awesome-rag-production
View on GitHubA curated list of battle-tested tools, frameworks, and best practices for building scalable, production-grade Retrieval-Augmented Generation (RAG) systems.
Curated production guide to RAG frameworks, data ingestion, embeddings, vector databases, retrieval, evaluation, observability, and deployment. Includes decision guides, reference architectures, benchmarks, and production case studies.
Use Cases
Choose production RAG frameworks and infrastructureBuild document ingestion and indexing pipelinesSelect embedding models and vector databasesImprove retrieval with reranking and query transformationEvaluate RAG quality and benchmark systemsMonitor, secure, and scale RAG deployments
Built With
- Language
- Python
- Frameworks
- LangChain · LangGraph · LlamaIndex · Haystack · RAGAS · Ollama · vLLM
Tags
RAG · production · embeddings · vector databases · retrieval · reranking · evaluation · observability · LLMOps · curated list