rag-skills

What problem does it solve?

This Skill provides a curated set of RAG-focused best practices covering LlamaIndex usage, ChromaDB vector stores, and Celery workers. It targets reliability, performance, and maintainability of on-prem RAG pipelines.

Core Features & Use Cases

• Guidelines for ingestion, retrieval, embeddings, and task orchestration across Python stacks.
• Code-review checklists and architecture patterns to ensure consistency across components.
• Use Case: Audit and optimize a production RAG workflow by enforcing deterministic IDs, thread-safe access, and proper Celery routing.

Quick Start

Apply the rag-skills guidelines to your project by auditing your RAG components and implementing the recommended patterns.