A

ai-testing

LangChain.js e2e testing best practices in TypeScript: deterministic FakeChatModel tests, structured-output validation, and an eval harness

AI-assisted QA automation project that reads real SRS/BRS documents (TXT, PDF, DOCX), automatically generates baseline test cases, and analyzes bug data to identify defect patterns and risk-prone areas.

This project focuses on reducing manual QA effort while keeping human QA judgment and refinement in the loop.