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Langfuse GitHub Banner

Contributing to Langfuse

First off, thanks for taking the time to contribute! ❤️

The best ways to contribute to Langfuse:

  • Submit and vote on Ideas
  • Create and comment on Issues
  • Open a PR.

We welcome contributions through GitHub pull requests. This document outlines our conventions regarding development workflow, commit message formatting, contact points, and other resources. Our goal is to simplify the process and ensure that your contributions are easily accepted.

We gratefully welcome improvements to documentation (docs repo), the core application (this repo) and the SDKs (Python, JS).

The maintainers are available on Discord in case you have any questions.

And if you like the project, but just don't have time to contribute code, that's fine. There are other easy ways to support the project and show your appreciation, which we would also be very happy about:

  • Star the project;
  • Tweet about it;
  • Refer to this project in your project's readme;
  • Submit and vote on Ideas;
  • Create and comment on Issues;
  • Mention the project at local meetups and tell your friends/colleagues.

Making a change

Before making any significant changes, please open an issue. Discussing your proposed changes ahead of time will make the contribution process smooth for everyone. Changes that were not discussed in an issue may be rejected.

Once we've discussed your changes and you've got your code ready, make sure that tests are passing and open your pull request.

A good first step is to search for open issues. Issues are labeled, and some good issues to start with are labeled: good first issue.

Project Overview

We recommend checking out DeepWiki to familiarize yourself with the project:

Ask DeepWiki

Technologies we use

  • Application (this repository)
    • NextJS 14, pages router
    • NextAuth.js / Auth.js
    • tRPC: Frontend APIs
    • Prisma ORM
    • Zod v4
    • Tailwind CSS
    • shadcn/ui tailwind components (using Radix and tanstack)
    • Fern: generate OpenAPI spec and Pydantic models
  • JS SDK (langfuse/langfuse-js)
    • openapi-typescript to generated types based on OpenAPI spec
  • Python SDK (langfuse/langfuse-python)
    • Pydantic for input validation, models generated by fern

Architecture Overview

See this diagram for an overview of the architecture.

Network Overview

flowchart TB
    User["UI, API, SDKs"]
    subgraph vpc["VPC"]
        Web["Web Server<br/>(langfuse/langfuse)"]
        Worker["Async Worker<br/>(langfuse/worker)"]
        Postgres["Postgres - OLTP<br/>(Transactional Data)"]
        Cache["Redis/Valkey<br/>(Cache, Queue)"]
        Clickhouse["Clickhouse - OLAP<br/>(Observability Data)"]
        S3["S3 / Blob Storage<br/>(Raw events, multi-modal attachments)"]
    end
    LLM["LLM API/Gateway<br/>(optional)"]

    User --> Web
    Web --> S3
    Web --> Postgres
    Web --> Cache
    Web --> Clickhouse
    Web -.->|"optional for playground"| LLM

    Cache --> Worker
    Worker --> Clickhouse
    Worker --> Postgres
    Worker --> S3
    Worker -.->|"optional for evals"| LLM
Loading

Database Overview

The diagram below may not show all relationships if the foreign key is not defined in the database schema. For instance, trace_id in the observation table is not defined as a foreign key to the trace table to allow unordered ingestion of these objects, but it is still a foreign key in the application code.

Full database schema: packages/shared/prisma/schema.prisma

Repository Structure

We built a monorepo using pnpm and turbo to manage the dependencies and build process. The monorepo contains the following packages:

  • web: is the main application package providing Frontend and Backend APIs for Langfuse.
  • worker: contains an application for asynchronous processing of tasks.
  • packages:
    • shared: contains shared code between the above packages.
    • config-eslint: contains eslint configurations which are shared between the above packages.
    • config-typescript: contains typescript configurations which are shared between the above packages.
  • ee: contains all enterprise features. See EE README for more details.

Development Setup

Requirements

  • Node.js 24 as specified in the .nvmrc
  • Pnpm v.9.5.0
  • Docker to run the database locally
  • Clickhouse client

Note: You can also simply run Langfuse in a GitHub Codespace via the provided devcontainer. To do this, click on the green "Code" button in the top right corner of the repository and select "Open with Codespaces".

