Overview
Research summary
LangSmith combines application tracing, production monitoring, datasets, human feedback and automated evaluation for LLM applications and agents. Developers can inspect nested calls, compare experiments and track model usage, latency and quality. The platform supports applications built with LangChain or independent frameworks, including OpenTelemetry integrations.
Managed cloud, bring-your-own-cloud and self-hosted deployment options are offered commercially. The linked repository contains MIT-licensed client SDKs rather than the complete platform, so its language and licence describe those integration packages. LangSmith is distinct from the open-source LangChain and LangGraph libraries even though they integrate closely.
Repository summary
- Stars
- Unavailable
- Open issues
- Unavailable
- Last push
- Unavailable
- Commits, 90 days
- Unavailable
- Repository activity
- Not scored
- Version
- Unavailable
Recorded catalogue figures. View repository data and provenance →
Classification
Pricing & services
Paid services available
The provider offers paid products or services. Free options may also be available.
Commercial offering checked 2026-10-02.
Licence scope
The linked repository contains client SDKs, not the platform implementation.
Implementation
Recorded implementation details and interfaces for LangSmith.
Implementation details
Commercial observability/evaluation platform with Python and JavaScript/TypeScript client SDKs.
- Languages
- Python, TypeScript (SDKs)
- Repository type
- integration
Recorded interfaces and capabilities
Licence scope
The linked repository contains client SDKs, not the platform implementation.
Repository
Repository snapshots, release information and recorded maintenance signals.
Repository snapshot
- Stars
- Unavailable
- Open issues
- Unavailable
- Last push
- Unavailable
- Commits, 90 days
- Unavailable
- Repository activity
- Not scored
- Archived
- Not recorded
Repository activity is a snapshot, not a quality or popularity ranking. It combines recent-push freshness (50%), 90-day commits (30%) and issue pressure (20%).
Maintenance and provenance
- Catalogue snapshot
- 2026-10-06
Documentation
Recorded references and research provenance for this entry.
Recorded sources 9
- https://www.langchain.com/langsmith Project page · Research reference
- https://github.com/langchain-ai/langsmith-sdk Linked repository · Research reference
- https://www.langchain.com/community Research reference
- https://forum.langchain.com/c/help/langsmith/8 Research reference
- https://www.langchain.com/blog/regression-testing Research reference
- https://www.youtube.com/watch?v=xTMngs6JWNM Research reference
- https://www.youtube.com/oembed?url=https%3A%2F%2Fwww.youtube.com%2Fwatch%3Fv%3DxTMngs6JWNM&format=json Research reference
- https://www.langchain.com/langsmith/observability Commercial offering evidence
- https://www.langchain.com/pricing Commercial offering evidence
Research metadata
- Research date
- 2026-10-01
- Catalogue snapshot
- 2026-10-06
Community & social 2 channels
Video
- YouTubeLangChain — includes LangSmith walkthroughsOfficialLearningDemos
Link details for YouTube — LangChain — includes LangSmith walkthroughs
- Last checked
Communities
- DiscourseLangSmith observability and evaluation supportOfficialDiscussionSupportFeedback
Link details for Discourse — LangSmith observability and evaluation support
- Access
- Public
- Status
- Active
- Last checked
Related tools
Editorially linked entries to explore alongside LangSmith. This is not a ranking.
