retrieval-augmented-generation

An offline CPU-first low-resource chat application to perform RAG on your corpus of data. Powered by OpenChat and CTranslate2.

A curated list of awesome Pinecone resources, libraries, tools and applications

Recurrence Meets Transformers for Universal Multimodal Retrieval

Chat with your documents using Generative AI & Retrieval-Augmented Generation (RAG)

using mulimodal RAG to query texts, images and tables from pdf for QA

A repository of curated use cases, articles, blogs, videos on how companies are using Artificial Intelligence and Machine Learning.

Kairos: An autonomous development supervisor powered by Context Engineering. It provides a living memory and a contextual constitution for your projects to prevent AI context loss.

Tool for auto-generating README documentation for code repositories

LoRA supervised fine-tuning, RLHF (PPO) and RAG with llama-3-8B on the TLDR summarization dataset

Your medical AI assistant - chat with your docs, get cited answers. RAG-powered with Gemini & Pinecone.

Elixir RAG library with multi-LLM routing (Gemini, Claude, OpenAI, Ollama), GraphRAG, knowledge graphs, modular retrievers/rerankers, composable pipelines, pgvector integration, advanced chunking, and tool-using agents. Fork of bitcrowd/rag.

AI powered legal research engine. The system is based on multi AI agentic RAG systems leveraging the power of Llama3 LLM

Easily create semantic search based LLM applications

Implementation of Retrieval Augmented Generation model in typescript with Gemini LLM

The data layer for AI with Vector, Graph and Vector-Math built into one single rust engine

🧠 Multimodal Retrieval-Augmented Generation that "weaves" together text and images seamlessly. 🪡

In this end to end project I have built a RAG app using ObjectBox Vector Databse and LangChain. With Objectbox you can do OnDevice AI, without the data ever needing to leave the device.

An AI-powered search engine to interact with documentation using RAG and local LLMs. Privately deployable with vector search and a modern frontend.

FloatChat AI is a conversational AI platform for ARGO Ocean Data Discovery and Visualization, providing accurate and interactive tools to explore oceanographic data. Built with Python, LangChain, Pandas, and machine learning models, it makes complex ocean data accessible and actionable for researchers and enthusiasts.

Development and deployment on AWS of a question-answer LLM model using Llama2 with 7B parameters and RAG with LangChain