retrieval-augmented-generation and Retrieval-Augmented-Generation

retrieval-augmented-generation
53
Established
Retrieval-Augmented-Generation
33
Emerging
Maintenance 10/25
Adoption 7/25
Maturity 16/25
Community 20/25
Maintenance 2/25
Adoption 5/25
Maturity 7/25
Community 19/25
Stars: 33
Forks: 24
Downloads: —
Commits (30d): 0
Language: Jupyter Notebook
License: Apache-2.0
Stars: 12
Forks: 18
Downloads: —
Commits (30d): 0
Language: Python
License: —
No Package No Dependents
No License Stale 6m No Package No Dependents

About retrieval-augmented-generation

VectorInstitute/retrieval-augmented-generation

Reference Implementations for the RAG bootcamp

This collection provides examples for building applications that can answer questions using up-to-date or private information, going beyond what a large language model was originally trained on. You input a question and relevant external data (like documents, web pages, or database records), and it outputs an accurate, specific answer. It's designed for developers, data scientists, and AI engineers looking to create smart assistants or search tools.

AI development natural language processing information retrieval question answering data integration

About Retrieval-Augmented-Generation

ThomasJanssen-tech/Retrieval-Augmented-Generation

Build a RAG (Retrieval Augmented Generation) app in 10 minutes!

This tool helps you quickly build a custom question-answering system using your own documents. You feed it your text files, and it creates a smart chatbot that can answer questions based only on the information you provided. This is ideal for anyone needing to create a focused, knowledgeable AI assistant without extensive programming.

custom-chatbot document-qa knowledge-base-search information-retrieval internal-knowledge

Related comparisons

retrieval-augmented-generation and RAG-Overview retrieval-augmented-generation and Retrieval-Augmented-Generation-LLM-Demonstrator retrieval-augmented-generation and RAG-Playground retrieval-augmented-generation and RAG

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