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26 个仓库

Awesome GitHub RepositoriesAI Agent Infrastructure

Back-end systems and registries that support the deployment, integration, and tracking of AI agents.

Explore 26 awesome GitHub repositories matching artificial intelligence & ml · AI Agent Infrastructure. Refine with filters or upvote what's useful.

Awesome AI Agent Infrastructure GitHub Repositories

用 AI 发现最棒的仓库。我们将通过 AI 为您搜索最匹配的仓库。
  • awesome-selfhosted/awesome-selfhostedawesome-selfhosted 的头像

    awesome-selfhosted/awesome-selfhosted

    299,516在 GitHub 上查看↗

    这是一个由社区策划的开源软件目录,专为在私有服务器环境和家庭实验室中部署而设计。它作为发现主流云服务独立自托管替代方案的综合资源,使用户能够保持对数字基础设施的完全数据所有权和控制权。 该目录通过层级分类法构建,将庞大的应用程序集合组织成逻辑类别,范围从媒体管理和数据分析到私有通信和团队生产力工具。它通过协作同行评审流程脱颖而出,社区成员验证每个提交的质量和相关性,以确保目录保持准确和可靠。 该项目涵盖了广泛的能力领域,包括基础设施自动化、基于容器的服务部署和声明式配置管理。这些工具协助用户维护可复现的服务器环境,并管理私有硬件上的复杂服务依赖。 该目录作为版本控制仓库进行维护,确保所有更新和社区驱动的变更都是可追踪且透明的。

    Provides an integrated environment for building and running AI applications with support for retrieval-augmented generation.

    awesomeawesome-listcloud
    在 GitHub 上查看↗299,516
  • anthropics/skillsanthropics 的头像

    anthropics/skills

    151,506在 GitHub 上查看↗

    This project provides a standardized framework for extending the functional range of artificial intelligence agents through a registry of modular, declarative instructions. It enables agentic workflow automation by allowing developers to define task-specific behaviors and operational constraints that guide how agents interact with external tools and execute multi-step processes. The system distinguishes itself through a directory-based discovery model and a plugin-registry architecture that facilitates the distribution of specialized workflows. By utilizing a schema-driven specification that

    Maintains a central directory of functional modules that agents can discover and utilize to perform specialized tasks.

    Pythonagent-skills
    在 GitHub 上查看↗151,506
  • x1xhlol/system-prompts-and-models-of-ai-toolsx1xhlol 的头像

    x1xhlol/system-prompts-and-models-of-ai-tools

    141,061在 GitHub 上查看↗

    This project is a community-driven knowledgebase and registry for AI agent configurations. It serves as a centralized repository for system prompts, environment settings, and integration strategies designed to standardize the behavior of various AI-assisted development tools. By capturing these configurations in a structured format, the project enables developers to maintain consistent AI agent performance across different workstations and environments. The repository distinguishes itself through a hierarchical, version-controlled architecture that treats prompt engineering patterns as portab

    Streamlines the management of task-tracking configurations and workflows for AI agents.

    aiboltcluely
    在 GitHub 上查看↗141,061
  • shubhamsaboo/awesome-llm-appsShubhamsaboo 的头像

    Shubhamsaboo/awesome-llm-apps

    114,725在 GitHub 上查看↗

    This repository serves as a comprehensive collection of resources, templates, and starter code for building artificial intelligence applications. It provides a centralized hub for developers to access practical implementations of common workflows, including retrieval-augmented generation pipelines and autonomous agent loops, alongside educational materials designed to support rapid prototyping and experimentation. The project distinguishes itself by offering a dual focus on technical implementation and critical analysis. It provides a library of lightweight, single-file agents and tutorials f

    Deployment guides assist in hosting and maintaining persistent, self-improving agents that operate continuously.

    Pythonagentsllmspython
    在 GitHub 上查看↗114,725
  • openhands/openhandsOpenHands 的头像

    OpenHands/OpenHands

    77,330在 GitHub 上查看↗

    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 enables agents to autonomously navigate codebases, implement features, and resolve issues through iterative reasoning and tool execution. The platform distinguishes itself through a model-agnostic orchestrator that connects diverse language models to a unified tool registry. It

    Connects agents to external databases and development tools using standardized protocols with configurable safety and approval policies.

    Pythonagentartificial-intelligencechatgpt
    在 GitHub 上查看↗77,330
  • datawhalechina/hello-agentsdatawhalechina 的头像

    datawhalechina/hello-agents

    59,685在 GitHub 上查看↗

    This project provides a comprehensive framework for building, training, and managing autonomous agents. It enables the construction of systems that utilize language models to plan, manage memory, and execute multi-step tasks through iterative reasoning loops and tool-based actions. The framework distinguishes itself by offering specialized capabilities for interacting with graphical user interfaces and legacy software, allowing agents to perceive visual elements and perform actions like a human user. It supports complex, cross-application workflows through graph-based orchestration and provid

    Provides a centralized registry for defining and distributing functional tools to autonomous agents.

