5 repository-uri
Mechanisms for making specific files accessible to multiple agents within a shared environment.
Distinct from File Sharing Management: Shortlist candidates focus on P2P or network file sharing, whereas this is about shared context for AI agents.
Explore 5 awesome GitHub repositories matching data & databases · Agent Shared Storage. Refine with filters or upvote what's useful.
Open Multi-Agent is a TypeScript framework for multi-agent orchestration that decomposes natural language goals into a runtime-generated directed acyclic graph of tasks. It functions as a task orchestrator and workflow state manager, coordinating multiple AI models to execute parallel and sequential operations. The framework is distinguished by a proposer-judge consensus protocol used to validate agent outputs through a quorum of agreement. It employs provider-agnostic model routing to assign specific models to tasks based on roles or execution phases and utilizes state-based workflow checkpo
Maintains a namespaced key-value store allowing multiple agents to share findings during execution.
AIOS is an LLM agent operating system and orchestration kernel designed to manage memory, resource scheduling, and tool execution for multiple autonomous AI agents. It serves as a comprehensive framework for developing and deploying agents, featuring a dedicated resource manager that coordinates model backends, GPU memory, and isolated kernel instances. The system distinguishes itself through a semantic memory engine that uses vector search and autonomous clustering for long-term knowledge management, and a semantic file system that allows users to control computer files and system operations
Makes specific files accessible within a shared environment for collaborative use by multiple agents.
Agency Swarm is a multi-agent orchestration framework and development kit designed to coordinate specialized AI agents through defined communication patterns and handoffs. It functions as a system for managing agent swarms, providing an API gateway to expose these coordinated collectives as production-ready HTTP endpoints. The project distinguishes itself through its Model Context Protocol integration layer, which connects agents to external data sources and capabilities. It implements specialized orchestration patterns, such as the orchestrator-worker model and role-based delegation, to tran
Maintains a centralized data store to share objects and session data between agents.
Acest proiect este un framework pentru dezvoltarea și orchestrarea agenților software autonomi în cadrul aplicațiilor bazate pe JVM. Oferă un toolkit pentru încorporarea inteligenței artificiale direct în logica de business, permițând agenților să execute sarcini complexe prin planificare dinamică, orientată spre obiective, în loc de mașini de stare rigide. Prin utilizarea adnotărilor declarative, framework-ul permite dezvoltatorilor să definească capabilitățile agenților și să îi integreze în modelele de domeniu orientate pe obiecte existente. Framework-ul se distinge printr-un strat de abstractizare neutru față de furnizor, care permite schimbarea fără probleme a modelelor de limbaj locale și cloud la runtime. Suportă colaborarea distribuită, permițând agenților independenți să partajeze informații și să delege sarcini între diferite servicii. Pentru a asigura vizibilitatea în luarea deciziilor autonome, sistemul include instrumente cuprinzătoare care captează urme de execuție, metrici de performanță și log-uri de operațiuni, care pot fi exportate către platforme de monitorizare externe. Dincolo de orchestrarea de bază, platforma include o suită de instrumente pentru gestionarea ciclurilor de viață ale agenților, inclusiv descoperirea automată a abilităților, validarea și bootstrapping-ul mediului. Dispune de o interfață bazată pe terminal pentru chat interactiv și execuția sarcinilor, alături de primitive de securitate care impun limite de acces pentru operațiunile sistemului de fișiere. Framework-ul menține, de asemenea, un repository de memorie centralizat pentru a oferi context partajat între procesele agenților distribuiți.
Maintains a centralized memory repository for shared context across distributed agent processes.
Craft Agents is an open-source desktop application that serves as a unified hub for managing multiple AI agents and their providers from a single interface. It connects to services including Anthropic, Google AI Studio, ChatGPT Plus, and GitHub Copilot, while also supporting any OpenAI-compatible endpoint, with the ability to set per-workspace provider defaults for each session. The application operates on a client-server architecture that decouples the agent runtime into a remote server process and a thin desktop client, enabling sessions to persist across machines. It includes a WebSocket-b
Shares documents between different AI agents within a unified desktop workspace.