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16 repository-uri

Awesome GitHub RepositoriesInfrastructure and Runtime Environments

Covers the underlying server-side execution environments, workspace containers, and deployment infrastructure for hosting agents.

Explore 16 awesome GitHub repositories matching artificial intelligence & ml · Infrastructure and Runtime Environments. Refine with filters or upvote what's useful.

Awesome Infrastructure and Runtime Environments GitHub Repositories

Găsește cele mai bune repo-uri cu AI.Vom căuta cele mai potrivite repository-uri folosind AI.
  • openclaw/openclawAvatar openclaw

    openclaw/openclaw

    380,031Vezi pe GitHub↗

    Openclaw este o platformă pentru gestionarea mediilor de execuție ale agenților, oferind infrastructura necesară pentru a controla ciclurile de viață ale agenților, starea sesiunii și persistența spațiului de lucru. Dispune de un gateway centralizat care gestionează buclele modelelor, invocarea instrumentelor și evenimentele de streaming, suportând în același timp rutarea multi-agent și gestionarea memoriei persistente. Sistemul este conceput pentru a normaliza semnăturile de execuție ale instrumentelor și pentru a oferi o interfață standardizată pentru compatibilitatea între furnizori. Platforma include instrumente extinse pentru dezvoltatori, cum ar fi o interfață de linie de comandă pentru gestionarea spațiului de lucru, logare de diagnosticare și o arhitectură de plugin-uri care permite înregistrarea de instrumente și capabilități personalizate. Suportă fluxuri de lucru automatizate prin hook-uri bazate pe evenimente, programarea sarcinilor și integrarea cu servicii externe. Securitatea este gestionată prin politici de execuție, portabilitatea acreditărilor și fluxuri de lucru de aprobare pentru acțiunile agenților. Implementarea este susținută prin instalatoare de infrastructură automatizate și ajutoare de gateway containerizate, cu utilitare încorporate pentru backup-uri și gestionarea configurației. Sistemul oferă un format structurat pentru orchestrarea fluxurilor de lucru în mai mulți pași și include instrumente specializate pentru automatizarea browserului și patch-uri de cod structurate.

    Allocates persistent directory structures to serve as long-term memory and file storage for agent operations.

    TypeScriptaiassistantcrustacean
    Vezi pe GitHub↗380,031
  • langchain-ai/langchainAvatar langchain-ai

    langchain-ai/langchain

    139,458Vezi pe GitHub↗

    LangChain is an orchestration framework designed for building, managing, and deploying applications powered by large language models. It provides a unified integration layer that normalizes disparate model provider APIs into a consistent set of primitives, enabling developers to build complex, multi-step AI workflows that manage state, memory, and tool execution. The project distinguishes itself through a durable execution runtime that maintains persistent state across long-running processes by checkpointing progress to external storage. It models agent workflows as directed graphs, allowing

    Offers standardized endpoints for provisioning, configuring, and monitoring the operational lifecycle of assistant instances.

    Pythonagentsaiai-agents
    Vezi pe GitHub↗139,458
  • opendevin/opendevinAvatar OpenDevin

    OpenDevin/OpenDevin

    77,460Vezi pe GitHub↗

    OpenDevin is an autonomous software engineering agent and orchestrator designed to execute coding tasks and manage development workflows using large language models. It functions as a centralized control center for managing and switching between various local and cloud artificial intelligence backends. The system utilizes a Docker sandbox environment to isolate autonomous agents in containers, protecting the host filesystem during code execution. It includes an automated engineering workflow tool that integrates with version control and chat services to trigger tasks via webhooks or scheduled

    Ships a centralized server to host and coordinate multiple autonomous agents on a single instance.

    Python
    Vezi pe GitHub↗77,460
  • paperclipai/paperclipAvatar paperclipai

    paperclipai/paperclip

    70,619Vezi pe GitHub↗

    Paperclip is an LLM agent orchestration platform and governance suite designed to coordinate teams of autonomous AI agents. It provides a management plane for defining organizational hierarchies, assigning roles, and aligning individual agent tasks with a structured mission tree to ensure work maps to business objectives. The project distinguishes itself through a specialized agent skill registry and workspace manager. It allows for the discovery and injection of reusable workflows into agent runtimes without retraining and provides isolated, sandboxed execution environments with persistent s

    Provides home directories for agents to store and access local files during execution.

