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@arizeai/phoenix-mcp

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by Arize-ai
fetch_arize_documentation.py1.45 kB
""" Fetches the Arize documentation from Gitbook and serializes it into LangChain format. """ import json import logging import sys from typing import List from langchain.docstore.document import Document as LangChainDocument from langchain.document_loaders import GitbookLoader def load_gitbook_docs(docs_url: str) -> List[LangChainDocument]: """Loads documents from a Gitbook URL. Args: docs_url (str): URL to Gitbook docs. Returns: List[LangChainDocument]: List of documents in LangChain format. """ loader = GitbookLoader( docs_url, load_all_paths=True, ) return loader.load() if __name__ == "__main__": logging.basicConfig(level=logging.INFO, stream=sys.stdout) # fetch documentation docs_url = "https://docs.arize.com/arize/" embedding_model_name = "text-embedding-ada-002" documents = load_gitbook_docs(docs_url) # serialize documents and persist to file serialized_documents = [doc.json() for doc in documents] with open("arize_docs.json", "w") as f: json.dump(serialized_documents, f, indent=4) # read persisted data from file, deserialize, and check for equality with open("arize_docs.json") as f: serialized_documents = json.load(f) deserialized_documents = [ LangChainDocument.parse_raw(serialized_doc) for serialized_doc in serialized_documents ] assert documents == deserialized_documents

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