Open Source RAG Stack: A Complete Architecture from Ingestion to Frontend

goyalshaliniuk · x · 2026-08-25

This post outlines a comprehensive open-source RAG stack designed to transform raw data into context-rich, production-ready AI applications.

Core Components:

• Ingest & Processing: Pipelines built with Kubeflow, Airflow, Nifi, LangChain loaders, and Haystack.
• Retrieval & Ranking: Elasticsearch, Weaviate, FAISS for fetching data, enhanced by JinaAI rerankers.
• Embedding Models: Vector generation via HuggingFace Transformers, Sentence Transformers, JinaAI, and others.
• Vector Databases: Scalable storage with Milvus, Weaviate, PgVector, Chroma, and Qdrant.
• LLM Frameworks & Models: Orchestration via LangChain, Haystack, CrewAI, and LlamaIndex, powered by LLaMA, Mistral, Phi-2, DeepSeek, Qwen, and Gemma.
• Frontend: Interactive interfaces using NextJS, Streamlit, VueJS, and SvelteKit.

Original post →

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