This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
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A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.
- agentic-ai
- agentic-rag
- agents
- rag
MongoDB's Generative AI Showcase: an exhaustive collection of examples and sample applications covering Retrieval-Augmented Generation (RAG), AI agents, and industry-specific use cases.
Generative AI reference workflows optimized for accelerated infrastructure and microservice architecture.
- gpu-acceleration
- large-language-models
- llm
- llm-inference
Everything you need to know to build your own RAG application
- agentic-rag
- chatbot
- llm
- machine-learning
Convert any text to a graph of knowledge. This can be used for Graph Augmented Generation or Knowledge Graph based QnA
Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, interview preparation, and coding preparation.
This repository contains various advanced techniques for Retrieval-Augmented Generation (RAG) systems.
- ai
- chromadb
- cookbooks
- faiss
Objectron is a dataset of short, object-centric video clips. In addition, the videos also contain AR session metadata including camera poses, sparse point-clouds and planes. In each video, the camera moves around and above the object and captures it from different views. Each object is annotated with a 3D bounding box. The 3D bounding box describes the object’s position, orientation, and dimensions. The dataset contains about 15K annotated video clips and 4M annotated images in the following categories: bikes, books, bottles, cameras, cereal boxes, chairs, cups, laptops, and shoes
WFGY is heading toward WFGY 5.0 Polaris Protocol, a major open-source release for AI reasoning, RAG, agents, and real-world workflows. Includes Problem Map, Global Debug Card, WFGY 4.0, and the CFV Easter Egg.
This repository provides an advanced Retrieval-Augmented Generation (RAG) solution for complex question answering. It uses sophisticated graph based algorithm to handle the tasks.
Comprehensive guide to learn RAG from basics to advanced.
- ai-engineer
- generative-ai
- large-language-models
- llm-engineer
Official Implementation of "KBLaM: Knowledge Base augmented Language Model"