Showing 6 open source projects for "android studio project"

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  • Build Agents and Models on One Platform Icon
    Build Agents and Models on One Platform

    Everything you need to build production-ready agents and models. Access 200+ Google and third-party AI models and tools.

    Gemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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    Custom VMs From 1 to 96 vCPUs With 99.95% Uptime

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  • 1
    LangGraph Studio

    LangGraph Studio

    Desktop app for prototyping and debugging LangGraph applications

    LangGraph Studio offers a new way to develop LLM applications by providing a specialized agent IDE that enables visualization, interaction, and debugging of complex agentic applications. With visual graphs and the ability to edit state, you can better understand agent workflows and iterate faster. LangGraph Studio integrates with LangSmith so you can collaborate with teammates to debug failure modes. While in Beta, LangGraph Studio is available for free to all LangSmith users on any plan...
    Downloads: 12 This Week
    Last Update:
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  • 2
    JADX-AI-MCP

    JADX-AI-MCP

    Plugin for JADX to integrate MCP server

    JADX-AI-MCP is an open-source plugin that integrates large language models into the JADX Android decompiler to assist with reverse engineering and code analysis tasks. The project connects JADX with AI assistants through the Model Context Protocol, enabling language models to interact directly with decompiled Android application code. Through this integration, AI systems can inspect classes, analyze methods, retrieve application manifests, and examine other elements of Android packages in real time. ...
    Downloads: 30 This Week
    Last Update:
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  • 3
    swark.io

    swark.io

    Create architecture diagrams from code automatically using LLMs

    Swark is an open-source developer tool and Visual Studio Code extension that automatically generates software architecture diagrams directly from source code using large language models. The project aims to help developers quickly understand complex codebases by analyzing repositories and producing visual diagrams that represent system architecture, dependencies, and component relationships.
    Downloads: 6 This Week
    Last Update:
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  • 4
    llama.vscode

    llama.vscode

    VS Code extension for LLM-assisted code/text completion

    ...Developers can select and manage models through a configuration interface that automatically downloads and runs the required models locally. The extension also supports agent-style coding workflows, where AI tools can perform more complex tasks such as analyzing project context or editing multiple files.
    Downloads: 9 This Week
    Last Update:
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    99.99% Uptime for MySQL and PostgreSQL Databases

    Sub-second maintenance. 2x read/write performance. Built-in vector search for AI apps.

    Cloud SQL Enterprise Plus delivers near-zero downtime with 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server.
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  • 5
    Flexpilot IDE

    Flexpilot IDE

    Open-Source AI Native IDE

    Flexpilot IDE is an open-source integrated development environment designed specifically for AI-assisted software development. Built as a fork of Visual Studio Code, the project provides a familiar development interface while integrating advanced AI capabilities directly into the coding workflow. The platform is designed to be privacy-focused and flexible, allowing developers to use their own API keys for different large language models rather than relying on a single proprietary AI provider. ...
    Downloads: 3 This Week
    Last Update:
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  • 6
    MLC LLM

    MLC LLM

    Universal LLM Deployment Engine with ML Compilation

    MLC LLM is a machine learning compiler and deployment framework designed to enable efficient execution of large language models across a wide range of hardware platforms. The project focuses on compiling models into optimized runtimes that can run natively on devices such as GPUs, mobile processors, browsers, and edge hardware. By leveraging machine learning compilation techniques, mlc-llm produces high-performance inference engines that maintain consistent APIs across platforms. The system supports deployment on environments including Linux, macOS, Windows, iOS, Android, and web browsers while utilizing different acceleration technologies such as CUDA, Vulkan, Metal, and WebGPU. ...
    Downloads: 10 This Week
    Last Update:
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