Confident AI
DeepEval-powered LLM evaluation platform to test, benchmark, and safeguard apps
Langfuse
Collaborative platform for building, monitoring, and debugging LLM applications.
Langfuse lets AI teams develop, observe, evaluate, and iterate on LLM apps with unified tracing, prompt versioning, evaluation pipelines, and a self‑hostable deployment in minutes.
Overview
Overview
Langfuse is a platform designed for AI product teams that need end‑to‑end visibility into their LLM applications. It captures traces of model calls, retrievals, embeddings, and agent actions, allowing developers to debug complex sessions and iterate quickly using an integrated playground.
Core Capabilities
Beyond observability, Langfuse offers centralized prompt management with version control and low‑latency caching, flexible evaluation frameworks that support LLM‑as‑judge, human feedback, and custom pipelines, and dataset handling for benchmark testing. Typed SDKs for Python and JavaScript/TypeScript, plus a comprehensive OpenAPI spec, let you embed Langfuse into bespoke LLMOps workflows.
Deployment Options
You can start with Langfuse Cloud’s free tier—no credit card required—or self‑host in minutes using Docker Compose. For production, Helm charts, Kubernetes, and Terraform templates are available for AWS, Azure, and GCP, giving you full control over data residency and compliance.
Highlights
Unified tracing of LLM calls, retrievals, embeddings, and agent actions
Prompt management with version control and low‑latency caching
Flexible evaluation pipelines supporting LLM‑as‑judge and human feedback
Multiple deployment paths: SaaS, Docker Compose, Helm, and Terraform
Pros
- Rich observability for complex LLM workflows
- Extensible SDKs for Python and JavaScript/TypeScript
- Self‑hosting can be done in minutes with Docker Compose
- Broad integration ecosystem (OpenAI, LangChain, LlamaIndex, etc.)
Considerations
- Production self‑hosting may require container or Kubernetes expertise
- Feature set can be overkill for simple single‑model projects
- Community support is primarily via GitHub Discussions, no formal SLA
- Enterprise‑grade monitoring may need additional tooling
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Fit guide
Great for
- AI product teams needing end‑to‑end debugging and evaluation
- Enterprises requiring on‑prem observability for LLM pipelines
- Developers building multi‑model or agent‑based applications
- Teams already using LangChain, LlamaIndex, or similar frameworks
Not ideal when
- Projects with only a static prompt and no monitoring needs
- Teams lacking container or Kubernetes expertise for production
- Use cases demanding real‑time latency guarantees beyond tracing
- Organizations that require 24/7 commercial support contracts
How teams use it
Debugging a multi‑step agent workflow
Trace each LLM call, retrieval, and tool use to pinpoint failures and iterate via the integrated playground.
A/B testing prompt versions
Manage prompt versions, collect user feedback, and run automated evaluations to select the highest‑performing prompt.
Continuous evaluation of model updates
Run custom evaluation pipelines on new model releases, compare metrics, and prevent regressions before deployment.
Self‑hosting LLM observability in a regulated environment
Deploy Langfuse on a private Kubernetes cluster, keeping all trace data on‑premise to meet compliance requirements.
Tech snapshot
TypeScript99%
JavaScript1%
Shell1%
Dockerfile1%
CSS1%
PLpgSQL1%
Frequently asked questions
How do I get started with self‑hosting?
Clone the repository and run `docker compose up` for a local instance; for production use the Helm chart or Terraform templates.
Which languages are supported for SDKs?
Official SDKs are available for Python and JavaScript/TypeScript.
Can Langfuse work with non‑OpenAI models?
Yes, integrations include Ollama, Amazon Bedrock, LiteLLM proxy, and any model accessible via the API.
Is there a free tier for the managed cloud service?
Langfuse Cloud offers a generous free tier with no credit‑card required.
How is data stored and secured in self‑hosted deployments?
Data resides in a PostgreSQL database; you control encryption, backups, and network access as part of your infrastructure.
Project at a glance
Active- Stars
- 20,867
- Watchers
- 20,867
- Forks
- 2,047
Repo age2 years old
Last commit18 hours ago
Self-hostingSupported
Primary languageTypeScript
Last synced 12 hours ago