    TypeScript
    Vezi pe GitHub↗70,619
  • shareai-lab/learn-claude-codeAvatar shareAI-lab

    shareAI-lab/learn-claude-code

    67,975Vezi pe GitHub↗

    This project provides a modular framework for building and orchestrating autonomous AI agents. It functions as an agentic workflow engine that manages the full lifecycle of task execution, including model reasoning, tool invocation, and the integration of results. By utilizing a centralized orchestration platform, the system enables the creation of multi-agent teams that collaborate on complex objectives through structured communication and shared task graphs. The framework distinguishes itself through its focus on persistent, stateful operations and multi-agent coordination. It employs file-

    Provides separate filesystem directories for parallel agents to prevent file conflicts and resource interference.

    Pythonagentagent-developmentai-agent
    Vezi pe GitHub↗67,975
  • mastra-ai/mastraAvatar mastra-ai

    mastra-ai/mastra

    21,221Vezi pe GitHub↗

    Mastra is an orchestration framework designed for building, deploying, and managing autonomous AI agents and multi-agent systems. It provides a comprehensive suite of primitives for creating resilient AI applications, including durable workflow orchestration, event-driven agent loops, and semantic memory management. By integrating these core components, the platform enables developers to build complex, multi-step processes that can reason about goals and execute tasks without manual intervention. The framework distinguishes itself through its focus on observability and secure, isolated execut

    Provides programmatic access to agent capabilities through server-based APIs for external application interaction.

    TypeScriptagentsaichatbots
    Vezi pe GitHub↗21,221
  • pydantic/pydantic-aiAvatar pydantic

    pydantic/pydantic-ai

    17,791Vezi pe GitHub↗

    PydanticAI is a Python framework designed for building production-grade autonomous agents. It provides a unified interface for interacting with diverse language models, enabling developers to construct agents that perform complex tasks through structured data validation, tool execution, and multi-turn conversation management. The library centers on type-safe schema enforcement, ensuring that model inputs and outputs remain consistent and reliable throughout the agent's lifecycle. The framework distinguishes itself through a robust architecture that emphasizes modularity and testability. It ut

    Wraps agent logic in network applications to enable communication with other systems via standardized protocols.

    Pythonagent-frameworkgenaillm
    Vezi pe GitHub↗17,791
  • camel-ai/camelAvatar camel-ai

    camel-ai/camel

    17,253Vezi pe GitHub↗

    This project is a comprehensive framework for building and managing autonomous agent systems. It provides a unified architecture for orchestrating multi-agent societies, where specialized agents collaborate through roleplay to decompose and solve complex tasks. The system integrates language models with external environments, enabling agents to perform real-world actions through a standardized tool-calling abstraction layer. The framework distinguishes itself through its focus on iterative reasoning and data reliability. It employs automated feedback loops to refine agent outputs and self-eva

    Wraps agent instances as network-accessible services for integration with external systems.

    Pythonagentai-societiesartificial-intelligence
    Vezi pe GitHub↗17,253
  • kilo-org/kilocodeAvatar Kilo-Org

    Kilo-Org/kilocode

    15,616Vezi pe GitHub↗

    Kilocode is an autonomous engineering platform designed to orchestrate AI agents for complex software development tasks. It functions as a comprehensive system for automating coding, testing, and repository management by integrating directly with your codebase and terminal. The platform provides a unified gateway for model orchestration, allowing for the management of agentic workflows, event-driven automation, and persistent session state across distributed development environments. The platform distinguishes itself through its federated task management and policy-based access control, which

    Adds custom workspace creation flows to the environment, enabling the agent to manage non-standard project structures.

    TypeScriptaiai-ageai-coding
    Vezi pe GitHub↗15,616
  • lsdefine/genericagentAvatar lsdefine

    lsdefine/GenericAgent

    13,017Vezi pe GitHub↗

    GenericAgent is an LLM agent framework and autonomous system controller designed to manage local systems, web browsers, and hardware interfaces through action and observation loops. It functions as a tool orchestrator that routes model calls to local executors, enabling the automation of complex tasks on a host machine. The project is distinguished by its self-evolving AI agent capabilities, which convert successful execution paths into reusable procedural scripts and skill trees to reduce future reasoning overhead. It employs a context optimization engine that utilizes layered memory hierarc

    Spawns child agents with dedicated isolated workspaces to execute parallel sub-tasks.

