import glob import json import os import re import subprocess from typing import List import requests import pandas as pd from bs4 import BeautifulSoup from markdown import markdown import nbformat from nbconvert import MarkdownExporter from nbconvert.preprocessors import Preprocessor, ClearOutputPreprocessor from tqdm import tqdm VALIDATE_URLS = False def download_repositories(repo_urls_file: str, repo_dir: str): """ Downloads the Hugging Face repositories. """ if not os.path.exists(repo_dir): os.makedirs(repo_dir) with open(repo_urls_file, "r") as f: repositories_urls = json.load(f)["urls"] print(f'Downloading {len(repositories_urls)} repositories') for url in repositories_urls: try: subprocess.run(["git", "clone", url], cwd=repo_dir) except subprocess.CalledProcessError as e: print("Command failed with error:", e.stderr) class EmptyCellPreprocessor(Preprocessor): def preprocess_cell(self, cell, resources, index): if cell.source.strip() == '': cell.source = '' cell.cell_type = 'raw' return cell, resources def convert_notebook_to_txt(filename: str): """ Converts a notebook to a markdown file. """ with open(filename) as f: notebook = nbformat.read(f, as_version=4) # id validation error fix for cell in notebook['cells']: cell['id'] = str(cell['id']) clear_output = ClearOutputPreprocessor() notebook, resources = clear_output.preprocess(notebook, {}) exporter = MarkdownExporter() exporter.register_preprocessor(EmptyCellPreprocessor, enabled=True) output_notebook_text, resources = exporter.from_notebook_node(notebook) new_filename = filename.replace('.ipynb', '_ipynb.md') with open(new_filename, 'w') as f: f.write(output_notebook_text) return new_filename def extract_files_from_directories( repo_urls_file: str, repo_dir: str, docs_dir: str, files_extensions: List[str] ) -> None: """ This function reads markdown and markdownx files from the repositories directory, filters out non-English files, and adds the source GitHub URL as the first line of each file. The resulting files are saved in the docs_dir. """ languages = pd.read_csv("language-codes.csv").loc[:,"alpha2"].tolist() languages.remove("en") files = [ filename for extension in files_extensions for filename in glob.glob(repo_dir + f"**/*{extension}", recursive=True) ] print(f'Used extensions: {", ".join(files_extensions)}') print(f'Found {len(files)} files') repo_urls = [] with open(repo_urls_file, "r") as f: repo_urls = json.load(f)["urls"] # filter out the files that are not in english filtered_files = [] for filename in files: sep_file = filename.split("/") for seq in sep_file: if seq in languages: break else: filtered_files.append(filename) print(f'Found {len(filtered_files)} files in English') # generate a GitHub URL for a file based on its name and a list of possible repository URLs def get_github_url(filename: str, repo_urls: str, repo_dir: str) -> str: source = filename.replace(repo_dir, '') repo_name, file_path = source.split('/', 1) repo_url_prefix = None for repo_url in repo_urls: if repo_name == repo_url.split('/')[-1]: repo_url_prefix = repo_url break if not repo_url_prefix: raise ValueError(f"Repo URL not found for {repo_name}") url = f'{repo_url_prefix}/blob/main/{file_path}' if VALIDATE_URLS: try: response = requests.get(url) response.raise_for_status() except: print(f'filename: {filename}') print(f'repo: {repo_name}, file: {file_path}') print(f'url: {url}') raise return url # creates a valid filename by replacing certain characters and removing the repo_dir path def create_filename_from_path(filename: str, repo_dir: str) -> str: filename = filename.replace(repo_dir, '') chars_to_replace = ['/', '{', '}', '-', '.'] filename = ''.join(['_' if c in chars_to_replace else c for c in filename]) return filename # copy the files with the source added in the first line if not os.path.exists(docs_dir): os.makedirs(docs_dir) copied_files = [] for filename in tqdm(filtered_files): source_url = get_github_url(filename, repo_urls, repo_dir) data = f"source: {source_url}\n\n" # convert jupyter notebooks to txt files try: if filename.endswith('.ipynb'): filename = convert_notebook_to_txt(filename) # rename and copy files with open(filename, 'r') as f: data += f.read() output_filename = docs_dir + create_filename_from_path(filename, repo_dir) with open(output_filename, 'w') as f: f.write(data) if not os.path.isfile(output_filename): raise ValueError(f"Failed to create the output file: {output_filename}") copied_files.append(output_filename) except Exception as ex: print(f'Failed to copy file {filename}: {ex}') print(f'Successfully copied {len(set(copied_files))}/{len(filtered_files)} files') def markdown_cleaner(data: str): """ Clean markdown text. Args: data (str): The markdown text to be cleaned. Returns: str: The cleaned markdown text. """ soupped = BeautifulSoup(markdown(data), "html.parser") raw_text = ''.join(soupped.findAll(string=True)) clean_text = re.sub(r"", "", raw_text, flags=re.DOTALL) # remove any special tokens e.g <|endoftext|> clean_text = re.sub(r"<\|endoftext\|>", "", clean_text, flags=re.DOTALL) # discard non english text clean_text = re.sub(r"[^a-zA-Z0-9\s]", "", clean_text, flags=re.DOTALL) return "\n".join([t for t in clean_text.split("\n") if t]) if __name__ == '__main__': repo_urls_file = "./datasets/hf_repositories_urls.json" repo_dir = "./datasets/huggingface_repositories/" docs_dir = "./datasets/huggingface_docs/" download_repositories(repo_urls_file, repo_dir) extract_files_from_directories( repo_urls_file, repo_dir, docs_dir, files_extensions=['.md', '.mdx', '.ipynb'] )