awesome-repositories.com
博客
MCP
awesome-repositories.com

通过 AI 驱动的搜索,发现最优秀的开源仓库。

探索精选搜索开源替代品自托管软件博客网站地图
项目MCP 服务器关于排名机制媒体报道
法律隐私政策服务条款
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
·

10 个仓库

Awesome GitHub RepositoriesAgent Development

Platforms and interfaces that enable users to build and customize AI agents with specific skills and operational capabilities.

Explore 10 awesome GitHub repositories matching artificial intelligence & ml · Agent Development. Refine with filters or upvote what's useful.

Awesome Agent Development 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。
  • lobehub/lobehublobehub 的头像

    lobehub/lobehub

    78,736在 GitHub 上查看↗

    LobeHub is a comprehensive multi-agent orchestration platform designed for building, configuring, and deploying specialized AI agents. It provides a unified chat-based gateway that allows users to manage autonomous agent teams across web, desktop, and mobile environments. By utilizing a framework that supports persistent memory and granular tool integration, the platform enables the execution of complex, multi-step workflows and domain-specific tasks. The platform distinguishes itself through an interactive artifact renderer that injects dynamic, visual UI elements directly into the chat stre

    Exposes intuitive interfaces for defining agent skills and connecting external tools to handle domain-specific requirements.

    TypeScriptagentagent-collaborationagent-harness
    在 GitHub 上查看↗78,736
  • agentscope-ai/agentscopeagentscope-ai 的头像

    agentscope-ai/agentscope

    26,895在 GitHub 上查看↗

    Agentscope is a comprehensive toolkit for developing and orchestrating autonomous multi-agent systems. It provides a unified framework for building agents that can reason, execute tools, and manage memory, enabling the creation of complex, collaborative workflows where multiple specialized agents interact to solve multi-step objectives. The platform distinguishes itself through a robust orchestration engine that supports both sequential and concurrent agent pipelines. It utilizes a centralized event bus for real-time telemetry, allowing developers to track agent reasoning, tool usage, and sys

    Allows developers to define specialized agent behaviors by extending base classes with custom logic.

    Pythonagentchatbotlarge-language-models
    在 GitHub 上查看↗26,895
  • pydantic/pydantic-aipydantic 的头像

    pydantic/pydantic-ai

    17,791在 GitHub 上查看↗

    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

    Allows wrapping agents to inject custom pre-processing, post-processing, and context management logic.

    Pythonagent-frameworkgenaillm
    在 GitHub 上查看↗17,791
  • nirdiamant/agents-towards-productionNirDiamant 的头像

    NirDiamant/agents-towards-production

    17,375在 GitHub 上查看↗

    This project is a comprehensive framework for developing, orchestrating, and deploying autonomous agents. It provides a structured environment for building agents that utilize reasoning loops to perform multi-step tasks, manage state through graph-based workflows, and interact with external tools. By mapping unstructured model outputs into typed schemas, the framework ensures reliable integration with downstream application logic. The platform distinguishes itself through a focus on production-grade reliability and security. It incorporates hybrid memory systems that combine vector embeddings

    Provides native framework integrations to rapidly build and deploy data-gathering agents.

    Jupyter Notebookagentagent-frameworkagents
    在 GitHub 上查看↗17,375
  • botpress/botpressbotpress 的头像

    botpress/botpress

    14,748在 GitHub 上查看↗

    Botpress is a conversational AI builder and LLM agent platform used to design chatbot workflows and orchestrate agents powered by large language models. It provides a framework for managing the entire lifecycle of these agents, from initial creation through to deployment across various production environments. The platform includes a custom integration SDK for developing and publishing third-party connectors that extend agent capabilities. These tools allow for the creation of custom plugins that connect AI agents to external APIs and third-party services. The system supports both visual des

    Provides a platform for building and deploying automated AI agents using large language models.

