LangChain v0.3
Last updated: 09.16.24
What's changed
- All packages have been upgraded from Pydantic 1 to Pydantic 2 internally. Use of Pydantic 2 in user code is fully supported with all packages without the need for bridges like
langchain_core.pydantic_v1
orpydantic.v1
. - Pydantic 1 will no longer be supported as it reached its end-of-life in June 2024.
- Python 3.8 will no longer be supported as its end-of-life is October 2024.
These are the only breaking changes.
What’s new
The following features have been added during the development of 0.2.x:
- Moved more integrations from
langchain-community
to their ownlangchain-x
packages. This is a non-breaking change, as the legacy implementations are left inlangchain-community
and marked as deprecated. This allows us to better manage the dependencies of, test, and version these integrations. You can see all the latest integration packages in the API reference. - Simplified tool definition and usage. Read more here.
- Added utilities for interacting with chat models: universal model constructor, rate limiter, message utilities,
- Added the ability to dispatch custom events.
- Revamped integration docs and API reference. Read more here.
- Marked as deprecated a number of legacy chains and added migration guides for all of them. These are slated for removal in
langchain
1.0.0. See the deprecated chains and associated migration guides here.
How to update your code
If you're using langchain
/ langchain-community
/ langchain-core
0.0 or 0.1, we recommend that you first upgrade to 0.2.
If you're using langgraph
, upgrade to langgraph>=0.2.20,<0.3
. This will work with either 0.2 or 0.3 versions of all the base packages.
Here is a complete list of all packages that have been released and what we recommend upgrading your version constraints to.
Any package that now requires langchain-core
0.3 had a minor version bump.
Any package that is now compatible with both langchain-core
0.2 and 0.3 had a patch version bump.
You can use the langchain-cli
to update deprecated imports automatically.
The CLI will handle updating deprecated imports that were introduced in LangChain 0.0.x and LangChain 0.1, as
well as updating the langchain_core.pydantic_v1
and langchain.pydantic_v1
imports.
Base packages
Package | Latest | Recommended constraint |
---|---|---|
langchain | 0.3.0 | >=0.3,<0.4 |
langchain-community | 0.3.0 | >=0.3,<0.4 |
langchain-text-splitters | 0.3.0 | >=0.3,<0.4 |
langchain-core | 0.3.0 | >=0.3,<0.4 |
langchain-experimental | 0.3.0 | >=0.3,<0.4 |
Downstream packages
Package | Latest | Recommended constraint |
---|---|---|
langgraph | 0.2.20 | >=0.2.20,<0.3 |
langserve | 0.3.0 | >=0.3,<0.4 |
Integration packages
Package | Latest | Recommended constraint |
---|---|---|
langchain-ai21 | 0.2.0 | >=0.2,<0.3 |
langchain-aws | 0.2.0 | >=0.2,<0.3 |
langchain-anthropic | 0.2.0 | >=0.2,<0.3 |
langchain-astradb | 0.4.1 | >=0.4.1,<0.5 |
langchain-azure-dynamic-sessions | 0.2.0 | >=0.2,<0.3 |
langchain-box | 0.2.0 | >=0.2,<0.3 |
langchain-chroma | 0.1.4 | >=0.1.4,<0.2 |
langchain-cohere | 0.3.0 | >=0.3,<0.4 |
langchain-elasticsearch | 0.3.0 | >=0.3,<0.4 |
langchain-exa | 0.2.0 | >=0.2,<0.3 |
langchain-fireworks | 0.2.0 | >=0.2,<0.3 |
langchain-groq | 0.2.0 | >=0.2,<0.3 |
langchain-google-community | 2.0.0 | >=2,<3 |
langchain-google-genai | 2.0.0 | >=2,<3 |
langchain-google-vertexai | 2.0.0 | >=2,<3 |
langchain-huggingface | 0.1.0 | >=0.1,<0.2 |
langchain-ibm | 0.3.0 | >=0.3,<0.4 |
langchain-milvus | 0.1.6 | >=0.1.6,<0.2 |
langchain-mistralai | 0.2.0 | >=0.2,<0.3 |
langchain-mongodb | 0.2.0 | >=0.2,<0.3 |
langchain-nomic | 0.1.3 | >=0.1.3,<0.2 |
langchain-nvidia | 0.3.0 | >=0.3,<0.4 |
langchain-ollama | 0.2.0 | >=0.2,<0.3 |
langchain-openai | 0.2.0 | >=0.2,<0.3 |
langchain-pinecone | 0.2.0 | >=0.2,<0.3 |
langchain-postgres | 0.0.13 | >=0.0.13,<0.1 |
langchain-prompty | 0.1.0 | >=0.1,<0.2 |
langchain-qdrant | 0.1.4 | >=0.1.4,<0.2 |
langchain-redis | 0.1.0 | >=0.1,<0.2 |
langchain-sema4 | 0.2.0 | >=0.2,<0.3 |
langchain-together | 0.2.0 | >=0.2,<0.3 |
langchain-unstructured | 0.1.4 | >=0.1.4,<0.2 |
langchain-upstage | 0.3.0 | >=0.3,<0.4 |
langchain-voyageai | 0.2.0 | >=0.2,<0.3 |
langchain-weaviate | 0.0.3 | >=0.0.3,<0.1 |
Once you've updated to recent versions of the packages, you may need to address the following issues stemming from the internal switch from Pydantic v1 to Pydantic v2:
- If your code depends on Pydantic aside from LangChain, you will need to upgrade your pydantic version constraints to be
pydantic>=2,<3
. See Pydantic’s migration guide for help migrating your non-LangChain code to Pydantic v2 if you use pydantic v1. - There are a number of side effects to LangChain components caused by the internal switch from Pydantic v1 to v2. We have listed some of the common cases below together with the recommended solutions.
