retrieval-augmented-generation and Retrieval-Augmented-Generation-LLM-Demonstrator

retrieval-augmented-generation

Established

Retrieval-Augmented-Generation-LLM-Demonstrator

Emerging

Maintenance 10/25

Adoption 7/25

Maturity 16/25

Community 20/25

Maintenance 2/25

Adoption 4/25

Maturity 16/25

Community 13/25

Stars: 33

Forks: 24

Downloads: —

Commits (30d): 0

Language: Jupyter Notebook

License: Apache-2.0

Stars: 5

Forks: 2

Downloads: —

Commits (30d): 0

Language: Jupyter Notebook

License: MIT

No Package No Dependents

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-LLM-Demonstrator

Green-AI-Hub-Mittelstand/Retrieval-Augmented-Generation-LLM-Demonstrator

A vanilla from scratch Retrieval Augmented Generation (RAG) implementation that includes a web interface to control it.

Related comparisons

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

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