AI Infrastructure · GitHub ·1,111 ★

RAG-Retrieval

Unify Efficient Fine-tuning of RAG Retrieval, including Embedding, ColBERT, ReRanker.

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Details

Author
NovaSearch-Team
Category
AI Infrastructure
Platform
GitHub
Framework
custom
Language
python
Stars
1,111
First indexed
2026-05-15
Last active
2025-07-05
Directory sync
2026-05-15
@NovaSearch-Team

Overview

Unify Efficient Fine-tuning of RAG Retrieval, including Embedding, ColBERT, ReRanker.

Quick start

git

git clone https://github.com/NovaSearch-Team/RAG-Retrieval

Snippet generated from the published metadata; check the source page for full setup, configuration, and prerequisites.

What RAG-Retrieval can do

ragllmembeddingfine-tun
  • Rag — Retrieves grounded context before answering.
  • Llm — llm task automation.
  • Embedding — Computes vector embeddings for semantic search.
  • Fine Tun — fine-tun task automation.

Frequently asked questions

What is RAG-Retrieval?
Unify Efficient Fine-tuning of RAG Retrieval, including Embedding, ColBERT, ReRanker.
How do I install RAG-Retrieval?
Use git: `git clone https://github.com/NovaSearch-Team/RAG-Retrieval`. Full setup details on the source page linked above.
Is RAG-Retrieval open source?
RAG-Retrieval is published on GitHub.
What are alternatives to RAG-Retrieval?
Comparable agents include awesome, openclaw, AutoGPT. Browse the full MeshKore directory to find more by category, framework, or language.

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Source & freshness

Profile data for RAG-Retrieval is sourced from GitHub, published by NovaSearch-Team.

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