( |
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ComplianceSuite, |
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ComplianceCheck, |
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IntendedPurposeCheck, |
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GeneralLimitationsCheck, |
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ComputationalRequirementsCheck, |
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) |
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from bloom_card import bloom_card |
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checks = [ |
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IntendedPurposeCheck(), |
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GeneralLimitationsCheck(), |
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ComputationalRequirementsCheck(), |
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] |
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suite = ComplianceSuite(checks=checks) |
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def status_emoji(status: bool): |
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return "✅" if status else "🛑" |
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def run_compliance_check(model_card: str): |
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results = suite.run(model_card) |
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return [ |
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*[gr.Accordion.update(label=f"{r.name} - {status_emoji(r.status)}") for r in results], |
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*[gr.Markdown.update(value=r.to_string()) for r in results], |
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] |
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def fetch_and_run_compliance_check(model_id: str): |
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model_card = ModelCard.load(repo_id_or_path=model_id).content |
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return run_compliance_check(model_card=model_card) |
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def compliance_result(compliance_check: ComplianceCheck): |
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accordion = gr.Accordion(label=f"{compliance_check.name}", open=False) |
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with accordion: |
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description = gr.Markdown("Run an evaluation to see results...") |
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return accordion, description |
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def read_file(file_obj): |
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with open(file_obj.name) as f: |
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return f.read() |
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model_card_box = gr.TextArea(label="Model Card") |
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with gr.Blocks(css="#reverse-row { flex-direction: row-reverse;} #file-upload .boundedheight {max-height: 100px;}") as demo: |
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gr.Markdown("""\ |
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# RegCheck AI |
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This Space uses 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”. Choose a model card and check whether it has some useful info to comply with the EU AI Act! **(DISCLAIMER: this is NOT a commercial or legal advice-related product)** |
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""") |
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with gr.Row(elem_id="reverse-row"): |
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with gr.Column(): |
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submit_markdown = gr.Button(value="Run validation checks") |
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with gr.Tab(label="Results"): |
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with gr.Column(): |
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compliance_results = [compliance_result(c) for c in suite.checks] |
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compliance_accordions = [c[0] for c in compliance_results] |
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compliance_descriptions = [c[1] for c in compliance_results] |
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with gr.Column(): |
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with gr.Tab(label="Load a card from the 🤗 Hugging Face Hub"): |
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model_id_search = gr.Text(label="Model ID") |
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gr.Examples( |
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examples=[ |
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"society-ethics/model-card-webhook-test", |
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"bigscience/bloom", |
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"roberta-base", |
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"openai/clip-vit-base-patch32", |
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"distilbert-base-cased-distilled-squad", |
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], |
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fn=lambda x: ModelCard.load(repo_id_or_path=x).content, |
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inputs=[model_id_search], |
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outputs=[model_card_box] |
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) |
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submit_model_search = gr.Button(value="Load model card") |
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with gr.Tab(label="Upload your own card"): |
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file = gr.UploadButton(label="Upload a Markdown file", elem_id="file-upload") |
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file.upload( |
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fn=read_file, |
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inputs=[file], |
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outputs=[model_card_box] |
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) |
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model_card_box.render() |
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submit_model_search.click( |
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fn=lambda x: ModelCard.load(repo_id_or_path=x).content, |
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inputs=[model_id_search], |
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outputs=[model_card_box] |
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) |
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submit_markdown.click( |
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fn=run_compliance_check, |
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inputs=[model_card_box], |
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outputs=[*compliance_accordions, *compliance_descriptions] |
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) |
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demo.launch() |
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