Langchainjs Engineering Benchmarks
Langchainjs delivery benchmarks are based on 36 merged pull requests in the last 30 days (861 all-time), with 3.2 hours median cycle time, 0.1 hours median review time, and 11 active contributors. AI-related signals appear on 8.3% of recent work. PR volume is up 80% 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 |
|---|---|---|
| fix(core): build streaming llmOutput.tokenUsage from accumu… | thushanth-bengre-langchain | — |
| fix(google): allowlist JSON Schema keywords for Gemini sche… | thushanth-bengre-langchain | — |
| fix(deps): upgrade Vitest to address GHSA-82fw-gwwq-j7x9 | jkennedyvz | — |
| chore: exit prerelease | thushanth-bengre-langchain | — |
| revert(langchain): remove middleware trace policies (#11568) | thushanth-bengre-langchain | — |
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 16 minutes ago.
Updated daily from public GitHub pull requests.
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