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Langtrace vs Ragas

LangtraceRagas

Bottom line: Langtrace for lLM app developers; Ragas for teams evaluating RAG pipelines.

	Langtrace Open-source, OpenTelemetry-based observability for LLM applications Visit	Ragas Open-source evaluation toolkit for RAG and LLM applications. Visit
Votes	0	0
Pricing	Freemium	Free
Category	Llm Observability	Llm Observability
Tags	llm-observabilityopentelemetrytracingevaluationsopen-source	ragllm-evaluationopen-sourcetestingmetrics
Best for	LLM app developers RAG engineers Platform teams	Teams evaluating RAG pipelines Developers adding eval to CI/CD RAG researchers and practitioners
Pros	Fully open source and self-hostable Built on the OpenTelemetry standard Traces export to any observability stack Supports Python and TypeScript Covers models, frameworks, and vector DBs	Focused, research-backed RAG metrics Free and open source Reduces need for manual labeling via LLM scoring Synthetic test-set generation Broadened to LLM and agent evaluation
Cons	Smaller ecosystem than larger competitors Fewer turnkey enterprise features Evaluations can require manual effort Requires OpenTelemetry familiarity for advanced setups Managed cloud is less mature than incumbents	LLM-as-a-judge scores need validation Mainly a library; you build dashboards/infra Judge model choice affects reliability and cost Python-only Less turnkey than managed eval platforms

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