jawwad-ali/self-healing-rag
Self-healing RAG pipeline with drift detection and auto-remediation. Built on n8n + Neon Postgres + OpenAI.
SUMMARY AI summary by gpt-5-mini
Self‑Healing RAG Pipeline is an operational Retrieval‑Augmented Generation system that continuously monitors and repairs itself. Intended for AI/ML infrastructure teams and engineers running production RAG, it detects quality regressions, document edits, and embedding drift; re‑embeds or patches affected chunks; grades answers with a separate judge model; and A/B‑tests fixes before promotion. Key features: n8n workflows as schedulers/agents, Neon Postgres + pgvector as the single datastore, OpenAI for chat/embeddings and Anthropic Claude for grading, three watcher types (quality eval, doc‑change detector, drift detector), canary A/B testing of repairs, operator dashboard, and a full audit trail in Postgres. No Python runtime required; all logic runs inside n8n.
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Owner
Full-Stack Software Engineer | AI & scalable web apps | Open-source contributor | Portfolio: https://ali-jawwad.vercel.app | Karachi, Pakistan 🇵🇰
Dates
| Created on GitHub | 2026-05-09 |
| Last push | 2026-05-09 |
| First seen here | 2026-05-09 |
| Last fetched | 2026-05-09 18:11 |
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