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Agent Runtimes · Awesome GitHub Repositories

8 repos

Awesome GitHub RepositoriesAgent Runtimes

Backend environments that manage the execution loop, tool invocation, prompt processing, and lifecycle of autonomous agents.

Explore 8 awesome GitHub repositories matching artificial intelligence & ml · Agent Runtimes. Refine with filters or upvote what's useful.

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  3. Agentic Systems Frameworks
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Awesome Agent Runtimes GitHub Repositories

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  • openclaw/openclaw

    openclaw/openclaw

    211,971GitHubView on GitHub↗

    Openclaw is a platform for managing agent execution environments, providing the infrastructure to control agent lifecycles, session state, and workspace persistence. It features a centralized gateway that handles model loops, tool invocation, and streaming events, while supporting multi-agent routing and persistent mem

    TypeScriptaiassistantcrustacean
  • Significant-Gravitas/AutoGPT

    Significant-Gravitas/AutoGPT

    181,891GitHubView on GitHub↗

    AutoGPT is an orchestration platform designed for building, managing, and deploying autonomous agents. It provides a visual canvas-based environment where users can assemble agents by connecting modular blocks that represent actions, data flows, and conditional logic. The platform supports the entire agent lifecycle, i

    Pythonaiartificial-intelligenceautonomous-agents
  • langchain-ai/langchain

    langchain-ai/langchain

    127,015GitHubView on 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 t

    Pythonagentsaiai-agents
  • google-gemini/gemini-cli

    google-gemini/gemini-cli

    94,954GitHubView on GitHub↗

    This project provides a command-line interface for managing autonomous agent workflows, task orchestration, and system-level automation. It includes a comprehensive framework for defining agent skills, managing persistent memory, and delegating tasks to specialized subagents. Users can configure complex planning modes,

    TypeScriptaiai-agentscli
  • browser-use/browser-use

    browser-use/browser-use

    78,576GitHubView on GitHub↗

    Browser-use is a framework for building autonomous agents that navigate, interact with, and extract data from web interfaces using natural language instructions. By acting as an orchestration layer between large language models and browser automation protocols, it enables the execution of complex, multi-step workflows

    Pythonai-agentsai-toolsbrowser-automation
  • OpenHands/OpenHands

    OpenHands/OpenHands

    67,974GitHubView on GitHub↗

    OpenHands is an autonomous agent framework designed for software engineering workflows. It provides a modular platform for orchestrating AI agents that reason, plan, and execute tasks within isolated, containerized development environments. By integrating with standard version control and development tools, the system

    Pythonagentartificial-intelligencechatgpt
  • cline/cline

    cline/cline

    58,164GitHubView on GitHub↗

    Cline is an extensible agent runtime and multi-agent orchestration engine designed to automate complex software engineering workflows. It functions as an integrated development environment extension that bridges strategic task planning with autonomous execution, allowing users to manage multi-step projects through huma

    TypeScript
  • microsoft/autogen

    microsoft/autogen

    54,656GitHubView on GitHub↗

    This framework provides a development environment for building collaborative systems where autonomous agents interact to solve complex tasks through conversational workflows. It functions as a conversational workflow engine and event-driven runtime, coordinating multi-step processes by translating high-level goals into

    Pythonagenticagentic-agiagents

Explore sub-tags

  • Agent Action RepresentationsStandardized formats for encoding agent decisions, tool usage, and reasoning steps.
  • Agent Execution Runtimes1 sub-tagCore engines that manage the serialized execution loop, state persistence, and tool orchestration for AI agents.
  • Agent Streaming InterfacesInterfaces for streaming tool events, assistant deltas, and lifecycle phases during agent execution.
Concurrency Managers
Mechanisms for serializing agent runs to prevent race conditions and manage concurrent execution.
  • EmbeddedRuntime environments that provide dedicated workspaces with injected persona and memory configurations for agents.
  • Event-Driven Agent RuntimesExecution environments that manage asynchronous message passing and state transitions for distributed agent architectures.
  • Execution HooksMechanisms for triggering custom logic during agent command lifecycles.
  • LLM-Driven Agent LoopsSystems that orchestrate iterative task execution by processing environmental context and generating actionable commands via language models.
  • Runtime Compatibility ContractsSpecifications defining the interface and lifecycle responsibilities between an agent runtime and its execution environment.
  • Session Management SystemsSystems that manage persistent state, history, and context for conversational or agent-based interactions.
  • Steering and Streaming ControlsRuntime capabilities for steering inbound prompts into active agent runs using message queuing.
  • Streaming Response ProcessorsComponents that parse, chunk, and sanitize real-time streaming output from LLMs into actionable directives.