Codex Cloud Setup

You can also attach this repository to an OpenAI Codex cloud environment. The cloud environment itself is configured in the Codex UI, while the repo-owned bootstrap is versioned in:

  • scripts/codex/setup.sh
  • scripts/codex/maintenance.sh

Recommended Codex UI configuration:

  1. Create a new cloud environment for this repository in the Codex UI.

  2. Choose a base environment with Node.js 24 support.

  3. Set the setup script to:

    bash scripts/codex/setup.sh

  4. Set the maintenance script to:

    bash scripts/codex/maintenance.sh

  5. Keep internet access disabled by default, or only allow the minimum domains needed for your task.

  6. Add secrets and environment variables in the Codex UI instead of committing them to the repository.

Notes:

  • This Codex setup is intended for repository tasks such as code changes, linting, typechecking, and targeted tests.
  • It does not start the full Langfuse stack. Local development still uses Docker and pnpm run dx / pnpm run dev.
  • Running the full application inside Codex requires external services for PostgreSQL, Redis, ClickHouse, and object storage, plus matching environment variables in the Codex UI.

Steps

  1. Install development dependencies:

  2. Fork the repository and clone it locally

    git clone https://github.com/langfuse/langfuse.git
cd langfuse

  3. Install dependencies and set up pre-commit hooks

    pnpm install
pnpm run prepare  # Sets up Husky pre-commit hooks for code formatting

  4. Create an env file

     cp .env.dev.example .env

  5. Run the entire infrastructure in dev mode. Note: if you have an existing database, this command wipes it. Also, this will fail on the very first run. Please run it again.

    pnpm run dx # first run only (resets db, docker containers, etc...)
pnpm run dev # any subsequent runs

    You will be asked whether you want to reset Postgres and ClickHouse. Confirm both with 'Y' and press enter.

  6. Open the web app in your browser to start using Langfuse:

  7. Log in as a test user:

    • Username: demo@langfuse.com
    • Password: password

To get comprehensive example data, you can use the seed command:

pnpm run db:seed:examples

Monorepo quickstart

  • Available packages and their dependencies

    Packages are included in the monorepo according to the pnpm-workspace.yaml file. Each package maintains its own dependencies defined in the package.json. Internal dependencies can be added as well by adding them to the package dependencies: "@langfuse/shared": "workspace:*".

  • Executing commands

    You can run commands in all packages at once. For example, to install all dependencies in all packages, you can execute:

    pnpm install
pnpm run dev
pnpm --filter=web run dev # execute command only in one package
pnpm tc                   # fast typecheck all packages
pnpm build:check          # Full Next.js build to alternate dir (can run parallel with dev server)

    In the root package.json, you can find scripts which are executed with turbo e.g. turbo run dev. These scripts are executed with the help of Turbo. Turbo executes the commands in all packages taking care of the correct order of execution. Task definitions can be found in the turbo.config.js file.

  • Run migrations

    To run migrations, you can execute the following command.

    pnpm run db:migrate -- --name <name of the migration>

Note

If you frequently switch branches, use pnpm run dx instead of pnpm run dev. This command will install dependencies, reset the database (wipe and apply all migrations), and run the database seeder with example data before starting the development server.

Note

If you find yourself stuck and want to clean the repo, execute pnpm run nuke. It will remove all node_modules and build files.

System behavior

Ingestion API (/public/api/ingestion)

  • the ingestion API takes different event types (creation and updates of traces, generations, spans, events)
  • The API loops through each event and:
    • validates the event
    • stores the event raw in the events table
    • calculates tokens for generations
    • matches models from the models table to model for generations events
    • upserts the event in the traces or observations table
  • returns a 207 HTTP status code with a list of errors if any event failed to be ingested

Commit messages

On the main branch, we adhere to the best practices of conventional commits. All pull requests and branches are squash-merged to maintain a clean and readable history. This approach ensures the addition of a conventional commit message when merging contributions.

