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52b0570bec
- Support thinking blocks in core's `convert_to_openai_messages` (pass through instead of error) - Ignore thinking blocks in ChatOpenAI (instead of error) - Support Anthropic-style image blocks in ChatOpenAI --- Standard integration tests include a `supports_anthropic_inputs` property which is currently enabled only for tests on `ChatAnthropic`. This test enforces compatibility with message histories of the form: ``` - system message - human message - AI message with tool calls specified only through `tool_use` content blocks - human message containing `tool_result` and an additional `text` block ``` It additionally checks support for Anthropic-style image inputs if `supports_image_inputs` is enabled. Here we change this test, such that if you enable `supports_anthropic_inputs`: - You support AI messages with text and `tool_use` content blocks - You support Anthropic-style image inputs (if `supports_image_inputs` is enabled) - You support thinking content blocks. That is, we add a test case for thinking content blocks, but we also remove the requirement of handling tool results within HumanMessages (motivated by existing agent abstractions, which should all return ToolMessage). We move that requirement to a ChatAnthropic-specific test.
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)
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
LLM (Legacy)
LLM refers to the legacy text-completion models that preceded chat models. 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