langchain-databricks

What it is and what it does

langchain-databricks was an integration package that bridged LangChain applications with Databricks services—vector search, chat models, and MLflow tracking. It depended on langchain-core for the LangChain framework, databricks-vectorsearch for semantic search, mlflow for experiment tracking, and numpy and scipy for numerical operations.

However, this package is now deprecated. The maintainers have consolidated all functionality into databricks-langchain, which is the active, forward-looking package. Existing code using langchain-databricks will continue to run, but no new features or fixes are planned here; all development has moved to the replacement package.

Use it for:

• Connecting a LangChain chatbot to Databricks vector search for semantic retrieval over enterprise data
• Integrating Databricks Foundation Models as LLM backends in LangChain applications
• Logging and tracking LangChain experiments and model runs via MLflow on Databricks
• Building RAG (retrieval-augmented generation) pipelines that query Databricks vector stores

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Connects LangChain applications to Databricks services including vector search, chat models, and MLflow integration, but is now deprecated in favor of databricks-langchain.

No. Do not install this package for new projects. It is deprecated and dormant; install databricks-langchain instead, which provides all the same functionality with active maintenance. If you have existing code using langchain-databricks, plan a migration to databricks-langchain to ensure you receive future updates and bug fixes.

Install

langchain-databricks on PyPI

pip install langchain-databricks

uv add langchain-databricks

poetry add langchain-databricks

Installing langchain-databricks

Before you install

Low install friction with straightforward dependencies, but the package is dormant—last release was 602 days ago. Maintenance has ceased in favor of the consolidated databricks-langchain package.

License in practice

MIT license permits commercial and private use with minimal restrictions, but this is a deprecated package; new projects should use databricks-langchain instead.

Quickstart

pip install langchain-databricks
from langchain_databricks import ChatDatabricks
chat_model = ChatDatabricks(endpoint="databricks-meta-llama-3-70b-instruct")
response = chat_model.invoke("What is MLflow?")

Requires Python 3.9 or later; Databricks workspace credentials and endpoint configuration needed at runtime.

Verify before relying

• Whether existing code using langchain-databricks will continue to work without breaking changes as Databricks evolves
• Compatibility guarantees with future versions of langchain-core, databricks-vectorsearch, and mlflow

Package facts

Evidence: langchain_databricks-0.1.2-py3-none-any.whl

Tags

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