    Pythonagentllmrag
    在 GitHub 上查看↗59,685
  • notifirehq/notifirenotifirehq 的头像

    notifirehq/notifire

    39,138在 GitHub 上查看↗

    Notifire is a multi-channel notification infrastructure designed to route and dispatch alerts across email, SMS, push, and chat providers through a unified interface. It functions as an agent communication gateway that normalizes inbound and outbound messages between chat platforms and AI agents for consistent data processing. The system includes a notification workflow engine that uses branching conditions and batching capabilities to design delivery sequences and reduce user fatigue. It also provides a pre-built notification center component, allowing web applications to embed a real-time i

    Routes user messages from various chat platforms to an AI agent and delivers the response back.

    TypeScript
    在 GitHub 上查看↗39,138
  • langchain-ai/deepagentslangchain-ai 的头像

    langchain-ai/deepagents

    25,006在 GitHub 上查看↗

    Deepagents is an LLM agent orchestration platform and stateful application server designed for deploying and managing AI agents built with computational graphs. It provides a containerized runtime environment that handles agent execution, state persistence, and the versioning of AI assistants. The platform distinguishes itself through deep integration with the Model Context Protocol, allowing agents to function as servers that expose tools and capabilities to external clients. It features a sophisticated observability suite for capturing execution traces, performing LLM-based evaluations agai

    Provides a containerized runtime and cloud environment for hosting AI graphs with integrated secrets and scaling.

    Pythonagentsdeepagentslangchain
    在 GitHub 上查看↗25,006
  • a2aproject/a2aa2aproject 的头像

    a2aproject/A2A

    24,404在 GitHub 上查看↗

    A2A is a standardized framework designed to enable interoperability, discovery, and orchestration among independent artificial intelligence agents. It provides a common communication protocol that allows heterogeneous agents to exchange data, verify identities, and collaborate across diverse programming languages and computing environments. By establishing a unified messaging standard, the project facilitates the creation of complex, multi-agent workflows where tasks are routed and managed between specialized services. The project distinguishes itself through a capability-based architecture t

    A discovery service that exposes agent capabilities, metadata, and service endpoints through standardized digital cards for automated service selection.

    Shella2aa2a-mcpa2a-protocol
    在 GitHub 上查看↗24,404
  • letta-ai/lettaletta-ai 的头像

    letta-ai/letta

    21,168在 GitHub 上查看↗

    Letta is a framework for building, deploying, and managing autonomous AI agents that maintain persistent state across long-term interactions. It provides a comprehensive suite of primitives for defining agents with configurable personas, modular memory blocks, and tool-use capabilities, enabling them to retain user preferences and conversation history over extended sessions. The platform distinguishes itself through its advanced memory management and orchestration capabilities. It allows agents to autonomously update their own memory, perform retrieval-augmented generation, and coordinate com

    Allows updating the configuration and definition of registered tools within the agent environment.

    Pythonaiai-agentsllm
    在 GitHub 上查看↗21,168
  • vercel-labs/agent-skillsvercel-labs 的头像

    vercel-labs/agent-skills

    20,764在 GitHub 上查看↗

    Agent Skills is a centralized registry and management system designed for the discovery, auditing, and integration of reusable procedural modules into automated agent workflows. It provides a structured environment for sourcing verified capabilities that extend the functional range of AI agents, enabling the development and scaling of complex, multi-step automated processes. The platform distinguishes itself through a security-first approach to module integration, utilizing audit-verified data to ensure that capabilities meet safety requirements before they are deployed. It incorporates a dec

    Provides a centralized registry for discovering, auditing, and integrating reusable procedural modules into automated agent workflows.

    JavaScript
    在 GitHub 上查看↗20,764
  • livekit/livekitlivekit 的头像

    livekit/livekit

    19,358在 GitHub 上查看↗

    LiveKit is a comprehensive framework for building and orchestrating real-time, multimodal AI agents that interact with users through voice, video, and text. It provides a centralized, event-driven architecture to manage the entire lifecycle of automated participants, from initialization and session state management to graceful shutdown. By utilizing a selective forwarding unit, the platform efficiently routes media streams between participants and agents, ensuring low-latency communication and secure, token-based authentication for all connections. The platform distinguishes itself through it

    Provides back-end systems and registries that support the deployment, integration, and tracking of AI agents.

    Gogolangmedia-serversfu
    在 GitHub 上查看↗19,358
  • camel-ai/camelcamel-ai 的头像

    camel-ai/camel

    17,253在 GitHub 上查看↗

    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

    Provides registries for searching and identifying available server tools to expand agent capabilities.

    Pythonagentai-societiesartificial-intelligence
    在 GitHub 上查看↗17,253
  • iofficeai/aionuiiOfficeAI 的头像

    iOfficeAI/AionUi

    16,621在 GitHub 上查看↗

    AionUi is an AI agent orchestration platform designed to manage and coordinate multiple autonomous assistants within a local environment. It functions as a framework for executing background processes and scheduled tasks that operate independently of the user interface, ensuring that automated workflows continue to run without manual oversight. The platform distinguishes itself through a local-first approach to document generation and file manipulation, allowing users to create and modify office files directly on their hardware to maintain data privacy. It supports parallel agent execution, e

    Provides a unified integration layer for connecting multiple agents to a shared set of functional tools.

