| # import re | |
| # import requests | |
| # import gradio as gr | |
| # from markdownify import markdownify | |
| # from requests.exceptions import RequestException | |
| # from utils.preprocessor import Preprocessor | |
| # # https://modal.com/docs/guide/webhook-urls | |
| # MODAL_ENDPOINT = "https://auto-readme-agent--text-to-speech-gradio-app.modal.run" | |
| # def visit_webpage(url, max_output_length=40000): | |
| # """ | |
| # Fetch the webpage, convert to markdown, and use Preprocessor methods. | |
| # """ | |
| # try: | |
| # response = requests.get(url, timeout=20) | |
| # response.raise_for_status() | |
| # markdown_content = markdownify(response.text).strip() | |
| # markdown_content = re.sub(r"\n{3,}", "\n\n", markdown_content) | |
| # # if len(markdown_content) > max_output_length: | |
| # # markdown_content = ( | |
| # # markdown_content[: max_output_length // 2] | |
| # # + f"\n..._This content has been truncated to stay below {max_output_length} characters_...\n" | |
| # # + markdown_content[-max_output_length // 2 :] | |
| # # ) | |
| # # Use Preprocessor class methods | |
| # section = Preprocessor.extract_section(markdown_content) | |
| # dir_paths, files = Preprocessor.extract_dirs_from_text(section) | |
| # # Format the result | |
| # result = ( | |
| # f"paths: {dir_paths}\n\n" | |
| # f"files: {files}" | |
| # ) | |
| # return result | |
| # except requests.exceptions.Timeout: | |
| # return "The request timed out. Please try again later or check the URL." | |
| # except RequestException as e: | |
| # return f"Error fetching the webpage: {str(e)}" | |
| # except Exception as e: | |
| # return f"An unexpected error occurred: {str(e)}" | |
| # demo = gr.Interface( | |
| # fn=visit_webpage, | |
| # inputs=[ | |
| # gr.Textbox(label="Website URL"), | |
| # gr.Textbox(label="Files or folders you want to highlight in the README (comma or newline separated)") | |
| # ], | |
| # outputs=gr.Textbox(label="Extracted Section, Directory Paths, and File Paths", show_copy_button=True), | |
| # title="Webpage Section and Path Extractor", | |
| # description="Enter a website URL. This tool fetches the page, extracts a markdown section, and lists directory paths and files found in that section. You can also specify files or folders you want to highlight in the generated README." | |
| # ) | |
| # if __name__ == "__main__": | |
| # demo.launch(debug=True) | |
| import gradio as gr | |
| import requests | |
| MODAL_API_URL = "https://agents-mcp-hackathon--smolagents-modal-agent-readme-agen-eb6ccb.modal.run" # Replace with your deployed Modal endpoint | |
| def generate_readme_from_github(repo_url): | |
| try: | |
| response = requests.post( | |
| MODAL_API_URL, | |
| json={"repo_url": repo_url}, | |
| timeout=600, | |
| ) | |
| if response.status_code == 200: | |
| return response.json().get("readme", "No README generated.") | |
| else: | |
| return f"Error: {response.status_code}\n{response.text}" | |
| except Exception as e: | |
| return f"Exception: {str(e)}" | |
| with gr.Blocks() as demo: | |
| gr.Markdown("# 📝 GitHub Repo → README.md Generator\nPaste a public GitHub repo link to generate a draft README.md using AI.") | |
| repo_input = gr.Textbox(label="GitHub Repository URL", placeholder="https://github.com/owner/repo") | |
| output = gr.Textbox(label="Generated README.md", lines=20) | |
| btn = gr.Button("Generate README") | |
| btn.click(generate_readme_from_github, inputs=repo_input, outputs=output) | |
| if __name__ == "__main__": | |
| demo.launch() |