VectraSDK – Open source, provider-agnostic RAG pipeline for production AI

Summary: VectraSDK is a modular, end-to-end retrieval-augmented generation (RAG) pipeline SDK that supports ingestion, chunking, embeddings, vector storage, retrieval, reranking, memory, and generation. It is provider-agnostic, enabling seamless switching between LLMs, embedding models, and vector databases across Python and Node without code changes.

What it does

VectraSDK orchestrates the full RAG workflow with built-in observability and evaluation, allowing advanced retrieval strategies like Hybrid search, HyDE, and LLM-based reranking. It provides production-ready components for ingestion, vector storage, retrieval, and generation in a single SDK.

Who it's for

It targets AI teams and developers building production AI applications who need flexible, maintainable RAG infrastructure without vendor lock-in or complex integration.

Why it matters

VectraSDK solves the challenges of provider lock-in, pipeline complexity, and lack of transparency in RAG systems, enabling faster iteration and easier experimentation with different models and vector databases.