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# `langchain_community.document_loaders.chatgpt`.ChatGPTLoader

class langchain_community.document_loaders.chatgpt.ChatGPTLoader(log_file: str, num_logs: int = -1)

  Load conversations from exported ChatGPT data.

  Initialize a class object.

  Parameters

    - log_file (str) – Path to the log file

    - num_logs (int) – Number of logs to load. If 0, load all logs.

  Methods

  `__init__`(log_file[, num_logs]) | Initialize a class object.
  `alazy_load`() | A lazy loader for Documents.
  `aload`() | Load data into Document objects.
  `lazy_load`() | A lazy loader for Documents.
  `load`() | Load data into Document objects.
  `load_and_split`([text_splitter]) | Load Documents and split into chunks.

  __init__(log_file: str, num_logs: int = -1)

    Initialize a class object.

    Parameters

      - log_file (str) – Path to the log file

      - num_logs (int) – Number of logs to load. If 0, load all logs.

  async alazy_load() → AsyncIterator[Document]

    A lazy loader for Documents.

    Return type

      AsyncIterator[Document]

  async aload() → List[Document]

    Load data into Document objects.

    Return type

      List[Document]

  lazy_load() → Iterator[Document]

    A lazy loader for Documents.

    Return type

      Iterator[Document]

  load() → List[Document]

    Load data into Document objects.

    Return type

      List[Document]

  load_and_split(text_splitter: Optional[TextSplitter] = None) → List[Document]

    Load Documents and split into chunks. Chunks are returned as Documents.

    Do not override this method. It should be considered to be deprecated!

    Parameters

      text_splitter (Optional[TextSplitter]) – TextSplitter instance to use for splitting documents. Defaults to RecursiveCharacterTextSplitter.

    Returns

      List of Documents.

    Return type

      List[Document]

# Examples using ChatGPTLoader

- OpenAI

- chatgpt_loader.md