RAG-system and RAG-Simplified
Both tools are competitors, as they are independent RAG systems, each with their own implementations for document retrieval and LLM answering, targeting similar use cases of enhancing LLM outputs with retrieved context.
Maintenance
2/25
Adoption
4/25
Maturity
9/25
Community
15/25
Maintenance
0/25
Adoption
4/25
Maturity
9/25
Community
14/25
Stars: 8
Forks: 4
Downloads: —
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stars: 5
Forks: 3
Downloads: —
Commits (30d): 0
Language: Python
License: MIT
Stale 6m
No Package
No Dependents
Stale 6m
No Package
No Dependents
About RAG-system
xumozhu/RAG-system
Retrieval-Augmented Generation system: ask a question, retrieve relevant documents, and generate precise answers. RAG demo: document retrieval + LLM answering
About RAG-Simplified
ShahMitul-GenAI/RAG-Simplified
Enhance GPT-3.5-Turbo output using Retrieval-Augmented Generation (RAG) with a user-friendly interface. Select between Wikipedia or integrate external documents to experience precise, context-aware responses.
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