open-retrievals and RAG_END_TO_END
Maintenance
2/25
Adoption
9/25
Maturity
25/25
Community
17/25
Maintenance
10/25
Adoption
0/25
Maturity
11/25
Community
0/25
Stars: 74
Forks: 13
Downloads: —
Commits (30d): 0
Language: Python
License: Apache-2.0
Stars: —
Forks: —
Downloads: —
Commits (30d): 0
Language: Python
License: MIT
Stale 6m
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About open-retrievals
LongxingTan/open-retrievals
All-in-One: Text Embedding, Retrieval, Reranking and RAG in Transformers
This project helps anyone working with large collections of text documents to find the most relevant information efficiently. You input your documents and a search query, and it outputs the best matching documents, ranked by relevance. It's designed for professionals who need to build advanced search or question-answering systems.
information-retrieval
document-search
question-answering
knowledge-management
text-analytics
About RAG_END_TO_END
sailaxmitumu2000/RAG_END_TO_END
Production Retrieval-Augmented Generation (RAG) system with FastAPI, async ingestion, embeddings, vector search, and grounded LLM responses.
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