Load module helps with serialization and deserialization.
Import an attribute from a module located in a package.
This utility function is used in custom __getattr__ methods within __init__.py
files to dynamically import attributes.
Return a dict representation of an object.
Return a JSON string representation of an object.
Revive a LangChain class from a JSON string.
Equivalent to load(json.loads(text)).
Only classes in the allowlist can be instantiated. The default allowlist includes
core LangChain types (messages, prompts, documents, etc.). See
langchain_core.load.mapping for the full list.
This function instantiates Python objects and can trigger side effects
during deserialization. Never call loads() on data from an untrusted
or unauthenticated source. See the module-level security model
documentation for details and best practices.
Serializable base class.
This class is used to serialize objects to JSON.
It relies on the following methods and properties:
is_lc_serializable: Is this class serializable?
By design, even if a class inherits from Serializable, it is not serializable
by default. This is to prevent accidental serialization of objects that should
not be serialized.
get_lc_namespace: Get the namespace of the LangChain object.
During deserialization, this namespace is used to identify the correct class to instantiate.
Please see the Reviver class in langchain_core.load.load for more details.
During deserialization an additional mapping is handle classes that have moved or been renamed across package versions.
lc_secrets: A map of constructor argument names to secret ids.
lc_attributes: List of additional attribute names that should be included
as part of the serialized representation.
Load LangChain objects from JSON strings or objects.
Each Serializable LangChain object has a unique identifier (its "class path"), which
is a list of strings representing the module path and class name. For example:
AIMessage -> ["langchain_core", "messages", "ai", "AIMessage"]ChatPromptTemplate -> ["langchain_core", "prompts", "chat", "ChatPromptTemplate"]When deserializing, the class path from the JSON 'id' field is checked against an
allowlist. If the class is not in the allowlist, deserialization raises a ValueError.
These functions deserialize by instantiating Python objects, which means
constructors (__init__) and validators may run and can trigger side effects.
With the default settings, deserialization is restricted to a core allowlist
of langchain_core types (for example: messages, documents, and prompts)
defined in langchain_core.load.mapping.
If you broaden allowed_objects (for example, by using 'all' or adding
additional classes), treat the serialized payload as a manifest and only
deserialize data that comes from a trusted source. A crafted payload that
is allowed to instantiate unintended classes could cause network calls,
file operations, or environment variable access during __init__.
The allowed_objects parameter controls which classes can be deserialized:
'core' (default): Allow classes defined in the serialization mappings for
langchain_core.'all': Allow classes defined in the serialization mappings. This
includes core LangChain types (messages, prompts, documents, etc.) and trusted
partner integrations. See langchain_core.load.mapping for the full list.For simple data types like messages and documents, the default allowlist is safe to use. These classes do not perform side effects during initialization.
Deserialization calls __init__ on allowed classes. If those classes perform side
effects during initialization (network calls, file operations, etc.), those side
effects will occur. The allowlist prevents instantiation of classes outside the
allowlist, but does not sandbox the allowed classes themselves.
Import paths are also validated against trusted namespaces before any module is imported.
allowed_objects possible. Prefer an explicit list
of classes over 'core' or 'all'.secrets_from_env set to False (the default). If you must use it,
ensure the serialized data comes from a fully trusted source, as a crafted
payload can read arbitrary environment variables.secrets_map, include only the specific secrets that the
serialized object requires.During serialization, plain dicts that contain an 'lc' key are escaped by wrapping
them: {"__lc_escaped__": {...}}. During deserialization, escaped dicts are unwrapped
and returned as plain dicts, NOT instantiated as LC objects.
This is an allowlist approach: only dicts explicitly produced by
Serializable.to_json() (which are NOT escaped) are treated as LC objects;
everything else is user data.
Even if an attacker's payload includes __lc_escaped__ wrappers, it will be unwrapped
to plain dicts and NOT instantiated as malicious objects.
from langchain_core.load import load
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.messages import AIMessage, HumanMessage
# Use default allowlist (classes from mappings) - recommended
obj = load(data)
# Allow only specific classes (most restrictive)
obj = load(
data,
allowed_objects=[
ChatPromptTemplate,
AIMessage,
HumanMessage,
],
)Serialization mapping.
This file contains a mapping between the lc_namespace path for a given
subclass that implements from Serializable to the namespace
where that class is actually located.
This mapping helps maintain the ability to serialize and deserialize well-known LangChain objects even if they are moved around in the codebase across different LangChain versions.
For example, the code for the AIMessage class is located in
langchain_core.messages.ai.AIMessage. This message is associated with the
lc_namespace of ["langchain", "schema", "messages", "AIMessage"],
because this code was originally in langchain.schema.messages.AIMessage.
The mapping allows us to deserialize an AIMessage created with an older
version of LangChain where the code was in a different location.
Serialize LangChain objects to JSON.
Provides dumps (to JSON string) and dumpd (to dict) for serializing
Serializable objects.
During serialization, plain dicts (user data) that contain an 'lc' key are escaped
by wrapping them: {"__lc_escaped__": {...original...}}. This prevents injection
attacks where malicious data could trick the deserializer into instantiating
arbitrary classes. The escape marker is removed during deserialization.
This is an allowlist approach: only dicts explicitly produced by
Serializable.to_json() are treated as LC objects; everything else is escaped if it
could be confused with the LC format.
Serializable base class.