rag-all-techniques and RAG-for-LLMs-demo
Maintenance
2/25
Adoption
10/25
Maturity
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Adoption
1/25
Maturity
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Community
12/25
Stars: 453
Forks: 114
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Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stars: 1
Forks: 1
Downloads: —
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stale 6m
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Stale 6m
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No Dependents
About rag-all-techniques
liu673/rag-all-techniques
Implementation of all RAG techniques in a simpler way(以简单的方式实现所有 RAG 技术)
This project provides practical, framework-agnostic implementations of various advanced Retrieval Augmented Generation (RAG) techniques. It takes unstructured text data, applies different methods for breaking it down and enriching it, and then uses a large language model to generate improved, contextually relevant answers to user queries. This is for AI practitioners, researchers, or anyone building custom question-answering systems who wants to understand and experiment with core RAG components.
AI-powered question-answering
information retrieval
natural language processing
text analytics
knowledge management
About RAG-for-LLMs-demo
gcerar/RAG-for-LLMs-demo
RAG for LLMs demo
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