A hybrid retrieval system for RAG that combines vector search and graph search, integrating unstructured and structured data. It retrieves context using embeddings and a knowledge graph, then passes it to an LLM for generating accurate responses.
📚 AI-powered research reading workbench. Project-based paper Q&A with Hybrid RAG, multi-agent workflows (ReAct/Plan-Act/RePlan), long-term memory, and traceable evidence. Built with LangChain + LangGraph + Streamlit.
Graph RAG workshop using Kùzu and LanceDB for hybrid RAG
🧠 Stop building AI that forgets. Master MCP (Model Context Protocol) with production-ready semantic memory, hybrid RAG, and the WARNERCO Schematica teaching app. FastMCP + LangGraph + Vector/Graph stores. Your AI assistant's long-term memory starts here.
BestRAG: A library for hybrid RAG, combining dense, sparse, and late interaction methods for efficient document storage and search.
Code from the ODSC Agentic Graph RAG workshop combining vector, FTS & graph retrieval for RAG. Includes observability and guardrails for evaluating outputs.
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.
Kash is a Go CLI that turns your raw documents (PDFs, Markdown, text files) into a self-contained AI agent packaged in a lightweight Docker container.
A fast, modern, and privacy-focused PDF toolkit that runs entirely in your browser. No uploads, no servers, no tracking — your files never leave your device.
Multi-agent marketing automation system using Azure OpenAI, RAG pipelines, and structured experimentation workflows.
🚀 HAG: Next-Gen AI | Neo4j + Weaviate Fusion | Dual-Similarity Retrieval | 100% Local & Private | Graph Intelligence Meets Vector Search
Agent Workflow Has Personality
Build autonomous AI workflows with multi-agent orchestration, intelligent routing, hybrid RAG, knowledge graphs, MCP tools, persistent memory, and human-in-the-loop execution.
A Bible chatbot powered by Retrieval-Augmented Generation (RAG), designed to uphold fidelity to original language texts while delivering precise, citable references.
PromptWeaver: RAG Edition helps design effective prompts for Traditional, Hybrid, and Agentic RAG systems. It offers templates, system prompts, and best practices to improve accuracy, context use, and LLM reasoning.
A Visual and Interactive tool to learn and explore Hybrid RAG (Vector + Graph DBs) and Agentic RAG systems.
A practical cookbook of 10 Advanced RAG techniques — Naive, Hybrid, HyDE, Fusion, Parent-Child, RRR, Contextual Compression, and more. Working code + real benchmarks + plain-English explanations.
The retrieval stack matters — but ragweld’s differentiator is the engineering surface area around it: benchmarking, evaluation, diagnosis, and operations. It’s built for senior engineers who need answers like: what changed, why did it change, and what should we try next — without guessing.
Hybrid RAG system for translating Ancient Egyptian transliterations using the TLA dataset.
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