awesome-repositories.com
Blog
MCP
awesome-repositories.com

Découvrez les meilleurs dépôts open-source grâce à notre recherche par IA.

ExplorerRecherches sélectionnéesAlternatives open sourceLogiciels auto-hébergésBlogPlan du site
ProjetServeur MCPÀ proposNotre méthodologiePresse
Mentions légalesConfidentialitéConditions d'utilisation
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
·

80 dépôts

Awesome GitHub RepositoriesAgentic Workflows

Frameworks for designing and executing autonomous agent processes through iterative refinement and state management.

Explore 80 awesome GitHub repositories matching artificial intelligence & ml · Agentic Workflows. Refine with filters or upvote what's useful.

Awesome Agentic Workflows GitHub Repositories

Trouvez les meilleurs dépôts grâce à l'IA.Nous recherchons les dépôts les plus pertinents grâce à l'IA.
  • microsoft/generative-ai-for-beginnersAvatar de microsoft

    microsoft/generative-ai-for-beginners

    112,045Voir sur GitHub↗

    This project is a comprehensive, open-source educational curriculum designed to guide developers through the mastery of generative artificial intelligence. It provides a structured learning path that covers foundational concepts, prompt engineering, and the practical application of large language models. The repository serves as a central hub for skill acquisition, offering sequential modules that progress from basic model mechanics to advanced architectural patterns. The curriculum distinguishes itself by focusing on the end-to-end lifecycle of intelligent software, including the implementat

    Instructs on the design and implementation of autonomous agent processes.

    Jupyter Notebookaiazurechatgpt
    Voir sur GitHub↗112,045
  • openhands/openhandsAvatar de OpenHands

    OpenHands/OpenHands

    77,330Voir sur 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 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

    Employs feedback loops where agents critique and refine outputs until reaching specific quality targets.

    Pythonagentartificial-intelligencechatgpt
    Voir sur GitHub↗77,330
  • foundationagents/metagptAvatar de FoundationAgents

    FoundationAgents/MetaGPT

    68,844Voir sur GitHub↗

    MetaGPT is an agentic workflow engine and multi-agent orchestration framework designed to automate complex software engineering and data analysis tasks. It functions as an automated software factory that transforms high-level natural language requirements into functional web applications, technical documentation, and production-ready code. By utilizing a runtime environment that manages the lifecycle of specialized agents, the platform bridges the gap between user intent and finished software components. The system distinguishes itself through role-based agent orchestration and dynamic task d

    Executes structured research workflows using automated teams to analyze market demand, competitor positioning, and product viability.

    Pythonagentgptllm
    Voir sur GitHub↗68,844
  • shareai-lab/learn-claude-codeAvatar de shareAI-lab

    shareAI-lab/learn-claude-code

    67,975Voir sur 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 isolated filesystem workspaces for parallel agent tasks using version control worktrees.

    Pythonagentagent-developmentai-agent
    Voir sur GitHub↗67,975
  • cline/clineAvatar de cline

    cline/cline

    63,750Voir sur 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 human-in-the-loop oversight or independent agent operation. The platform distinguishes itself by enabling the creation of specialized agent teams that share a common state and coordinate through a centralized task manager. It enforces project-specific architectural guidelines and co

    Manages iterative refinement and task delegation to execute autonomous development processes from start to finish.

    TypeScript
    Voir sur GitHub↗63,750
  • addyosmani/agent-skillsAvatar de addyosmani

    addyosmani/agent-skills

    60,849Voir sur GitHub↗

    Agent-skills is a collection of structured instructions and behavioral personas designed to standardize how AI coding agents perform engineering tasks. It functions as a workflow orchestrator that maps natural language intent to repeatable technical sequences and verification checklists. The project distinguishes itself through the use of specialized markdown-defined roles, such as security auditors or test engineers, to apply targeted domain expertise. It employs an evidence-based verification model that requires runtime data or passing tests as mandatory exit criteria to ensure AI-generated

    Provides frameworks for designing step-by-step actionable processes and verification checklists for autonomous agents.

    Shellagent-skillsantigravityantigravity-ide
    Voir sur GitHub↗60,849
  • yeachan-heo/oh-my-codexAvatar de Yeachan-Heo

    Yeachan-Heo/oh-my-codex

    30,984Voir sur GitHub↗

    oh-my-codex is an AI coding workflow orchestrator and a retrieval augmented generation documentation assistant. It manages complex programming tasks through a structured sequence of planning, execution, and verification phases, while providing tools for querying and translating technical documentation. The project utilizes Git worktrees to isolate parallel coding sessions, ensuring that concurrent tasks remain independent. It integrates a vector-store knowledge base to index documents into embeddings, enabling semantic search and factual context retrieval across multiple languages. The syste

    Utilizes Git worktrees to create isolated filesystem environments for concurrent AI coding sessions.

