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2 Repos

Awesome GitHub RepositoriesAgentic Application Implementation

End-to-end process of planning and executing software builds using AI agents and coding tools.

Distinct from Implementation Planning: No candidate covers the holistic transition from AI concept to shipped product; others are limited to planning or specific languages.

Explore 2 awesome GitHub repositories matching artificial intelligence & ml · Agentic Application Implementation. Refine with filters or upvote what's useful.

Awesome Agentic Application Implementation GitHub Repositories

Finde die besten Repos mit KI.Wir suchen mit KI nach den am besten passenden Repositories.
  • buildermethods/agent-osAvatar von buildermethods

    buildermethods/agent-os

    3,885Auf GitHub ansehen↗

    Agent-OS is an LLM multi-agent orchestration framework and AI software development lifecycle tool designed to coordinate specialized agents through shared workspaces and structured task lists. It functions as an agentic application bootstrapper and technical specification engine, providing the infrastructure to guide the process from product requirements to automated coding and deployment. The system distinguishes itself through spec-driven development, using detailed technical specifications and layered context injection to ensure generated code aligns with project standards. It employs a ma

    Plans and implements applications using coding tools to move from initial concept to a shipped product.

    Shell
    Auf GitHub ansehen↗3,885
  • datawhalechina/vibe-vibeAvatar von datawhalechina

    datawhalechina/vibe-vibe

    3,126Auf GitHub ansehen↗

    vibe-vibe is an LLM agent engineering framework and toolchain optimizer designed for orchestrating multi-agent systems. It serves as a comprehensive guide and methodology for transforming conceptual ideas into deployed applications through agentic software engineering. The project focuses on the orchestration of specialized AI agent roles with defined collaboration boundaries and iterative feedback loops. It provides frameworks for toolchain optimization, including the selection and evaluation of protocols that extend model capabilities and the design of standardized tool interfaces. The sys

    Implements an end-to-end process of planning and executing software builds using AI agents and test-driven development.

    agentagentic-aiai
    Auf GitHub ansehen↗3,126
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