langfuse

Free

🪢 Open source LLM engineering platform: LLM Observability, metrics, evals, prompt management, playground, datasets. Integrates with OpenTelemetry, Langchain, OpenAI SDK, LiteLLM, and more. 🍊YC W23

Model APIsFreeFree tier

Type

Open Source

Founded

2023

Company

Langfuse

Visit Website GitHub (26.5k stars)

About langfuse

Langfuse is an open-source AI engineering platform designed to help teams collaboratively debug, analyze, and iterate on LLM applications. It provides comprehensive observability through detailed tracing of LLM and non-LLM calls, including cost, latency, and user tracking. The platform includes a prompt management system with version control, deployment labeling, and interactive testing via a playground. Evaluation tools support online and offline assessments, LLM-as-a-judge, human annotation, and experiments with datasets. Langfuse offers an API-first architecture, data exports to blob storage, and integrates with OpenTelemetry, Langchain, OpenAI SDK, LiteLLM, and over 100 other frameworks. It is self-hostable and used by 19 of the Fortune 50 companies. Backed by Y Combinator (W23) and now part of ClickHouse.

Key Features

Comprehensive observability with detailed traces, sessions, user tracking, and cost/latency metrics

Prompt management with version control, deployment labels, and collaborative editing

Evaluation tools including online/offline evals, LLM-as-a-judge, human annotation, and experiments

LLM Playground for interactive prompt testing

Datasets and experiments for testing prompt versions

API-first architecture with extensive public API

Data exports to blob storage (batch and scheduled)

Integrations with OpenTelemetry, Langchain, OpenAI SDK, LiteLLM, and 100+ frameworks

Self-hostable and open source with enterprise security features (SSO, RBAC, audit logs)

Agent tracing with graph visualization for complex workflows

Pros & Cons

Pros

Open source and self-hostable, reducing vendor lock-in
Free tier available with generous limits (50k units/month)
Extensive integration ecosystem with major LLM frameworks and observability standards
Robust prompt versioning and deployment workflow
Comprehensive evaluation capabilities including human annotation
Used and trusted by large enterprises (Fortune 500)

Cons

Higher-tier paid plans can be expensive for small teams (Core $29/mo, Pro $199/mo)
Self-hosting requires infrastructure management and technical setup
Learning curve for setting up tracing and evaluations initially
Some advanced features (SSO, audit logs) only available in Enterprise plan

Best For

Debugging and monitoring LLM applications in productionManaging and versioning prompts collaboratively across teamsEvaluating output quality and tracking regressionsExperimenting with different prompts and models in a playgroundCost and latency optimization for LLM callsUser behavior analysis and session tracking for conversational AI

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FAQ

Is Langfuse open source?

Yes, Langfuse is open source and available on GitHub with over 31,716 stars. It is self-hostable and extensible.

What integrations does Langfuse support?

Langfuse integrates with OpenTelemetry, Langchain, OpenAI SDK, LiteLLM, and over 100 other libraries and frameworks. It also supports proxy-based logging via LiteLLM.

Can I self-host Langfuse?

Yes, Langfuse offers a self-hosted option. You can deploy it on your own infrastructure for full control.

How much does Langfuse cost?

Langfuse has a free Hobby plan with 50k units/month and 30-day data retention. Paid plans start at $29/month (Core) for unlimited users and 100k units/month, $199/month (Pro) with extended retention, and Enterprise at $2499/month with advanced security and support.

Does Langfuse support multi-turn conversations?

Yes, Langfuse supports session tracking for multi-step conversations and agentic workflows, with agent graph visualization.