base.py — langchain Source File

Source Code

"""Base classes for media and documents.

This module contains core abstractions for **data retrieval and processing workflows**:

- `BaseMedia`: Base class providing `id` and `metadata` fields
- `Blob`: Raw data loading (files, binary data) - used by document loaders
- `Document`: Text content for retrieval (RAG, vector stores, semantic search)

!!! note "Not for LLM chat messages"

    These classes are for data processing pipelines, not LLM I/O. For multimodal
    content in chat messages (images, audio in conversations), see
    `langchain.messages` content blocks instead.
"""

from __future__ import annotations

import contextlib
import mimetypes
from io import BufferedReader, BytesIO
from pathlib import Path, PurePath
from typing import TYPE_CHECKING, Any, Literal, cast

from pydantic import ConfigDict, Field, model_validator

from langchain_core.load.serializable import Serializable

if TYPE_CHECKING:
    from collections.abc import Generator

PathLike = str | PurePath


class BaseMedia(Serializable):
    """Base class for content used in retrieval and data processing workflows.

    Provides common fields for content that needs to be stored, indexed, or searched.

    !!! note

        For multimodal content in **chat messages** (images, audio sent to/from LLMs),
        use `langchain.messages` content blocks instead.
    """

    # The ID field is optional at the moment.
    # It will likely become required in a future major release after
    # it has been adopted by enough VectorStore implementations.
    id: str | None = Field(default=None, coerce_numbers_to_str=True)
    """An optional identifier for the document.

    Ideally this should be unique across the document collection and formatted
    as a UUID, but this will not be enforced.
    """

    metadata: dict = Field(default_factory=dict)
    """Arbitrary metadata associated with the content."""


class Blob(BaseMedia):
    """Raw data abstraction for document loading and file processing.
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