langfuse
Open source AI engineering platform: LLM evals, observability, metrics, prompt management, playground, datasets
GraphCanon updated 2w · GitHub synced 2w · 34 views this month
Decision brief
Langfuse is an open source AI engineering platform designed to support evaluation and observability functions for large language models.
Good fit when
- Use Langfuse if you need advanced prompt management tools, as it offers comprehensive features specifically tailored for managing prompts efficiently.
- It is ideal when your project involves integrating with OpenTelemetry because Langfuse natively supports integration with this tool, enhancing observability and metrics tracking in a seamless manner.
Avoid when
- Avoid using Langfuse if you prefer a vendor-managed service as it requires self-hosting. This can be less desirable for teams looking to minimize infrastructure management.
- If your development environment is not compatible with Kubernetes, Docker Compose configurations, or major cloud providers (AWS, Azure, GCP) that Langfuse supports via specific templates and Helm, it
- Pricing:
- freemium - Langfuse offers an open-source version under MIT license except for some 'ee' folders, indicating a possible enterprise edition. Specific pricing details are not provided within the repository content
- Requirements:
- Requires Docker; Self-hosting options include Docker Compose and Kubernetes for deployment.
Observed Jul 11, 2026 · Source: enrich:decision_facts
Verify the decision
Adoption
Package downloads where a registry match exists. GitHub stars (32,271) are secondary evidence.
- npm downloads (30d)
- 7,176,492·npm downloads API·2w
- Docker Hub pulls (30d)
- 14,098,066·Docker Hub API·2w
Maintenance and security
Full trust report- Maintenance
- Very active (0d since push)
- As of 2w
- Provenance
- Not a fork · Organization account
- As of 2w
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
npm install langfuseHow it fits your stack(25)
Typed graph edges - alternatives, integrations, successors, and dependencies. Ranked by relationship type, not raw GitHub stars.
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Integrates
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Langfuse provides tools for evaluating and monitoring large language models with features like prompt management, LLM evaluation, and integration with various systems such as OpenTelemetry.
Capability facts
- Deploy
- Self-host
Source: dockerfile:docker-compose.yml · Aug 1, 2026
- Docker
- Dockerfile present
Source: dockerfile:docker-compose.yml · Aug 1, 2026
- CLI
- CLI entrypoint
Source: package.json:bin|scripts · Aug 1, 2026
- MCP server
- No MCP server detected
Source: repo_scan · Aug 1, 2026
- Languages
- typescript, javascript
Source: github.language+package.json · Aug 1, 2026
Categories
Graph entities
Tags
README
Self-Host Langfuse
Run Langfuse on your own infrastructure:
-
Local (docker compose): Run Langfuse on your own machine in 5 minutes using Docker Compose.
# Get a copy of the latest Langfuse repository git clone --depth=1 https://github.com/langfuse/langfuse.git cd langfuse # Run the langfuse docker compose docker compose up -
VM: Run Langfuse on a single Virtual Machine using Docker Compose.
-
Kubernetes (Helm): Run Langfuse on a Kubernetes cluster using Helm. This is the preferred production deployment.
See self-hosting documentation to learn more about architecture and configuration options.
[!TIP] Self-hosting Langfuse? Subscribe to the self-hosting update list to get an email about important features and new releases for open source Langfuse — self-hosting updates only, no marketing.
🥇 License
This repository is MIT licensed, except for the ee folders. See LICENSE and docs for more details.
For agents
This page has a .md twin and JSON over the API.