Running Unit Tests

All tests run in the CI and must pass before merging. All tests run against a running langfuse instance and write/delete real data from the database.

Test Database Setup

Per default, the tests use the local development database. Therefore, wiping your data in the process. For proper test isolation, create a .env.test file in the root directory:

cp .env.test.example .env.test

Then, a different PostgreSQL and Redis are used for the tests. The .env.test file only overrides the set values and falls back on .env for all undefined values.

  • PostgreSQL: Uses separate langfuse_test database for isolation
  • ClickHouse: Uses shared default database for now
  • Redis: Uses database 1 instead of 0 for isolation (Redis data is not cleaned between tests)

Tests automatically create the PostgreSQL test database if it doesn't exist and clean up data between runs.

Tests in the web package (public API)

We're using Jest with in the web package. Therefore, if you want to provide an argument to the test runner, do it directly without an intermittent --.

There are two types of unit tests:

  • test (server tests)
  • test-client

To run a specific test, for example the test: "should handle special characters in prompt names" in prompts.v2.servertest.ts, run:

cd web  # or with --filter=web
pnpm test --testPathPatterns="prompts\.v2\.servertest" --testNamePattern="should handle special characters in prompt names"

To run all tests:

pnpm run test

Run interactively in watch mode (not recommended!)

pnpm run test:watch

Tests in the worker package

For the worker package, we're using vitest to run unit tests.

pnpm run test --filter=worker -- FILE_YOU_WANT_TO_TEST.ts -t "test name"

CI/CD

We use GitHub Actions for CI/CD, the configuration is in .github/workflows/pipeline.yml

CI on main and pull_request

  • Check Linting
  • E2E test of API using Jest
  • E2E tests of UI using Playwright

CD on main

  • Publish Docker image to GitHub Packages if CI passes. Done on every push to main branch. Only released versions are tagged with latest.

Staging environment

We run a staging environment at https://staging.langfuse.com that is automatically deployed on every push to main branch.

The same environment is also used for preview deployments of pull requests. Limitations:

  • SSO is not available as dynamic domains are not supported by most SSO providers.
  • When making changes to the database, migrations to the staging database need to be applied manually by a maintainer. If you want to interactively test database changes in the staging environment, please reach out.

You can use the staging environment end-to-end with the Langfuse integrations or SDKs (host: https://staging.langfuse.com). However, please note that the staging environment is not intended for production use and may be reset at any time.

Production environment

We run two separate release/deployment processes:

  1. Langfuse Cloud deployment (frequent):
    • Every commit on the production branch triggers an ECS deployment to Langfuse Cloud.
    • To deploy current main to Langfuse Cloud, promote main to production via promote-main-to-production.yml (instead of force pushing from a local machine).
  2. Open-source release (less frequent):
    • The open-source Docker release process is handled via release.yml for self-hosted production users.

You can trigger the Langfuse Cloud promotion in either way:

  1. Preferred local command:
pnpm run release:cloud

This wraps the GitHub CLI trigger and performs preflight checks (main branch/sync checks and migration diff checks against production) before dispatching the workflow.

  1. GitHub UI: open Actions -> Promote Main to Production -> Run workflow, then set confirm=promote.

Theming

At Langfuse, we utilize CSS variables to manage our theme settings across the platform.

Our approach leverages separate CSS variables for backgrounds (--background) and foregrounds (--foreground), fully adhering to the shadcn/ui color conventions. The background suffix can be omitted if the variable is used for the background color of the component. We recommend using HSL values for these colors to enhance consistency and customization. There is no need to manually handle dark mode styling with "dark:" prefixes, as next-themes automatically manages the theme switching.

Given the following CSS variables:

--primary: 222.2 47.4% 11.2%; // e.g. background-color
--primary-foreground: 210 40% 98%; // e.g. text-color

The background color of the following component will be hsl(var(--primary)) and the foreground color will be hsl(var(--primary-foreground)).

