Showing 4 open source projects for "android app source code"

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  • 1
    gpt-oss

    gpt-oss

    gpt-oss-120b and gpt-oss-20b are two open-weight language models

    gpt-oss is OpenAI’s open-weight family of large language models designed for powerful reasoning, agentic workflows, and versatile developer use cases. The series includes two main models: gpt-oss-120b, a 117-billion parameter model optimized for general-purpose, high-reasoning tasks that can run on a single H100 GPU, and gpt-oss-20b, a lighter 21-billion parameter model ideal for low-latency or specialized applications on smaller hardware. Both models use a native MXFP4 quantization for...
    Downloads: 10 This Week
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  • 2
    CodexBar

    CodexBar

    Show usage stats for OpenAI Codex and Claude Code

    CodexBar is a lightweight macOS utility that displays real-time usage statistics for AI coding tools such as OpenAI Codex and Claude Code directly from the system menu bar. The application is designed to give developers quick visibility into token consumption and activity without requiring them to open web dashboards or log into provider portals. Built in Swift with a native macOS interface, it integrates seamlessly into the desktop environment and emphasizes minimal overhead. The tool is...
    Downloads: 3 This Week
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  • 3
    MCPB

    MCPB

    One-click local MCP server installation in desktop apps

    MCPB (MCP Bundles) defines a packaging format and toolchain for one-click installation of local Model Context Protocol (MCP) servers in desktop apps like Claude for macOS and Windows. An .mcpb file is a zip archive containing your server and a manifest.json that declares capabilities, entry points, permissions, and configuration inputs, much like how .crx packages Chrome extensions or .vsix packages VS Code extensions. The goal is to make local tool servers easy for end users to install,...
    Downloads: 2 This Week
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  • 4
    MiniMax-M2.5

    MiniMax-M2.5

    State of the art LLM and coding model

    MiniMax-M2.5 is a state-of-the-art foundation model extensively trained with reinforcement learning across hundreds of thousands of real-world environments. It delivers leading performance in coding, agentic tool use, search, and complex office workflows, achieving top benchmark scores such as 80.2% on SWE-Bench Verified and 76.3% on BrowseComp. Designed to reason efficiently and decompose tasks like an experienced architect, M2.5 plans features, structure, and system design before...
    Downloads: 3 This Week
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