import os import requests import zipfile import io import gradio as gr def get_file_summary(file_info): return { "name": file_info.filename, "type": "binary" if file_info.file_size > 1024 * 1024 else "text", "size": file_info.file_size, } def extract_repo_content(url): if "huggingface.co" not in url: return "Invalid URL. Please provide a valid Hugging Face URL." repo_name = url.split('/')[-2] repo_type = url.split('/')[-3] api_url = f"https://huggingface.co/api/{repo_type}/{repo_name}/tree/main" response = requests.get(api_url) if response.status_code != 200: return f"Failed to fetch repository content. Status code: {response.status_code}" repo_content = response.json() extracted_content = [] headers = [] for file_info in repo_content: file_summary = get_file_summary(file_info) headers.append(file_summary) if file_summary["type"] == "text" and file_summary["size"] <= 1024 * 1024: file_url = f"https://huggingface.co/{repo_type}/{repo_name}/resolve/main/{file_info['filename']}" file_response = requests.get(file_url) if file_response.status_code == 200: file_content = file_response.text extracted_content.append({"header": file_summary, "content": file_content}) else: extracted_content.append({"header": file_summary, "content": "Failed to fetch file content."}) else: extracted_content.append({"header": file_summary, "content": "File too large or binary, content not captured."}) return extracted_content def format_output(extracted_content): formatted_output = "" for file_data in extracted_content: formatted_output += f"### File: {file_data['header']['name']}\n" formatted_output += f"**Type:** {file_data['header']['type']}\n" formatted_output += f"**Size:** {file_data['header']['size']} bytes\n" formatted_output += "#### Content:\n" formatted_output += f"```\n{file_data['content']}\n```\n\n" return formatted_output def extract_and_display(url): extracted_content = extract_repo_content(url) formatted_output = format_output(extracted_content) return formatted_output app = gr.Blocks() with app: gr.Markdown("# Gradio Space/Model Content Extractor") url_input = gr.Textbox(label="Hugging Face Space/Model URL") output_display = gr.Markdown() extract_button = gr.Button("Extract Content") extract_button.click(fn=extract_and_display, inputs=url_input, outputs=output_display) app.launch()