Structured RAG: ingest, index, query

Sample code that explores an architecture for using language models to build a personal agent that can work with application agents.

Luann (fka TypeAgent) allows you to create many LLM based agent(Various types of agent,scale up)

TypeAgent is an experimental opinionated library that makes it easy to build generative AI Agents using TypeScript definitions

TypeAgent 是一个基于大语言模型的智能体系统，由 NestJS 后端服务和 Next.js 前端界面组成，提供完整的多智能体协作和可视化交互能力。

Structured RAG: ingest, index, query

Demonstration of TypeAgent AMP (Agent Memory & Planning) on an incident-response email thread, showcasing Structured-RAG memory: intent distillation, action tracking, memory write-back, auditable history queries, memory-driven decisions, and entity/relationship extraction (people, roles, systems).

Art of the possible sample using TypeAgent, Brain-computer Interface (fNIRS BCI device), and Azure services

Guidoが作ったStructured RAG実装「typeagent_py」のテンプレート集

"Something Happened" app v2, built on TypeAgent and its Knowledge Processor

Port of the TypeAgent repository, exploring structuredRAG for a memory retrieval mechanism for Microsoft Graph