<div class="bg-primary text-primary-foreground">Hello</div>

Color Variables

Variable Description Examples
--background Background color Default background color of body
--foreground Foreground color Default text color of body
--muted Muted background color TabsList, Skeleton and Switch
--muted-foreground Muted foreground color
--popover Popover background color DropdownMenu, HoverCard, Popover
--popover-foreground Popover foreground color
--card Card background color Card
--card-foreground Card foreground color
--border Border color Default border color
--input Input field border color Input, Select, Textarea
--primary Primary button background colors Button variant="primary"
--primary-foreground Primary button foreground color
--secondary Secondary button background color Button variant="secondary"
--secondary-foreground Secondary button foreground color
--accent Used for accents such as hover effects DropdownMenuItem, SelectItem
--accent-foreground Used for texts on hover effects DropdownMenuItem, SelectItem
--destructive Destructive action color for background Button variant="destructive"
--destructive-foreground Destructive action color for text
--ring Focus ring color MultiSelect
--primary-accent Primary accent color used for branding Layout
--hover-primary-accent Primary accent color used for hover effects for links SignIn and AuthCloudRegionSwitch
--muted-green Muted green for Event label ObservationTree
--muted-magenta Muted magenta for Generation label ObservationTree
--muted-blue Muted blue for Span label ObservationTree
--muted-gray Muted gray for disabled status badges StatusBadge
--accent-light-green Light green accent for background of output and assistant messages IOPreview, Generations, Traces
--accent-dark-green Dark green accent for border of output and assistant messages CodeJsonViewer and IOPReview
--light-red Light red for error background level-color and StatusBadge
--dark-red Dark red for error text and error badge dot color level-color and ErrorPage
--light-yellow Light yellow for warning background LevelColor
--dark-yellow Dark yellow for warning text LevelColor
--light-green Light green for success status badge background StatusBadge
--dark-green Dark green for success status badge text and dot StatusBadge
--light-blue Light blue for background of Staging label LangfuseLogo
--dark-blue Dark blue for text and border of Staging label LangfuseLogo
--accent-light-blue Light blue accent for table link hover effect TableLink
--accent-dark-blue Dark blue accent for table link text TableLink

Adding New Colors

  1. Global Definitions: Add new CSS variable definitions in the global.css file.
  2. Tailwind Configuration: Reflect these new colors in the tailwind.config.js to maintain alignment with Tailwind's utility classes.

By following these guidelines, you can ensure that any contributions to our theme are consistent, maintainable, and aligned with our design system.

Maintainers

Using secrets stored in 1Password

When applying changes to non-local environments, you may need to use secrets stored in 1Password. We use the 1Password CLI for this purpose.

Example:

op run --env-file="./.env" -- pnpm --filter=shared run db:deploy

Editing default models and prices

You can update the default AI models and prices by adding or updating an entry in worker/src/constants/default-model-prices.json.

Please note that

  • prices are in USD
  • the list is ordered by ID, so make sure to keep this order and insert new models at the end of the list
  • the updated_at field must be updated with the current date in ISO 8601 format. Otherwise, the change will be ignored.

Transition period until V3 release

Until the V3 release, both the JSON record must be updated and a migration must be created to continue supporting self-hosted users. Note that the migration must updated both the models as well as the prices table accordingly.

Updating the OpenAPI Specs & fern SDKs

We maintain the API specifications manually to guarantee a high degree of understandability. If you made changes to the API, please update the respective .yml files in fern/apis/....

To generate the respective openapi.yml files which power the online API reference & SDKs, run:

npx fern-api generate --api server  # for the server API
npx fern-api generate --api client  # for the client API
npx fern-api generate --api organizations  # for the organizations API

Note: You need a signed in fern account to run those commands.

License

Langfuse is MIT licensed, except for ee/ folder. See LICENSE and docs for more details.

When contributing to the Langfuse codebase, you need to agree to the Contributor License Agreement. You only need to do this once and the CLA bot will remind you if you haven't signed it yet.