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4b08a7e8e8
This fix ensures that the chunk size is correctly determined when processing text embeddings. Previously, the code did not properly handle cases where chunk_size was None, potentially leading to incorrect chunking behavior. Now, chunk_size_ is explicitly set to either the provided chunk_size or the default self.chunk_size, ensuring consistent chunking. This update improves reliability when processing large text inputs in batches and prevents unintended behavior when chunk_size is not specified. --------- Co-authored-by: Chester Curme <chester.curme@gmail.com>
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