Langfuse traces every LLM call, tool use and cost in your application, with prompt management and evaluation built in — self-hostable.
| Category | LLM / RAG framework |
| Type | LLM observability |
| License | MIT |
| Runs locally | Yes |
| Built with | TypeScript |
| Skill level | Intermediate |
| Best for | debugging and monitoring LLM apps in production |
Other open-source llm / rag framework tools worth comparing:
LangChainCompose chains, tools and agents
LlamaIndexThe data framework for RAG
HaystackProduction pipelines for search and RAG
DSPyProgram — not prompt — language models
txtaiAll-in-one embeddings database
RAGFlowDeep-document-understanding RAG
Semantic KernelMicrosoft's enterprise agent framework
GraphRAGRAG that builds a knowledge graph first
LiteLLMOne API for 100+ LLM providers
InstructorReliable structured outputs from LLMs
OutlinesGuarantee valid JSON and grammars
GuidanceInterleave control and generation
LLMWareEnterprise RAG with small specialised models
FlashRankUltra-light reranking for better RAG
Sentence TransformersThe standard way to make embeddings
RagasMeasure whether your RAG is any good
PromptfooUnit tests for your prompts
PhoenixTrace, evaluate and debug LLM appsLangfuse is free and open-source (MIT license), so you can use, self-host and modify it at no cost.
Yes. Langfuse is designed to run on your own machine or server, keeping your data private.
Popular open-source alternatives include LangChain, LlamaIndex, Haystack. See the comparisons above to choose.
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