    TypeScript
    Voir sur GitHub↗30,984
  • openai/symphonyAvatar de openai

    openai/symphony

    25,622Voir sur GitHub↗

    Symphony is an agentic workflow manager and autonomous software implementation engine. It serves as an orchestrator for large language model coding agents, converting high-level project requirements and task board items into verified pull requests. The system manages an autonomous development workflow by delegating implementation runs to agents that handle end-to-end feature development and bug fixes. It generates automated pull requests backed by proof-of-work verification, ensuring that code contributions are validated before human review. The platform coordinates a cycle of planning, codi

    Serves as a coordination layer that manages the execution and verification of autonomous coding agents.

    Elixir
    Voir sur GitHub↗25,622
  • joonspk-research/generative_agentsAvatar de joonspk-research

    joonspk-research/generative_agents

    21,565Voir sur GitHub↗

    Generative Agents is a computational platform for simulating autonomous agents that exhibit human-like social behaviors and decision-making processes. The system functions as a multi-agent simulator where individual participants operate within a virtual environment, driven by large language models to process observations and generate natural language actions. The framework distinguishes itself through a hierarchical memory system that allows agents to store, retrieve, and synthesize past experiences into higher-level insights. This architecture supports the development of complex social dynam

    Assign unique backgrounds and personal narratives to agents at the start of a simulation to influence their subsequent behaviors, memories, and social interactions with other participants.

    Voir sur GitHub↗21,565
  • everyinc/compound-engineering-pluginAvatar de EveryInc

    EveryInc/compound-engineering-plugin

    21,527Voir sur GitHub↗

    This project is a suite of tools for autonomous engineering, featuring a workflow manager that chains ideation, planning, and implementation into a single automated process for delivering pull requests. It includes a technical implementation planner for codebase research and blueprint generation, along with a framework for agentic code review that uses specialized agents to identify security and architectural issues. The system provides utilities for AI coding assistant migration, including a plugin converter for transforming instructions between different IDEs and a configuration synchronize

    Uses version control worktrees to isolate code changes during autonomous implementation cycles.

    TypeScriptcompoundengineering
    Voir sur GitHub↗21,527
  • mastra-ai/mastraAvatar de mastra-ai

    mastra-ai/mastra

    21,221Voir sur 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

    Implements iterative feedback loops that allow agents to refine and improve their outputs based on validation criteria.

    TypeScriptagentsaichatbots
    Voir sur GitHub↗21,221
  • nikivdev/flowAvatar de nikivdev

    nikivdev/flow

    21,136Voir sur GitHub↗

    Flow is an orchestration framework for designing and executing complex workflows using autonomous agents powered by large language models. It serves as a toolkit for constructing agentic pipelines and a runtime for managing agent lifecycles, session states, and tool execution. The project is distinguished by its support for hierarchical swarm management, where director agents decompose large projects into smaller tasks for specialized worker agents. It enables multiple coordination patterns, including sequential linear pipelines and concurrent execution where agents analyze tasks from differe

    Provides a toolkit for constructing iterative agentic processes and pipelines with state management.

    Rustagentsautonomymoonbit
    Voir sur GitHub↗21,136
  • claude-code-best/claude-codeAvatar de claude-code-best

    claude-code-best/claude-code

    20,272Voir sur GitHub↗

    Claude Code is a command-line interface and multi-agent orchestration framework designed for autonomous software engineering. It enables AI agents to perform codebase modifications, debugging, and Git workflow management while coordinating multiple specialized agents to decompose and execute complex engineering tasks in parallel. The system distinguishes itself through a high degree of isolation and safety, utilizing Git worktrees to create independent working directories for concurrent agents and implementing a tiered permission system that combines user rules, project policies, and OS-level

    Prevents write conflicts by utilizing Git worktrees to maintain independent file states for parallel agent tasks.

    TypeScript
    Voir sur GitHub↗20,272
  • livekit/livekitAvatar de livekit

    livekit/livekit

    19,358Voir sur GitHub↗

    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

    Triggers the agent to speak a predefined message or generate a dynamic response to start or continue a conversation.

