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langchain-eval-harness
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skills/.curated/langchain-eval-harness/SKILL.md
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- Last checked
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- 2,916
- Repository last updated
- Nov 12, 2026
- License
- MIT
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- ai Repository topic
- automation Repository topic
- claude-code Repository topic
- devops Repository topic
- mcp Repository topic
- ai-agents Repository topic
- anthropic Repository topic
- claude-code-plugins Repository topic
- developer-tools Repository topic
- llm Repository topic
- saas Declared skill tag
- langchain Declared skill tag
- langgraph Declared skill tag
- python Declared skill tag
- langchain-1.0 Declared skill tag
- evaluation Declared skill tag
- langsmith Declared skill tag
- ragas Declared skill tag
- deepeval Declared skill tag
- research Declared skill tag
- research Derived category
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# LangChain Eval Harness (Python)
## Overview
A team swapped `gpt-4o` for `claude-sonnet-4-6` to save money and a week later CS
noticed answer quality dropped on 15% of refund tickets — the regression was
invisible in code review and invisible in CI because no golden set existed.
Fix: a versioned golden set, a stacked eval pipeline (LangSmith +
ragas + deepeval + custom trajectory), and a PR-blocking regression gate
with paired Wilcoxon significance. The tooling exists; the patterns for
wiring it into a statistically honest loop are scattered across five doc sites.
Build a 100-example JSONL golden set, wire LangSmith `evaluate()` with a
custom correctness evaluator, add a ragas quartet (faithfulness, answer