Langchainjs Engineering Benchmarks
Langchainjs delivery benchmarks are based on 41 merged pull requests in the last 30 days (937 all-time), with 3.7 hours median cycle time, 0.2 hours median review time, and 16 active contributors. AI-related signals appear on 9.8% of recent work. PR volume is down -18% compared to the prior period.
Repo vs LangChain Average
Delivery Trend and AI Signals
PR Backlog (Humans)
Excludes AI agents and automation accounts.
PR Backlog (AI Agents)
AI coding agents only.
Cycle Time by AI-Related Signals
PR Breakdown
Top AI Tools
PR Type Breakdown
Recent Pull Requests
View PR Explorer| Title | Author | AI |
|---|---|---|
| chore(core): fill in client versions in tool-call-delta cha… | richardscarrott | — |
| feat(core,openai,anthropic,aws,xai): stream tool-call args … | richardscarrott | — |
| test(core): accept either order of a chunk's stream events … | richardscarrott | AI |
| chore(deps): restore missing `@modelcontextprotocol/core@2.… | richardscarrott | AI |
| fix(langchain): deliver final answers after todo updates | hntrl | — |
Methodology
Metrics are computed from merged pull request data synced daily from GitHub. AI-related metrics are directional signals inferred from pull request activity patterns and heuristics. Summary metrics use a 30-day rolling window; trends use a 90-day window. Last updated 2 hours, 46 minutes ago.
Updated daily from public GitHub pull requests.
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