Showing 3 open source projects for "android app source code"

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  • 1
    AnyClaw

    AnyClaw

    Android app running two AI coding agents with a built-in Linux runtime

    openclaw-android-assistant, also known as AnyClaw, is an Android application that packages two AI coding agents into a single mobile app environment. It bundles the OpenClaw personal AI assistant together with the OpenAI Codex CLI so developers can interact with AI agents directly from an Android device. Both agents run inside a self-contained Linux userland that is embedded within the APK, allowing command execution, coding tasks, and agent interactions without requiring root access or external tools. openclaw-android-assistant provides a control dashboard interface where users can manage agents, sessions, skills, and conversations from a unified interface. ...
    Downloads: 20 This Week
    Last Update:
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  • 2
    Preswald

    Preswald

    Python tool for browser-based interactive data apps in one file

    ...This approach allows developers to create dashboards, reports, notebooks, and data tools that are portable, fast, and capable of running offline. Preswald emphasizes a code-first workflow where users define applications entirely in Python while using built-in UI components such as tables, charts, and forms. It also includes a reactive execution model that only recomputes necessary parts of the app, improving performance and responsiveness.
    Downloads: 4 This Week
    Last Update:
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  • 3
    Generative AI for Beginners (Version 3)

    Generative AI for Beginners (Version 3)

    21 Lessons, Get Started Building with Generative AI

    Generative AI for Beginners is a 21-lesson course by Microsoft Cloud Advocates that teaches the fundamentals of building generative AI applications in a practical, project-oriented way. Lessons are split into “Learn” modules for core concepts and “Build” modules with hands-on code in Python and TypeScript, so you can jump in at any point that matches your goals. The course covers everything from model selection, prompt engineering, and chat/text/image app patterns to secure development practices and UX for AI. It also walks through modern application techniques such as function calling, RAG with vector databases, working with open source models, agents, fine-tuning, and using SLMs. ...
    Downloads: 0 This Week
    Last Update:
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