Common issues when transitioning to Pydantic 2
1. Do not use the langchain_core.pydantic_v1
namespace
Replace any usage of langchain_core.pydantic_v1
or langchain.pydantic_v1
with
direct imports from pydantic
.
For example,
from langchain_core.pydantic_v1 import BaseModel
to:
from pydantic import BaseModel
This may require you to make additional updates to your Pydantic code given that there are a number of breaking changes in Pydantic 2. See the Pydantic Migration for how to upgrade your code from Pydantic 1 to 2.
2. Passing Pydantic objects to LangChain APIs
Users using the following APIs:
BaseChatModel.bind_tools
BaseChatModel.with_structured_output
Tool.from_function
StructuredTool.from_function
should ensure that they are passing Pydantic 2 objects to these APIs rather than
Pydantic 1 objects (created via the pydantic.v1
namespace of pydantic 2).
While v1
objects may be accepted by some of these APIs, users are advised to
use Pydantic 2 objects to avoid future issues.
3. Sub-classing LangChain models
Any sub-classing from existing LangChain models (e.g., BaseTool
, BaseChatModel
, LLM
)
should upgrade to use Pydantic 2 features.
For example, any user code that's relying on Pydantic 1 features (e.g., validator
) should
be updated to the Pydantic 2 equivalent (e.g., field_validator
), and any references to
pydantic.v1
, langchain_core.pydantic_v1
, langchain.pydantic_v1
should be replaced
with imports from pydantic
.
from pydantic.v1 import validator, Field # if pydantic 2 is installed
# from pydantic import validator, Field # if pydantic 1 is installed
# from langchain_core.pydantic_v1 import validator, Field
# from langchain.pydantic_v1 import validator, Field
class CustomTool(BaseTool): # BaseTool is v1 code
x: int = Field(default=1)
def _run(*args, **kwargs):
return "hello"
@validator('x') # v1 code
@classmethod
def validate_x(cls, x: int) -> int:
return 1
Should change to:
from pydantic import Field, field_validator # pydantic v2
from langchain_core.pydantic_v1 import BaseTool
class CustomTool(BaseTool): # BaseTool is v1 code
x: int = Field(default=1)
def _run(*args, **kwargs):
return "hello"
@field_validator('x') # v2 code
@classmethod
def validate_x(cls, x: int) -> int:
return 1
CustomTool(
name='custom_tool',
description="hello",
x=1,
)
4. model_rebuild()
When sub-classing from LangChain models, users may need to add relevant imports to the file and rebuild the model.
You can read more about model_rebuild
here.
from langchain_core.output_parsers import BaseOutputParser
class FooParser(BaseOutputParser):
...
New code:
from typing import Optional as Optional
from langchain_core.output_parsers import BaseOutputParser
class FooParser(BaseOutputParser):
...
FooParser.model_rebuild()
Migrate using langchain-cli
The langchain-cli
can help update deprecated LangChain imports in your code automatically.
Please note that the langchain-cli
only handles deprecated LangChain imports and cannot
help to upgrade your code from pydantic 1 to pydantic 2.
For help with the Pydantic 1 to 2 migration itself please refer to the Pydantic Migration Guidelines.
As of 0.0.31, the langchain-cli
relies on gritql for applying code mods.
Installation
pip install -U langchain-cli
langchain-cli --version # <-- Make sure the version is at least 0.0.31
Usage
Given that the migration script is not perfect, you should make sure you have a backup of your code first (e.g., using version control like git
).
The langchain-cli
will handle the langchain_core.pydantic_v1
deprecation introduced in LangChain 0.3 as well
as older deprecations (e.g.,from langchain.chat_models import ChatOpenAI
which should be from langchain_openai import ChatOpenAI
),
You will need to run the migration script twice as it only applies one import replacement per run.
For example, say that your code is still using the old import from langchain.chat_models import ChatOpenAI
:
After the first run, you’ll get: from langchain_community.chat_models import ChatOpenAI
After the second run, you’ll get: from langchain_openai import ChatOpenAI
# Run a first time
# Will replace from langchain.chat_models import ChatOpenAI
langchain-cli migrate --help [path to code] # Help
langchain-cli migrate [path to code] # Apply
# Run a second time to apply more import replacements
langchain-cli migrate --diff [path to code] # Preview
langchain-cli migrate [path to code] # Apply
Other options
# See help menu
langchain-cli migrate --help
# Preview Changes without applying
langchain-cli migrate --diff [path to code]
# Approve changes interactively
langchain-cli migrate --interactive [path to code]