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The Memory Layer for AI Agents - Drop-in memory infrastructure for AI agents and apps. Context that persists. Built for production.
The open-source RAG platform: built-in citations, deep research, 22+ file formats, partitions, MCP server, and more.
$ git clone https://github.com/agentset-ai/agentset.gitThe Memory Layer for AI Agents - Drop-in memory infrastructure for AI agents and apps. Context that persists. Built for production.
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This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
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Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.
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🚀 EvoAgentX: Building a Self-Evolving Ecosystem of AI Agents
What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers?
50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
Data from GitHub · snapshot Nov 13, 2026