    TypeScriptacpaiai-agent
    在 GitHub 上查看↗16,621
  • optuna/optunaoptuna 的头像

    optuna/optuna

    14,388在 GitHub 上查看↗

    Optuna is a Python-based hyperparameter optimization framework designed to automate the search for optimal machine learning model configurations. It functions as a Bayesian optimization library that systematically tests parameter combinations to maximize or minimize objective functions, streamlining the model development process through iterative evaluation. The project distinguishes itself through a define-by-run dynamic construction model, which allows users to build complex, conditional search spaces using standard programming logic. Its architecture is highly modular, featuring a pluggabl

    Enables sharing custom optimization packages with the broader community.

    Pythondistributedhyperparameter-optimizationmachine-learning
    在 GitHub 上查看↗14,388
  • hkuds/openharnessHKUDS 的头像

    HKUDS/OpenHarness

    14,084在 GitHub 上查看↗

    OpenHarness is a framework for building and orchestrating AI agents that utilize tools and plugins to execute complex tasks. It provides an orchestration system for managing language model lifecycles and a multi-agent coordination system for delegating workloads across teams of specialized subagents. The project features an agent gateway that bridges language model agents to external chat platforms and communication channels. It includes a tool integration engine for executing shell, file, and web operations, supported by a memory and skill manager that handles persistent user preferences and

    Ships a gateway that routes messages between external communication platforms and AI agents.

    Python
    在 GitHub 上查看↗14,084
  • google/skillsgoogle 的头像

    google/skills

    13,815在 GitHub 上查看↗

    This project is an AI agent integration layer and skill library that connects large language models to external APIs and developer technologies. It functions as a cloud infrastructure automation framework, providing a standardized interface for managing compute, storage, and database resources through automated agent interactions. The system utilizes a skill registry to extend agent capabilities, allowing intelligent agents to interact with cloud platforms and productivity tools. It provides a resource management interface to execute configuration updates and implement standardized security p

    Provides the middleware layer that connects autonomous agents to external APIs and databases.

    Python
    在 GitHub 上查看↗13,815
  • diet103/claude-code-infrastructure-showcasediet103 的头像

    diet103/claude-code-infrastructure-showcase

    9,707在 GitHub 上查看↗

    This project is a collection of patterns and configurations for deploying AI agents with specialized technical skills and personas. It provides a framework for agentic software engineering, defining standards for AI-driven development workflows and the management of modular technical capabilities. The system features a skill framework that activates technical guidelines based on prompt intent and a context management system that preserves project state using persistent plans and checklists across session resets. It employs a modular organization of guidelines to prevent context window overflo

    Showcases patterns and configurations for deploying AI agents with specialized technical skills and personas.

    Shell
    在 GitHub 上查看↗9,707
  • hatchet-dev/hatchethatchet-dev 的头像

    hatchet-dev/hatchet

    6,622在 GitHub 上查看↗

    Hatchet is an open-source durable workflow engine and task orchestration platform. It provides a framework for building and executing fault-tolerant, multi-step pipelines as directed acyclic graphs (DAGs), with automatic retries, scheduling, and real-time observability. The system is built around durable task checkpointing, which persists execution state after each step so work can resume from the last checkpoint after a worker crash or restart, and it supports event-driven task resumption that pauses a task until a matching external event arrives. The platform distinguishes itself through it

    Generates provider-specific tool definitions from Hatchet workflow or task definitions for use with an agent SDK.

    Goconcurrencydagdistributed
    在 GitHub 上查看↗6,622
  • brainblend-ai/atomic-agentsBrainBlend-AI 的头像

    BrainBlend-AI/atomic-agents

    5,688在 GitHub 上查看↗

    Provides a registry of prebuilt tools conforming to a shared schema interface for agent composition.

    Pythonaiartificial-intelligencelarge-language-model
    在 GitHub 上查看↗5,688
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  1. Home
  2. Artificial Intelligence & ML
  3. Agentic Systems Frameworks
  4. Development and Runtime Environments
  5. AI Agent Infrastructure

探索子标签

  • AI Tool Integration LayersMiddleware for connecting autonomous agents to external APIs and databases with safety and approval policies.
  • Agent Capability Registries1 个子标签Structured databases or catalogs for managing and discovering agent-specific functional modules.
  • Agent Deployment GuidesDocumentation and tutorials for hosting and maintaining persistent AI agent runtimes.
  • Communication GatewaysInfrastructure for routing messages between communication platforms and AI agents. **Distinct from AI Agent Infrastructure:** Focuses on the transport and routing layer between users and agents rather than general agent deployment.
  • Issue Tracking for AI AgentsMechanisms for logging, tracking, and managing tasks or bugs specifically within AI agent workflows.
  • Shared Tool Registries1 个子标签Centralized registries for distributing functional tools across multiple AI agents. **Distinct from AI Agent Infrastructure:** Distinct from general infrastructure: focuses on the registry of shared functional tools for agents.