---
id: langchain-ollama
version: "1.1.0"
license: MIT
license_treatment: permissive
maintenance: active
---

# langchain-ollama — An integration package connecting Ollama and LangChain

License: permissive · Maintenance: active · Downloads: 3.1M/mo

## What it is and what it does

This package is a LangChain integration that bridges your Python application to Ollama, a tool for running large language models locally. Instead of calling a remote API, you use LangChain's standard interfaces to interact with models running on your own machine or network via Ollama. It depends on langchain-core for the framework abstractions and ollama for the underlying model communication.

The integration lets you build LangChain applications—chains, agents, RAG systems—that use locally-hosted models rather than cloud-based APIs. This is useful when you need privacy, want to avoid API costs, or prefer to run models on your own hardware. The package is actively maintained, supports Python 3.10 through 3.14, and carries no known security vulnerabilities.

Use it for:

- Build a RAG pipeline that retrieves documents and generates answers using a locally-run model without cloud API calls.
- Create a chatbot or agent that uses Ollama models through LangChain's standard chat and tool-calling interfaces.
- Prototype LangChain applications offline or in air-gapped environments where cloud API access is unavailable.
- Run inference on sensitive data using local models to avoid sending data to external services.
- Experiment with different open-source models through Ollama while keeping the same LangChain application code.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Connects LangChain applications to Ollama, enabling use of locally-run language models through a unified LangChain interface.

Yes. This is a lightweight, actively maintained integration with no security issues, permissive licensing, and strong community backing. Install it if you want to use Ollama models within LangChain applications. The only prerequisite is having Ollama itself installed and running separately.

## Install

pip install langchain-ollama
uv add langchain-ollama
poetry add langchain-ollama

## Installing langchain-ollama

Before you install: Low friction install with just two runtime dependencies. Actively maintained with recent releases; repo shows strong community engagement and no archived status.

License in practice: MIT license permits unrestricted use, modification, and distribution with minimal restrictions—suitable for both open-source and proprietary projects.

Quickstart:

pip install langchain-ollama

from langchain_ollama import OllamaLLM

llm = OllamaLLM(model="llama2")
response = llm.invoke("What is machine learning?")

Ollama must be installed and running as a service on your system or network before the integration can connect to it.

Verify before relying:

- Whether Ollama must be installed and running separately as a system service or daemon
- Specific Ollama versions or model formats supported by this integration
- Performance characteristics or latency overhead of the LangChain-Ollama bridge

## Package facts

- License: MIT (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 3.1M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

langchain ollama integration, local llm with langchain, ollama language model wrapper, langchain local model provider, run ollama in langchain, langchain ollama connector, langchain-integration, local-llm, ollama

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