retrieval-augmented-generation

Minimal local-first multimodal RAG library powered by SQLite + sqlite-vec.

RAG system with real-time news scraping built using mixtral-8x7b, ChromaDB, bart summarizer

A project combining roguelike with LLMs, RAG, Text2Speech, and Speech2Text

ChatGPT, embedding search, and retrieval-augmented generation for Squeak/Smalltalk

This is a RAG project to chat with your uploaded PDF , made using Langchain and Anthropic Claude 3 used as LLM , hosted using Streamlit

Evals framework for Information Retrieval Systems

This repository shares end-to-end scripts on how to use various Weaviate features and integrations!

Open-source, Python-first RAG platform with FastAPI APIs, LangGraph-native agents, pluggable vector stores (Qdrant/Weaviate/Milvus/pgvector/Elasticsearch), and multi-provider LLM support (OpenAI/Anthropic/Gemini/Ollama/vLLM).


HyDRA: Hybrid Dynamic RAG Agents, An advanced, agentic AI framework that transforms Retrieval-Augmented Generation from a static pipeline into a dynamic, learning reasoning system.

Perform RAG (Retrieval-Augmented Generation) from your PDFs using this Colab notebook! Powered by Llama 2

A Question Generation Application leveraging RAG and Weaviate vector store to be able to retrieve relative contexts and generate a more useful answer-aware questions

KONASH: Train knowledge agents that search, retrieve, and reason. Based on KARL (Databricks, 2026).

ESGenius: EMNLP 2025 Main Oral benchmark for LLM ESG and sustainability knowledge, with 1,136 questions, evaluation code, interactive heatmap, and Hugging Face dataset release.

A vector database for querying meaningfully similar data.

A rag application to chat with your documents with the help of gemini, pinecone and Next.js

Production-ready Retrieval Augmented Generation (RAG) system with hybrid retrieval, advanced evaluation metrics, and monitoring. Build enterprise LLM applications with reduced hallucinations, better context management, and comprehensive observability.

Explore cutting-edge Redis capabilities for Vector Similarity Search, Hybrid Search (Vector Similarity + Meta Search), Semantic Caching, and an advanced RAG model integrated with a Language Model (LLM) Chatbot. Unlock the full potential of Redis as a vector database with this comprehensive showcase of powerful features.

A Multi-Agent RAG platform using Vector DBs and AI models to accurately answer AML/CFT compliance queries.

This project implements RAG using OpenAI's embedding models and LangChain's Python library

Build sovereign RAG systems with MAS‑RAG, Dual‑RAG, GraphRAG, Spatial‑RAG, multimodal pipelines, and vector search directly inside Oracle AI Database 26ai and Exadata.