Langfuse Selfhosting
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In this tutorial, you’ll learn how to run Langfuse locally using Docker Compose and integrate it with your LLM-based applications (e.g., those built with LangChain). Langfuse provides comprehensive tracking and observability for:
Token usage
Execution time and performance metrics
Error rates and unexpected behaviors
Agent and chain interactions
By the end of this tutorial, you’ll have a local Langfuse instance running on http://localhost:3000 and be ready to send tracking events from your application.
[Note]
langchain-opentutorial
is a package that provides a set of easy-to-use environment setup, useful functions and utilities for tutorials.
set environment variables is in .env.
Copy the contents of .env_sample and load it into your .env with the key you set.
Docker & Docker Compose
Docker Desktop (Mac/Windows) or
Docker Engine & Docker Compose plugin (Linux)
Git
Make sure you can run git clone from your terminal or command prompt.
Sufficient System Resources
Running Langfuse locally requires a few GB of memory available for Docker containers.
open your terminal and run the following command:
This will download the Langfuse repository to your local machine. and move into the directory.
Inside the langfuse
directory, simply run:
Docker Compose will pull and start multiple containers for the Langfuse stack:
Database (Postgres)
Langfuse backend services
Langfuse web/UI
This is the simplest way to run Langfuse locally and explore its features.
After 2-3 minutes, you should see logs indicating that the 'langfuse-web-1' container is Ready. At that point, open your browser to:
You will be greeted by the Langfuse login/setup sceen or homepage.
Follow the on-screen prompts to configure your local Langfuse instance(e.g., create an initial admin user). Once the setup completes, you can log in to the Langfuse UI.
From here, you will be able to:
Create projects to track events from your LLM apps
Invite team members (if applicable)
Adjust various settings like API keys, encryption or networking
To start collecting trace data in your local Langfuse instance, you’ll need to send events from your application code:
Obtain your Project Key / API Key from the Langfuse UI.
Install the appropriate Langfuse SDK in your application environment (e.g., npm install @langfuse/node for Node.js, or pip install langfuse for Python—if available).
Initialize the Langfuse client and pass in the host (pointing to your local instance) and the API key.
Record events (e.g., chain steps, LLM requests, agent actions) in your code to send structured data to Langfuse.
(Refer to Langfuse’s official docs for language-specific integration examples.)
Once you’re up and running:
UI: Go to http://localhost:3000 for the Langfuse dashboard.
Logs: Monitor the Docker logs in your terminal for any errors or system messages.
Configuration: Check the configuration guide for advanced setups:
Authentication & SSO
Encryption
Headless Initialization
Networking
Organization Creators
UI Customization
Stopping/Restarting
To stop the containers, press Ctrl + C in the same terminal window running Docker Compose. If you used a detached mode (-d), then:
Add the -v flag to remove volumes as well (which also deletes stored data).
To upgrade to the latest Langfuse version, simply:
This will pull the newest images and restart Langfuse. Refer to the upgrade guide for more detailed steps.
You can try out langfuse by running the code below.
Set up the environment. You may refer to for more details.
You can checkout the for more details.