Search results for "neo4j"
The Context Optimization Layer for LLM Applications
PraisonAI 🦞 — Hire a 24/7 AI Workforce. Stop writing boilerplate and start shipping autonomous agents that research, plan, code, and execute tasks. Deployed in 5 lines of code with built-in memory, R
Universal memory layer for AI Agents. It provides scalable, extensible, and interoperable memory storage and retrieval to streamline AI agent state management for next-generation autonomous systems.
Harness LLMs with Multi-Agent Programming
AI-powered spec generation and review using multi-repo code graph intelligence for backend teams that ship to production.
An MCP server plus a CLI tool that indexes local code into a graph database to provide context to AI assistants.
Graph RAG with pure vector search, achieving SOTA performance in multi-hop reasoning scenarios.
Open security scanner for AI supply chain: agents, MCP, containers, cloud, GPU, and runtime with blast-radius analysis.
AgenticX is a unified, production-ready multi-agent platform — Python SDK + CLI (agx) + Studio server + Machi desktop app. Features Meta-Agent orchestration, 15+ LLM providers, MCP Hub, hierarchical m
Unified framework for building enterprise RAG pipelines with small, specialized models
🚀 2026 最系统的 AI Agent 速成指南｜智能体实战教程 · 完整学习路径 + 实战项目 + 面试题库 · 对标大模型应用开发工程师岗位 · 覆盖LangChain / LangGraph / Coze / Dify / MCP / skills / LLM / RAG / 提示词 · 企业级部署与微调 · 从0到企业级落地 + 从学习到上线项目 + 面试准备一体化
Memory that remembers the story not just the facts. Three layer sentence graph for AI agents -> Facts, Episodes, raw Sentences. One DB. Zero config.
META‑AGENTIC α‑AGI 👁️✨ — Mission 🎯 End‑to‑end: Identify 🔍 → Out‑Learn 📚 → Out‑Think 🧠 → Out‑Design 🎨 → Out‑Strategise ♟️ → Out‑Execute ⚡
Framework for AI agents to build and maintain an Obsidian wiki using Karpathy's LLM Wiki pattern
This project implements a comprehensive framework for Knowledge Graph Retrieval Augmented Generation (KG-RAG). It focuses on financial data from SEC 10-Q filings and explores how knowledge graphs can
Python LLM-RAG deep agent using LangChain, LangGraph and LangSmith built on Quart web microframework and served using Hypercorn ASGI and WSGI web server.
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