mirror of
https://github.com/hwchase17/langchain
synced 2024-11-11 19:11:02 +00:00
236e957abb
After this PR chat models will correctly handle pydantic 2 with
bind_tools and with_structured_output.
```python
import pydantic
print(pydantic.__version__)
```
2.8.2
```python
from langchain_openai import ChatOpenAI
from pydantic import BaseModel, Field
class Add(BaseModel):
x: int
y: int
model = ChatOpenAI().bind_tools([Add])
print(model.invoke('2 + 5').tool_calls)
model = ChatOpenAI().with_structured_output(Add)
print(type(model.invoke('2 + 5')))
```
```
[{'name': 'Add', 'args': {'x': 2, 'y': 5}, 'id': 'call_PNUFa4pdfNOYXxIMHc6ps2Do', 'type': 'tool_call'}]
<class '__main__.Add'>
```
```python
from langchain_openai import ChatOpenAI
from pydantic.v1 import BaseModel, Field
class Add(BaseModel):
x: int
y: int
model = ChatOpenAI().bind_tools([Add])
print(model.invoke('2 + 5').tool_calls)
model = ChatOpenAI().with_structured_output(Add)
print(type(model.invoke('2 + 5')))
```
```python
[{'name': 'Add', 'args': {'x': 2, 'y': 5}, 'id': 'call_hhiHYP441cp14TtrHKx3Upg0', 'type': 'tool_call'}]
<class '__main__.Add'>
```
Addresses issues: https://github.com/langchain-ai/langchain/issues/22782
---------
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
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| poetry.lock | ||
| pyproject.toml | ||
| README.md | ||
langchain-openai
This package contains the LangChain integrations for OpenAI through their openai SDK.
Installation and Setup
- Install the LangChain partner package
pip install langchain-openai
- Get an OpenAI api key and set it as an environment variable (
OPENAI_API_KEY)
LLM
See a usage example.
from langchain_openai import OpenAI
If you are using a model hosted on Azure, you should use different wrapper for that:
from langchain_openai import AzureOpenAI
For a more detailed walkthrough of the Azure wrapper, see here
Chat model
See a usage example.
from langchain_openai import ChatOpenAI
If you are using a model hosted on Azure, you should use different wrapper for that:
from langchain_openai import AzureChatOpenAI
For a more detailed walkthrough of the Azure wrapper, see here
Text Embedding Model
See a usage example
from langchain_openai import OpenAIEmbeddings
If you are using a model hosted on Azure, you should use different wrapper for that:
from langchain_openai import AzureOpenAIEmbeddings
For a more detailed walkthrough of the Azure wrapper, see here