LLM Observability, Prompt Management, LLM Evaluations,
Datasets, LLM Metrics, and Prompt Playground
Langfuse uses Github Discussions for Support and Feature Requests.
We’re hiring. Join us in Product Engineering and Developer Relations.
- LLM Analytics: Track metrics (cost, latency, quality) and gain insights from dashboards & data exports (Analytics)
- LLM Evaluations: Collect and calculate scores for your LLM completions (Scores & Evaluations)
- Experiments: Track and test app behaviour before deploying a new version
Managed deployment by the Langfuse team, generous free-tier (hobby plan), no credit card required.
» Langfuse Cloud
Self-Hosting Open Source LLM Observability with Langfuse
# Clone repository
git clone https://github.com/langfuse/langfuse.git
cd langfuse
# Run server and database
docker compose up -d
→ Learn more about deploying locally
Langfuse is simple to self-host and keep updated. It currently requires only a single docker container and a postgres database.
→ Self Hosting Instructions
Templated deployments: Railway, GCP, AWS, Azure, Kubernetes and others
You need a Langfuse public and secret key to get started. Sign up here and find them in your project settings.
Ingesting Data · Instrumenting Your Application · LLM Observability with Langfuse
Note: We recommend using our fully async, typed SDKs that allow you to instrument any LLM application with any underlying model. They are available in Python (Decorators) & JS/TS. The SDKs will always be the most fully featured and stable way to ingest data into Langfuse.
See the → Quickstart to integrate Langfuse.
LLM Observability Integrations
Integration | Supports | Description |
---|---|---|
SDK | Python, JS/TS | Manual instrumentation using the SDKs for full flexibility. |
OpenAI | Python, JS/TS | Automated instrumentation using drop-in replacement of OpenAI SDK. |
Langchain | Python, JS/TS | Automated instrumentation by passing callback handler to Langchain application. |
LlamaIndex | Python | Automated instrumentation via LlamaIndex callback system. |
Haystack | Python | Automated instrumentation via Haystack content tracing system. |
LiteLLM | Python, JS/TS (proxy only) | Use any LLM as a drop in replacement for GPT. Use Azure, OpenAI, Cohere, Anthropic, Ollama, VLLM, Sagemaker, HuggingFace, Replicate (100+ LLMs). |
Vercel AI SDK | JS/TS | TypeScript toolkit designed to help developers build AI-powered applications with React, Next.js, Vue, Svelte, Node.js. |
API | Directly call the public API. OpenAPI spec available. |
Packages integrated with Langfuse:
Name | Description |
---|---|
Instructor | Library to get structured LLM outputs (JSON, Pydantic) |
Dify | Open source LLM app development platform with no-code builder. |
Ollama | Easily run open source LLMs on your own machine. |
Mirascope | Python toolkit for building LLM applications. |
Flowise | JS/TS no-code builder for customized LLM flows. |
Langflow | Python-based UI for LangChain, designed with react-flow to provide an effortless way to experiment and prototype flows. |
In order of preference the best way to communicate with us:
This repository is MIT licensed, except for the ee
folders. See LICENSE and docs for more details.
GET API to export your data
GET routes to use data in downstream applications (e.g. embedded analytics). You can also access them conveniently via the SDKs (docs).
We take data security and privacy seriously. Please refer to our Security and Privacy page for more information.
By default, Langfuse automatically reports basic usage statistics of self-hosted instances to a centralized server (PostHog).
This helps us to:
- Understand how Langfuse is used and improve the most relevant features.
- Track overall usage for internal and external (e.g. fundraising) reporting.
None of the data is shared with third parties and does not include any sensitive information. We want to be super transparent about this and you can find the exact data we collect here.
You can opt-out by setting TELEMETRY_ENABLED=false
.
Open Source Projects Using Langfuse
Top open-source Python projects that use Langfuse, ranked by stars (Source):