text: encrypted, cloud-based and centralized instant messaging service. The application also provides optional end-to-end encrypted chats and video calling, VoIP, file sharing and several other features.This notebook covers how to load data from Telegram into a format that can be ingested into LangChain.from langchain.document_loaders import TelegramChatFileLoader, TelegramChatApiLoaderloader = TelegramChatFileLoader("example_data/telegram.json")loader.load()    [Document(page_content="Henry on 2020-01-01T00:00:02: It's 2020...\n\nHenry on 2020-01-01T00:00:04: Fireworks!\n\nGrace Ã°Å¸Â§Â¤ Ã°Å¸\x8dâ€™ on 2020-01-01T00:00:05: You're a minute late!\n\n", metadata={'source': 'example_data/telegram.json'})]TelegramChatApiLoader loads data directly from any specified chat from Telegram. In order to export the data, you will need to authenticate your Telegram account. You can get the API_HASH and API_ID from https://my.telegram.org/auth?to=appschat_entity â€“ recommended to be the entity of a channel.loader = TelegramChatApiLoader(    chat_entity="<CHAT_URL>",  # recommended to use Entity here    api_hash="<API HASH >",    api_id="<API_ID>",    user_name="",  # needed only for caching the session.)loader.load()PreviousSubtitleNextTencent COS DirectoryCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright Â© 2023 LangChain, Inc.