retrieval-augmented-generation

A Blazor Web App and Minimal API for performing RAG (Retrieval Augmented Generation) and vector search using the native VECTOR type in Azure SQL Database and Azure OpenAI.

Official code of the ACL 2025 paper "SimGRAG: Leveraging Similar Subgraphs for Knowledge Graphs Driven Retrieval-Augmented Generation"

Lightweight, In-memory, Semantic Search, Text Vector Database to embed in any .NET Application

Powerful web application that combines Streamlit, LangChain, and Pinecone to simplify document analysis. Powered by OpenAI's GPT-3, RAG enables dynamic, interactive document conversations, making it ideal for efficient document retrieval and summarization.

LitePali is a minimal, efficient implementation of ColPali for image retrieval and indexing, optimized for cloud deployment.

The best RAG interface yet.

Completely local RAG. Chat with your PDF documents (with open LLM) and UI to that uses LangChain, Streamlit, Ollama (Llama 3.1), Qdrant and advanced methods like reranking and semantic chunking.

Swift package for on-device Retrieval-Augmented Generation (RAG)

A complete collection of RAG interview questions, answers (548 questions & 41 RAG types), system design scenarios, architecture patterns, and production-ready concepts.

[ICLR 2026] Beyond a Million Tokens: Benchmarking and Enhancing Long-Term Memory in LLMs

Production-ready RAG Framework (Python/FastAPI). 1-line config swaps: 6 Vector DBs (Weaviate, Pinecone, Qdrant, ChromaDB, pgvector, MongoDB), 5 LLMs (Gemini, OpenAI, Claude, Ollama, OpenRouter). OpenAI-compatible API. 2100+ tests.

A collection of personally developed projects contributing towards the advancement of Artificial General Intelligence(AGI)

Advanced document extraction and chunking techniques for retrieval augmented generation that is aware of the layout of documents. Increases knowledge retrieval accuracy and provides control for retrieved knowledge context management

A Python CLI to test, benchmark, and find the best RAG chunking strategy for your Markdown documents.

Initiative to evaluate and rank the most popular LLMs across common task types based on their propensity to hallucinate.

A diverse, simple, and secure all-in-one LLMOps platform

Using LlamaIndex, Redis, and OpenAI to chat with PDF documents. Supplementary material for blog post on Microsoft Developer Blog

Research feedback grounded in the papers that define your field

An F/OSS solution combining AI with Wikipedia knowledge via a RAG pipeline

Official Implementation of LongLive-RAG: A general retrieval-augmented framework for long video generation.