All functionality related to Naver, including HyperCLOVA X models, particularly those accessible through Naver Cloud CLOVA Studio.
Naver is a global technology company with cutting-edge technologies and a diverse business portfolio including search, commerce, fintech, content, cloud, and AI.
Naver Cloud is the cloud computing arm of Naver, a leading cloud service provider offering a comprehensive suite of cloud services to businesses through its Naver Cloud Platform (NCP).
Please refer to NCP User Guide for more detailed instructions (also in Korean).

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Installation and Setup

  • Get a CLOVA Studio API Key by issuing it and set it as an environment variable (CLOVASTUDIO_API_KEY).
Naver integrations live in two packages:
  • langchain-naver: a dedicated integration package for Naver.
  • langchain-naver-community: a community-maintained package and is not officially maintained by Naver or LangChain.
pip install -U langchain-naver
# pip install -U langchain-naver-community // Install to use Naver Search tool.
(Note) Naver integration via langchain-community, a collection of third-party integrations, is outdated.
  • Use langchain-naver instead as new features should only be implemented via this package.
  • If you are using langchain-community (outdated) and got a legacy API Key (that doesn’t start with nv-* prefix), you should set it as NCP_CLOVASTUDIO_API_KEY, and might need to get an additional API Gateway API Key by creating your app and set it as NCP_APIGW_API_KEY.

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Chat models

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ChatClovaX

See a usage example. 
from langchain_naver import ChatClovaX

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Embedding models

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ClovaXEmbeddings

See a usage example. 
from langchain_naver import ClovaXEmbeddings

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Tools

The Naver Search integration allows your LangChain applications to retrieve information from Naver’s search engine. This is particularly useful for Korean language queries and getting up-to-date information about Korean topics. To use the Naver Search tools, you need to:
  1. Sign in to the Naver Developers portal
  2. Create a new application and enable the Search API
  3. Obtain your NAVER_CLIENT_ID and NAVER_CLIENT_SECRET from the “Application List” section
  4. Set these as environment variables in your application
from langchain_naver_community.tool import NaverSearchResults
from langchain_naver_community.utils import NaverSearchAPIWrapper

# Set up the search wrapper
search = NaverSearchAPIWrapper()

# Create a tool
tool = NaverSearchResults(api_wrapper=search)
See a usage example for more details.

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Specialized Search Tools

The package also provides specialized search tools for different types of content: 
from langchain_naver_community.tool import NaverNewsSearch  # For news articles
from langchain_naver_community.tool import NaverBlogSearch  # For blog posts
from langchain_naver_community.tool import NaverImageSearch  # For images
Each of these can be used within LangChain agents to provide more targeted search capabilities.