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from __future__ import annotations |
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import shutil |
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import tempfile |
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import gradio as gr |
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from huggingface_hub import HfApi |
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title = 'Model Demo Creation' |
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description = 'This is a Space that creates demo apps for models in Model Hub.' |
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article = '' |
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examples = [ |
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[ |
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'', |
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'google/vit-base-patch16-224', |
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'', |
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'Demo for google/vit-base-patch16-224', |
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'', |
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'', |
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], |
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[ |
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'', |
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'google/vit-base-patch16-224, microsoft/resnet-50', |
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'', |
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'Compare Image Classification Models', |
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'', |
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'', |
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], |
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[ |
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'', |
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'EleutherAI/gpt-j-6B, EleutherAI/gpt-neo-1.3B', |
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'', |
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'Compare Text Generation Models', |
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'', |
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'', |
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], |
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] |
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api = HfApi() |
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def check_if_model_exists(model_name: str) -> bool: |
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return any(info.modelId == model_name |
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for info in api.list_models(search=model_name)) |
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def list_missing_models(model_names: list[str]) -> list[str]: |
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missing_models = [] |
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for model_name in model_names: |
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if not check_if_model_exists(model_name): |
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missing_models.append(model_name) |
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return missing_models |
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def save_space_info(dirname: str, filename: str, content: str) -> None: |
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with open(f'{dirname}/{filename}', 'w') as f: |
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f.write(content) |
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def run(space_name: str, model_names_str: str, hf_token: str, title: str, |
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description: str, article: str) -> str: |
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model_names = [name.strip() for name in model_names_str.split(',')] |
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model_names_str = '\n'.join(model_names) |
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if len(model_names) == 0: |
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return 'Model Name cannot be empty.' |
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missing_models = list_missing_models(model_names) |
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if len(missing_models) > 0: |
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message = 'The following model were not found: ' |
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for model_name in missing_models: |
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message += f'\n{model_name}' |
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return message |
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try: |
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space_url = api.create_repo(repo_id=space_name, |
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repo_type='space', |
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private=True, |
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token=hf_token, |
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space_sdk='gradio') |
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except Exception as e: |
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return str(e) |
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with tempfile.TemporaryDirectory() as temp_dir: |
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shutil.copy('assets/template.py', f'{temp_dir}/app.py') |
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save_space_info(temp_dir, 'TITLE', title) |
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save_space_info(temp_dir, 'DESCRIPTION', description) |
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save_space_info(temp_dir, 'ARTICLE', article) |
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save_space_info(temp_dir, 'MODEL_NAMES', model_names_str) |
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api.upload_folder(repo_id=space_name, |
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folder_path=temp_dir, |
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path_in_repo='.', |
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token=hf_token, |
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repo_type='space') |
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return f'Successfully created: {space_url}' |
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gr.Interface( |
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fn=run, |
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inputs=[ |
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gr.Textbox(label='Space Name', placeholder='<user_name>/<space_name>'), |
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gr.Textbox(label='Model Names', |
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placeholder='e.g. microsoft/resnet-50'), |
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gr.Textbox( |
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label='Hugging Face Token', |
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placeholder= |
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'This should be a token with write permission. See: https://huggingface.co/settings/tokens' |
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), |
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gr.Textbox(label='Title (Optional)'), |
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gr.Textbox(label='Description (Optional)'), |
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gr.Textbox(label='Article (Optional)'), |
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], |
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outputs=gr.Textbox(label='Output'), |
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title=title, |
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description=description, |
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article=article, |
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examples=examples, |
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cache_examples=False, |
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).launch(enable_queue=True, share=False) |
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