Source code for langchain_core.globals

# flake8: noqa
"""Global values and configuration that apply to all of LangChain."""

import warnings
from typing import TYPE_CHECKING, Optional

if TYPE_CHECKING:
    from langchain_core.caches import BaseCache


# DO NOT USE THESE VALUES DIRECTLY!
# Use them only via `get_<X>()` and `set_<X>()` below,
# or else your code may behave unexpectedly with other uses of these global settings:
# https://github.com/langchain-ai/langchain/pull/11311#issuecomment-1743780004
_verbose: bool = False
_debug: bool = False
_llm_cache: Optional["BaseCache"] = None


[docs]def set_verbose(value: bool) -> None:
    """Set a new value for the `verbose` global setting.

    Args:
        value: The new value for the `verbose` global setting.
    """
    try:
        import langchain  # type: ignore[import]

        # We're about to run some deprecated code, don't report warnings from it.
        # The user called the correct (non-deprecated) code path and shouldn't get warnings.
        with warnings.catch_warnings():
            warnings.filterwarnings(
                "ignore",
                message=(
                    "Importing verbose from langchain root module is no longer supported"
                ),
            )
            # N.B.: This is a workaround for an unfortunate quirk of Python's
            #       module-level `__getattr__()` implementation:
            # https://github.com/langchain-ai/langchain/pull/11311#issuecomment-1743780004
            #
            # Remove it once `langchain.verbose` is no longer supported, and once all users
            # have migrated to using `set_verbose()` here.
            langchain.verbose = value
    except ImportError:
        pass

    global _verbose
    _verbose = value


[docs]def get_verbose() -> bool:
    """Get the value of the `verbose` global setting.

    Returns:
        The value of the `verbose` global setting.
    """
    try:
        import langchain  # type: ignore[import]

        # We're about to run some deprecated code, don't report warnings from it.
        # The user called the correct (non-deprecated) code path and shouldn't get warnings.
        with warnings.catch_warnings():
            warnings.filterwarnings(
                "ignore",
                message=(
                    ".*Importing verbose from langchain root module is no longer supported"
                ),
            )
            # N.B.: This is a workaround for an unfortunate quirk of Python's
            #       module-level `__getattr__()` implementation:
            # https://github.com/langchain-ai/langchain/pull/11311#issuecomment-1743780004
            #
            # Remove it once `langchain.verbose` is no longer supported, and once all users
            # have migrated to using `set_verbose()` here.
            #
            # In the meantime, the `verbose` setting is considered True if either the old
            # or the new value are True. This accommodates users who haven't migrated
            # to using `set_verbose()` yet. Those users are getting deprecation warnings
            # directing them to use `set_verbose()` when they import `langchain.verbose`.
            old_verbose = langchain.verbose
    except ImportError:
        old_verbose = False

    global _verbose
    return _verbose or old_verbose


[docs]def set_debug(value: bool) -> None:
    """Set a new value for the `debug` global setting.

    Args:
        value: The new value for the `debug` global setting.
    """
    try:
        import langchain  # type: ignore[import]

        # We're about to run some deprecated code, don't report warnings from it.
        # The user called the correct (non-deprecated) code path and shouldn't get warnings.
        with warnings.catch_warnings():
            warnings.filterwarnings(
                "ignore",
                message="Importing debug from langchain root module is no longer supported",
            )
            # N.B.: This is a workaround for an unfortunate quirk of Python's
            #       module-level `__getattr__()` implementation:
            # https://github.com/langchain-ai/langchain/pull/11311#issuecomment-1743780004
            #
            # Remove it once `langchain.debug` is no longer supported, and once all users
            # have migrated to using `set_debug()` here.
            langchain.debug = value
    except ImportError:
        pass

    global _debug
    _debug = value


[docs]def get_debug() -> bool:
    """Get the value of the `debug` global setting.

    Returns:
        The value of the `debug` global setting.
    """
    try:
        import langchain  # type: ignore[import]

        # We're about to run some deprecated code, don't report warnings from it.
        # The user called the correct (non-deprecated) code path and shouldn't get warnings.
        with warnings.catch_warnings():
            warnings.filterwarnings(
                "ignore",
                message="Importing debug from langchain root module is no longer supported",
            )
            # N.B.: This is a workaround for an unfortunate quirk of Python's
            #       module-level `__getattr__()` implementation:
            # https://github.com/langchain-ai/langchain/pull/11311#issuecomment-1743780004
            #
            # Remove it once `langchain.debug` is no longer supported, and once all users
            # have migrated to using `set_debug()` here.
            #
            # In the meantime, the `debug` setting is considered True if either the old
            # or the new value are True. This accommodates users who haven't migrated
            # to using `set_debug()` yet. Those users are getting deprecation warnings
            # directing them to use `set_debug()` when they import `langchain.debug`.
            old_debug = langchain.debug
    except ImportError:
        old_debug = False

    global _debug
    return _debug or old_debug


[docs]def set_llm_cache(value: Optional["BaseCache"]) -> None:
    """Set a new LLM cache, overwriting the previous value, if any.

    Args:
        value: The new LLM cache to use. If `None`, the LLM cache is disabled.
    """
    try:
        import langchain  # type: ignore[import]

        # We're about to run some deprecated code, don't report warnings from it.
        # The user called the correct (non-deprecated) code path and shouldn't get warnings.
        with warnings.catch_warnings():
            warnings.filterwarnings(
                "ignore",
                message=(
                    "Importing llm_cache from langchain root module is no longer supported"
                ),
            )
            # N.B.: This is a workaround for an unfortunate quirk of Python's
            #       module-level `__getattr__()` implementation:
            # https://github.com/langchain-ai/langchain/pull/11311#issuecomment-1743780004
            #
            # Remove it once `langchain.llm_cache` is no longer supported, and
            # once all users have migrated to using `set_llm_cache()` here.
            langchain.llm_cache = value
    except ImportError:
        pass

    global _llm_cache
    _llm_cache = value


[docs]def get_llm_cache() -> "BaseCache":
    """Get the value of the `llm_cache` global setting.

    Returns:
        The value of the `llm_cache` global setting.
    """
    try:
        import langchain  # type: ignore[import]

        # We're about to run some deprecated code, don't report warnings from it.
        # The user called the correct (non-deprecated) code path and shouldn't get warnings.
        with warnings.catch_warnings():
            warnings.filterwarnings(
                "ignore",
                message=(
                    "Importing llm_cache from langchain root module is no longer supported"
                ),
            )
            # N.B.: This is a workaround for an unfortunate quirk of Python's
            #       module-level `__getattr__()` implementation:
            # https://github.com/langchain-ai/langchain/pull/11311#issuecomment-1743780004
            #
            # Remove it once `langchain.llm_cache` is no longer supported, and
            # once all users have migrated to using `set_llm_cache()` here.
            #
            # In the meantime, the `llm_cache` setting returns whichever of
            # its two backing sources is truthy (not `None` and non-empty),
            # or the old value if both are falsy. This accommodates users
            # who haven't migrated to using `set_llm_cache()` yet.
            # Those users are getting deprecation warnings directing them
            # to use `set_llm_cache()` when they import `langchain.llm_cache`.
            old_llm_cache = langchain.llm_cache
    except ImportError:
        old_llm_cache = None

    global _llm_cache
    return _llm_cache or old_llm_cache