Code & Development · GitHub ·600 ★

RAG-Driven-Generative-AI

This repository provides programs to build Retrieval Augmented Generation (RAG) code for Generative AI with LlamaIndex, Deep Lake, and Pinecone leveraging the power of OpenAI and Hugging Face models for generation and evaluation.

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Details

Author
Denis2054
Category
Code & Development
Platform
GitHub
Framework
llamaindex
Language
jupyter notebook
Stars
600
First indexed
2026-05-15
Last active
2025-09-23
Directory sync
2026-05-15
@Denis2054

Overview

This repository provides programs to build Retrieval Augmented Generation (RAG) code for Generative AI with LlamaIndex, Deep Lake, and Pinecone leveraging the power of OpenAI and Hugging Face models for generation and evaluation.

Quick start

git

git clone https://github.com/Denis2054/RAG-Driven-Generative-AI

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

What RAG-Driven-Generative-AI can do

hrapifine-tunragembedding
  • Hr — Handles people operations such as hiring and policy Q&A.
  • Api — api task automation.
  • Fine Tun — fine-tun task automation.
  • Rag — Retrieves grounded context before answering.
  • Embedding — Computes vector embeddings for semantic search.

Frequently asked questions

What is RAG-Driven-Generative-AI?
This repository provides programs to build Retrieval Augmented Generation (RAG) code for Generative AI with LlamaIndex, Deep Lake, and Pinecone leveraging the power of OpenAI and Hugging Face models for generation and evaluation.
How do I install RAG-Driven-Generative-AI?
Use git: `git clone https://github.com/Denis2054/RAG-Driven-Generative-AI`. Full setup details on the source page linked above.
Is RAG-Driven-Generative-AI open source?
RAG-Driven-Generative-AI is published on GitHub.
What are alternatives to RAG-Driven-Generative-AI?
Comparable agents include everything-claude-code, system-prompts-and-models-of-ai-tools, claude-code. Browse the full MeshKore directory to find more by category, framework, or language.

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Source & freshness

Profile data for RAG-Driven-Generative-AI is sourced from GitHub, published by Denis2054.

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