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## Goal Solve the following problems with `langchain-openai`: - Structured output with `o1` [breaks out of the box](https://langchain.slack.com/archives/C050X0VTN56/p1735232400232099). - `with_structured_output` by default does not use OpenAI’s [structured output feature](https://platform.openai.com/docs/guides/structured-outputs). - We override API defaults for temperature and other parameters. ## Breaking changes: - Default method for structured output is changing to OpenAI’s dedicated [structured output feature](https://platform.openai.com/docs/guides/structured-outputs). For schemas specified via TypedDict or JSON schema, strict schema validation is disabled by default but can be enabled by specifying `strict=True`. - To recover previous default, pass `method="function_calling"` into `with_structured_output`. - Models that don’t support `method="json_schema"` (e.g., `gpt-4` and `gpt-3.5-turbo`, currently the default model for ChatOpenAI) will raise an error unless `method` is explicitly specified. - To recover previous default, pass `method="function_calling"` into `with_structured_output`. - Schemas specified via Pydantic `BaseModel` that have fields with non-null defaults or metadata (like min/max constraints) will raise an error. - To recover previous default, pass `method="function_calling"` into `with_structured_output`. - `strict` now defaults to False for `method="json_schema"` when schemas are specified via TypedDict or JSON schema. - To recover previous behavior, use `with_structured_output(schema, strict=True)` - Schemas specified via Pydantic V1 will raise a warning (and use `method="function_calling"`) unless `method` is explicitly specified. - To remove the warning, pass `method="function_calling"` into `with_structured_output`. - Streaming with default structured output method / Pydantic schema no longer generates intermediate streamed chunks. - To recover previous behavior, pass `method="function_calling"` into `with_structured_output`. - We no longer override default temperature (was 0.7 in LangChain, now will follow OpenAI, currently 1.0). - To recover previous behavior, initialize `ChatOpenAI` or `AzureChatOpenAI` with `temperature=0.7`. - Note: conceptually there is a difference between forcing a tool call and forcing a response format. Tool calls may have more concise arguments vs. generating content adhering to a schema. Prompts may need to be adjusted to recover desired behavior. --------- Co-authored-by: Jacob Lee <jacoblee93@gmail.com> Co-authored-by: Bagatur <baskaryan@gmail.com> |
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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