    Gogolangmedia-serversfu
    Voir sur GitHub↗19,358
  • qwenlm/qwen-codeAvatar de QwenLM

    QwenLM/qwen-code

    19,078Voir sur GitHub↗

    Qwen-code is an AI-powered development framework designed for orchestrating intelligent coding agents within terminal and IDE environments. It provides a comprehensive infrastructure for automating software maintenance, code generation, and complex refactoring tasks by managing multi-agent workflows and persistent session states. The system is built to handle both interactive development and automated background processes, ensuring that agents can execute shell commands and file operations safely within isolated, sandboxed environments. What distinguishes this project is its focus on granular

    Supports parallel execution of multiple agent instances by leveraging version control worktrees to maintain independent file states.

    TypeScript
    Voir sur GitHub↗19,078
  • eosphoros-ai/db-gptAvatar de eosphoros-ai

    eosphoros-ai/DB-GPT

    18,999Voir sur GitHub↗

    DB-GPT is an agentic data analysis platform and business intelligence AI that functions as a large language model data assistant. It provides a text-to-SQL interface and a sandboxed code execution environment to translate natural language into executable database queries and Python scripts. The platform utilizes iterative agentic reasoning to plan and execute multi-step data analysis workflows through tool calls. It features a modular skill-based extension system that allows domain knowledge and analysis workflows to be packaged into reusable functional components. The system integrates data

    Provides frameworks for designing autonomous agent processes to standardize complex data analysis workflows.

    Pythonagentsbgidatabase
    Voir sur GitHub↗18,999
  • camel-ai/camelAvatar de camel-ai

    camel-ai/camel

    17,253Voir sur 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

    Refines agent outputs through automated self-evaluation and multi-step verification loops.

    Pythonagentai-societiesartificial-intelligence
    Voir sur GitHub↗17,253
  • kilo-org/kilocodeAvatar de Kilo-Org

    Kilo-Org/kilocode

    15,616Voir sur 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

    Creates independent git worktrees for parallel tasks to allow agents to work on separate features without interference.

    TypeScriptaiai-ageai-coding
    Voir sur GitHub↗15,616
  • plandex-ai/plandexAvatar de plandex-ai

    plandex-ai/plandex

    15,001Voir sur GitHub↗

    Plandex is an AI-powered software development platform that operates as a command-line interface to manage complex, long-running coding tasks. It functions as an automated agent that decomposes high-level programming objectives into granular, actionable steps, executing multi-file code changes directly within a local project environment. The system distinguishes itself through a state-machine-based execution model that tracks progress across iterative development cycles. By utilizing context-aware code indexing and an iterative feedback loop, the tool refines generated code through successive

    Refines generated code through successive cycles of execution, validation, and correction based on feedback.

    Goaiai-agentsai-developer-tools
    Voir sur GitHub↗15,001
  • shangtongzhang/reinforcement-learning-an-introductionAvatar de ShangtongZhang

    ShangtongZhang/reinforcement-learning-an-introduction

    14,569Voir sur GitHub↗

    This project is a Python-based educational framework designed to simulate reinforcement learning algorithms and environments. It serves as a platform for reproducing classic textbook examples, allowing users to study agent behavior, policy improvement, and the fundamental mechanics of decision-making in controlled settings. The library provides implementations for core reinforcement learning concepts, including temporal difference learning, Monte Carlo episode sampling, and tabular value function approximation. It enables the analysis of specific algorithmic behaviors, such as identifying and

    Refines agent behavior through iterative policy evaluation and improvement cycles.

    Pythonartificial-intelligencereinforcement-learning
    Voir sur GitHub↗14,569
Préc.123…4Suivant
  1. Home
  2. Artificial Intelligence & ML
  3. Agentic Systems Frameworks
  4. Agentic Workflows

Explorer les sous-tags

  • Agent Task Initiations2 sous-tagsMechanisms for starting agent sessions via command-line arguments or external instruction files.
  • Human-in-the-Loop OversightMechanisms for humans to monitor and intervene in autonomous agent workflows via interactive interfaces. **Distinct from Agentic Workflows:** Focuses on human intervention and oversight rather than the automated design of the workflow.
  • Iterative Refinement Workflows2 sous-tagsSystems that employ feedback loops between agents to improve output quality through successive iterations.
  • Worktree Isolation1 sous-tagMechanisms for maintaining independent file states for parallel agent tasks using version control worktrees. **Distinct from State Isolation:** Distinct from general state isolation: focuses on leveraging version control worktrees specifically for agent task isolation.