Built a RAG library that doesn't assume you have a GPU

Every RAG library I tried had the same problem: reranking needed

torch + CUDA, which meant a 2GB+ dependency even if all you wanted

was CPU inference on a small server.

So I built ragleap-rag around a 23MB ONNX quantized reranker instead.

No GPU required, no massive install.

It grew from there into a fuller RAG toolkit:

- 6 vector backends (pgvector, FAISS, Pinecone, Weaviate, Qdrant, Milvus)

- 8 embedding providers, 12+ generation providers with automatic fallback

- Real per-call cost tracking with monthly budgets and auto-downgrade

- 238 tests, CI on every PR

It's fully open source: pip install ragleap-rag

I'm a solo dev building this alongside a commercial SaaS platform, so

it's genuinely a side project - built because I needed it, not to sell

anything. Would love feedback, especially from anyone who's hit the

same GPU-dependency wall.