    TypeScript
    在 GitHub 上查看↗14,748
  • eigent-ai/eigenteigent-ai 的头像

    eigent-ai/eigent

    12,557在 GitHub 上查看↗

    Eigent is a comprehensive platform for developing, configuring, and orchestrating autonomous AI agents. It functions as an agent development environment and workflow automation engine, enabling users to build modular agents equipped with custom toolsets, domain-specific skill packages, and external API connections to perform targeted operational tasks. The framework distinguishes itself through a robust multi-agent orchestration layer that coordinates teams of specialized agents to execute complex workflows. By utilizing hierarchical task decomposition, the system breaks high-level goals into

    Offers a modular environment for building and customizing autonomous agents with specific skills and operational capabilities.

    TypeScript
    在 GitHub 上查看↗12,557
  • google/dopaminegoogle 的头像

    google/dopamine

    10,879在 GitHub 上查看↗

    Dopamine is a reinforcement learning research framework designed for prototyping and testing algorithms across diverse simulated environments. It provides an agent development toolkit that utilizes a flat class hierarchy to facilitate the creation and extension of learning agents. The framework includes a standardization layer via environment wrappers that connect agents to various physics simulations and gaming environments. It also features a high-performance experience replay buffer for storing and sampling transition data to improve training stability, alongside a dedicated hyperparameter

    Provides platforms and interfaces to build and customize reinforcement learning agents through subclassing.

    Jupyter Notebook
    在 GitHub 上查看↗10,879
  • microsoft/ufomicrosoft 的头像

    microsoft/UFO

    9,017在 GitHub 上查看↗

    UFO is a multi-device task orchestrator and LLM agent orchestration framework designed to decompose natural language requests into executable task graphs. It functions as a cross-platform UI automation tool capable of performing interactions on Windows and mobile devices while routing tasks to distributed agents based on their hardware and software capabilities. The system is distinguished by its RAG-enhanced agent architecture, which integrates external documentation and previous execution traces to improve decision-making. It employs a hybrid UI detection approach that combines computer vis

    Provides a template-driven toolkit for creating custom device agents with support for tool augmentation.

    Pythonagentautomationcopilot
    在 GitHub 上查看↗9,017
  • awslabs/agent-squadawslabs 的头像

    awslabs/agent-squad

    7,663在 GitHub 上查看↗

    Agent Squad is a multi-agent system orchestrator and language model agent orchestration framework. It serves as an AI workflow automation engine and tool integration layer designed to coordinate teams of specialized agents to solve complex tasks through routing, parallel execution, and state management. The project is distinguished by its ability to dynamically compose purpose-specific agents on-demand and route requests based on intent, language, or domain expertise. It supports advanced coordination patterns, including parallel subtask distribution, sequential task pipelines, and the abilit

    Provides platforms to build and customize AI agents with specialized logic for model interactions and API calls.

    Pythonagentic-aiagentsai-agents
    在 GitHub 上查看↗7,663
  • serpentai/serpentaiSerpentAI 的头像

    SerpentAI/SerpentAI

    6,979在 GitHub 上查看↗

    SerpentAI is a game AI development kit and computer vision framework designed for building autonomous agents that interact with video games. It serves as a game input automation tool and a machine learning model integration engine, allowing developers to create agents that perceive game states and execute actions. The framework utilizes a plugin-based agent architecture to provide modular extensions for game-specific logic and behaviors. It features a specialized system for training, bundling, and deploying machine learning classifiers to recognize visual contexts and game states in real time

    Provides a platform for creating specialized AI behaviors that determine how agents perceive and react to game environments.

    Pythonartificial-intelligencecomputer-visiondeep-learning
    在 GitHub 上查看↗6,979
  1. Home
  2. Artificial Intelligence & ML
  3. Agentic Systems Frameworks
  4. Integration and Deployment
  5. Agent Development

探索子标签

  • Custom Agent BuildersInterfaces for configuring agent skills and tool integrations.