BlueBash/RAG-Raptor-RE-Ranker-demo
The method of re-ranking involves a two-stage retrieval system, with re-rankers playing a crucial role in evaluating the relevance of each document to the query. RAG systems can be optimized to mitigate hallucinations and ensure dependable search outcomes by selecting the optimal reranking model.
No commits in the last 6 months.
Stars
5
Forks
1
Language
Python
License
—
Category
Last pushed
Jul 16, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/BlueBash/RAG-Raptor-RE-Ranker-demo"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
LongxingTan/open-retrievals
All-in-One: Text Embedding, Retrieval, Reranking and RAG in Transformers
axiom-llc/axiom-rag
Production RAG pipeline — grounded retrieval, source-cited answers, Precision@k + MRR eval. CLI...
ereztdev/RAGOps
AI powered troubleshooting for ground support equipment. Deterministic RAG pipeline that ingests...
AdnanSattar/Spatial-RAG
A production-ready full-stack system that combines semantic search with spatial proximity to...
KazKozDev/production-rag
Production-quality Retrieval-Augmented Generation with multi-strategy retrieval and...