Showing 4 open source projects for "test automation"

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    Dagger

    Dagger

    Containerized automation engine for programmable CI/CD workflows

    Dagger is an open source automation engine designed to build, test, and deliver software in a consistent and programmable way. It enables developers to define software delivery workflows using code instead of complex shell scripts or configuration files. Dagger executes tasks inside containers, ensuring that automation runs in identical environments across local machines, CI servers, or cloud infrastructure.
    Downloads: 0 This Week
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  • 2
    npcpy

    npcpy

    The AI toolkit for the AI developer

    npcpy is a Python-based agent framework and command-line toolkit (the NPC Shell) for developers to build, test, and integrate AI agents into their workflows, including both command-line and GUI interfaces via NPC Studio. Welcome to npcpy, the core library of the NPC Toolkit that supercharges natural language processing pipelines and agent tooling. npcpy is a flexible framework for building state-of-the-art applications and conducting novel research with LLMs. The structure of npcpy also...
    Downloads: 4 This Week
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  • 3
    Harbor LLM

    Harbor LLM

    Run a full local LLM stack with one command using Docker

    ...Harbor supports multiple inference engines, including llama.cpp and vLLM, and connects them seamlessly to user interfaces. It also includes tools for web retrieval, image generation, voice interaction, and workflow automation. Built on Docker, Harbor allows services to run in isolated containers while communicating over a local network. It is intended for local development and experimentation rather than production deployment, giving developers a flexible way to explore AI systems, test configurations, and manage complex LLM stacks without manual wiring or setup overhead.
    Downloads: 2 This Week
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  • 4
    Trae Agent

    Trae Agent

    LLM-based agent for general purpose software engineering tasks

    ...Because of its transparent, research-friendly design and detailed logging (trajectory recording), it is positioned not just as a productivity tool but also as a platform for researchers to explore, analyze, or extend AI-based code automation strategies.
    Downloads: 0 This Week
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