    Pythonai-agentautomationautonomous-agent
    Vezi pe GitHub↗13,017
  • yaoapp/yaoAvatar YaoApp

    YaoApp/yao

    7,544Vezi pe GitHub↗

    Yao is an LLM agent framework and low-code web app builder designed for orchestrating autonomous AI agents. It provides a platform to design, deploy, and coordinate agents with specialized personas that can plan tasks, utilize external tools, and execute multi-stage pipelines. The project distinguishes itself through a Model Context Protocol server for connecting assistants to external binaries and HTTP services, and a gRPC remote execution engine that allows agents to manage remote servers and devices. It includes a model-agnostic provider bridge that supports dynamic switching between vario

    Maintains long-running AI agent sessions in isolated containers that persist across inactivity.

    Goagentagentic-aiagents
    Vezi pe GitHub↗7,544
  • openai/openai-cs-agents-demoAvatar openai

    openai/openai-cs-agents-demo

    6,410Vezi pe GitHub↗

    This is a demonstration project from OpenAI that showcases a multi-agent customer service workflow built with the OpenAI Agents SDK. It coordinates several specialized AI agents to handle common airline support tasks such as flight booking and cancellation, refunds and compensation, seat and special service requests, real-time flight information, and airline policy FAQ responses, all within a single conversational interface. The system routes incoming customer requests to the appropriate specialized agent based on intent, and enforces guardrails to block off-topic or malicious requests. It su

    Provides a real, resumable file system and execution environment for each agent to safely handle coding or document tasks.

    Python
    Vezi pe GitHub↗6,410
  • siteboon/claudecodeuiAvatar siteboon

    siteboon/claudecodeui

    6,350Vezi pe GitHub↗

    Claudecodeui is an open-source web interface that orchestrates multiple AI coding agents from different providers—including Claude Code, Cursor CLI, Codex, and Gemini CLI—side by side in isolated cloud environments. It functions as a multi-provider orchestration platform, allowing users to run agents from different tools within the same workspace without being locked into a single vendor. The platform runs each agent session inside a hypervisor-level Docker sandbox that isolates filesystem, network, and process access, with sessions persisting in the cloud to survive network disconnection or

    Keeping AI agent sessions running in isolated cloud containers that survive laptop closure, network loss, or sleep.

    JavaScriptanthropicanthropic-aianthropic-claude
    Vezi pe GitHub↗6,350
  • voltagent/voltagentAvatar VoltAgent

    VoltAgent/voltagent

    6,020Vezi pe GitHub↗

    Gives each agent a persistent filesystem, sandbox execution, search, and skills available across conversations.

    TypeScriptagentsaiai-agents
    Vezi pe GitHub↗6,020
  • nicocha30/ligolo-ngAvatar nicocha30

    nicocha30/ligolo-ng

    4,289Vezi pe GitHub↗

    Ligolo-ng is a network tunneling framework and control server designed for managing remote agents and coordinating network routing. It functions as a reverse tunneling proxy and a site-to-site VPN tool, utilizing a userland TUN interface to pivot network traffic through remote agents. The project distinguishes itself by using a TUN interface routing system to forward TCP, UDP, and ICMP traffic through multiple remote agents. It implements a C2 model where a central server manages remote agents to bypass firewall restrictions and provide direct subnet access to isolated networks. The system c

    Provides a central control server that manages remote agents, handles tunnels, and provides automatic recovery from network failures.

    Gogolangoffensive-securitypentest-tool
    Vezi pe GitHub↗4,289
  • i-am-bee/beeai-frameworkAvatar i-am-bee

    i-am-bee/beeai-framework

    3,304Vezi pe GitHub↗

    The BeeAI Framework is an LLM agent framework and multi-agent orchestration engine used to build autonomous agents that coordinate reasoning, tool execution, and complex workflows. It functions as a structured AI output controller and RAG integration library, providing a unified interface to manage multiple language model providers. The framework is distinguished by its implementation of the Model Context Protocol, allowing agents, tools, and models to be shared between different AI platforms and hosted as agentic tooling servers. It enables the design of collaborative agent teams through dec

    Hosts agents and their capabilities as servers to expose them to external clients and platforms.

    Pythonagentsaiai-agent
    Vezi pe GitHub↗3,304
  1. Home
  2. Artificial Intelligence & ML
  3. Agentic Systems Frameworks
  4. Integration and Deployment
  5. Infrastructure and Runtime Environments

Explorează sub-etichetele

  • Agent Servers2 sub-tag-uriRuntime environments and APIs designed for hosting, managing, and configuring the execution of agent-based applications.
  • Agent Workspace Environments1 sub-tagPersistent directory structures that provide agents with a dedicated workspace for file access and long-term memory storage.