Open-source LLM migration and regression testing for AI agents. Compare models, detect tool-call regressions, and gate model changes in CI.
Migrate LLM apps between models safely — then benchmark old vs. new to prove the upgrade. Agent skill for behavior-preserving migrations + a runnable eval harness (three-arm leaderboard, prompt sweeps). Works in Claude Code, Codex & Cursor.
Plan, research, and evaluate LLM application migrations between models, providers, and platforms (Claude, GPT, Bedrock) before changing code
Evaluate Claude Sonnet model migrations with paired workload evidence, critical quality gates, normalized token costs, compatibility checks, and reversible rollout plans.
A beginner-friendly, hands-on learning path for AI backend development, covering the fundamentals of TypeScript and backend architecture, PostgreSQL and database design, Drizzle ORM and migrations, embeddings and vector databases with pgvector, vector similarity search, RAG pipelines, and the core concepts needed to build AI-powered backend systems
A verified production LLM model migration, and how its method evolved into ModelPromote: blind evaluation, human approval, read-back activation, telemetry verification and rollback. Runnable offline on synthetic data.
Govern the switch when you change the AI model in production: require approval, activate with read-back confirmation, verify from telemetry, and roll back to a locked target. Leaves one portable migration record. TypeScript, zero runtime dependencies.
GitHub Action for LLM migration and regression testing — runs your golden suite on every PR and fails the check on model regressions.
Open-source capture SDK for AI agents — records model and tool calls to build golden suites for LLM migration and regression testing.
To associate your repository with the llm-migration topic, visit your repo's landing page and select "manage topics."