DeepYard

Langfuse vs RAG Failure Diagnostics Clinic

Side-by-side comparison built from DeepYard's structured catalog. Content updated Aug 21, 2026.

Direct Answer

Langfuse suits teams needing freemium free tier, observability focus, and 33,539 GitHub stars in current listing data. RAG Failure Diagnostics Clinic suits teams needing open-source access, debugging focus, and 133,530 GitHub stars in current listing data. This summary reflects catalog metadata only for decision support, not independent testing.

What this comparison weighs

  • Pricing and free-tier availability
  • License model and deployment fit
  • GitHub adoption and contributor depth
  • Catalog tags, integrations, and supported workflows
L

Langfuse

Open-source LLM engineering platform — traces, evals, prompt management — 23K+ stars

OSSfreemium
33.5Ktoday196
R

RAG Failure Diagnostics Clinic

Diagnose and fix common RAG pipeline failure modes

OSSFree
133.5Ktoday95
MetricLangfuseRAG Failure Diagnostics Clinic
GitHub Stars33.5K133.5K
Contributors19695
Last CommitAug 22, 2026Aug 22, 2026
Open Issues81114
Licenseopen-sourceopen-source
Pricingfreemiumopen-source
Free TierYesYes
Categorydev-toolsdev-tools
TrendingNoNo

Choose Langfuse if you need

  • Langfuse stands out for Observability workflows that are not listed for RAG Failure Diagnostics Clinic.
  • Langfuse is the stronger pick when Langchain matters because that capability is listed only on its profile.
  • Langfuse has a larger visible contributor base (196 vs 95).

Choose RAG Failure Diagnostics Clinic if you need

  • RAG Failure Diagnostics Clinic stands out for Debugging workflows that are not listed for Langfuse.
  • RAG Failure Diagnostics Clinic is the stronger pick when Any Rag Pipeline matters because that capability is listed only on its profile.
  • RAG Failure Diagnostics Clinic shows broader GitHub adoption with 133,530 stars versus 33,539 for Langfuse.

Meaningful differences

  • Pricing model: Langfuse is listed as freemium, while RAG Failure Diagnostics Clinic is listed as open-source.
  • Workflow emphasis: Langfuse highlights Observability, while RAG Failure Diagnostics Clinic highlights Debugging.
  • GitHub adoption: Langfuse shows 33,539 stars versus 133,530 for RAG Failure Diagnostics Clinic.
  • Contributor count: Langfuse lists 196 contributors and RAG Failure Diagnostics Clinic lists 95.

Shared capabilities

  • Evaluation

Shared Tags

evaluation

Only in Langfuse

observabilitytracingprompt-managementanalyticsopen-source

Only in RAG Failure Diagnostics Clinic

ragdebuggingdiagnosticspython

Limitations and evidence

  • DeepYard compares structured public metadata; this is not an independent benchmark unless a test record is shown.
  • Signals such as stars, contributors, and last commit indicate public activity, not purchase fit or runtime quality.
  • Pricing and feature coverage reflect the stored listing snapshot and may lag vendor changes between refreshes.

About Langfuse

Langfuse is an open-source LLM engineering platform providing observability, analytics, and prompt management. Features distributed tracing for complex agent chains, evaluation scoring, prompt versioning and A/B testing, dataset management, and cost tracking. Integrates with LangChain, LlamaIndex, OpenAI SDK, and any LLM framework via OpenTelemetry.

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About RAG Failure Diagnostics Clinic

A diagnostic tool that identifies why RAG pipelines produce poor results. It tests for common failure modes: irrelevant retrieval, missing context, hallucination over context, chunking issues, and embedding quality problems. Provides a structured report with specific fix recommendations for each detected issue. Essential for debugging production RAG systems. Part of the awesome-llm-apps collection.

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