Search Results for "mobile applications"
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Showing 62 open source projects for "mobile applications"
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Telegram MCP
MCP server to work with Telegram through MTProto
An MCP server that bridges the Telegram API and AI assistants, enabling seamless interaction between AI applications and Telegram through MTProto. -
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ncnn
High-performance neural network inference framework for mobile
ncnn is a high-performance neural network inference computing framework designed specifically for mobile platforms. It brings artificial intelligence right at your fingertips with no third-party dependencies, and speeds faster than all other known open source frameworks for mobile phone cpu. ncnn allows developers to easily deploy deep learning algorithm models to the mobile platform and create intelligent APPs. It is cross-platform and supports most commonly used CNN networks, including Classical CNN (VGG AlexNet GoogleNet Inception), Face Detection (MTCNN RetinaFace), Segmentation (FCN PSPNet UNet YOLACT), and more. ncnn is currently being used in a number of Tencent applications, namely: QQ, Qzone, WeChat, and Pitu. -
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OpenCV
Open Source Computer Vision Library
OpenCV (Open Source Computer Vision Library) is a comprehensive open-source library for computer vision, machine learning, and image processing. It enables developers to build real-time vision applications ranging from facial recognition to object tracking. OpenCV supports a wide range of programming languages including C++, Python, and Java, and is optimized for both CPU and GPU operations. -
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Chat with LLMs Everywhere
Run PyTorch LLMs locally on servers, desktop and mobile
TorchChat is an open-source project from the PyTorch ecosystem designed to demonstrate how large language models can be executed efficiently across different computing environments. The project provides a compact codebase that illustrates how to run conversational AI systems using PyTorch models on laptops, servers, and mobile devices. It is intended primarily as a reference implementation that shows developers how to integrate large language models into applications without requiring a large or complex infrastructure stack. TorchChat supports running models through Python interfaces as well as integrating them directly into native applications written in languages such as C or C++. ... -
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nndeploy
An Easy-to-Use and High-Performance AI Deployment Framework
nndeploy is an open-source framework designed to simplify the deployment of artificial intelligence models across multiple hardware platforms and devices. The framework focuses on making it easier to transform trained AI models into production-ready applications that can run efficiently on desktops, mobile devices, servers, and edge computing hardware. Developers can use visual workflows to design and configure AI processing pipelines by connecting modular nodes that represent different stages of the inference process. The system supports multiple inference engines and hardware accelerators, allowing the same AI workflow to run on different platforms without significant modifications. nndeploy also includes performance optimization techniques such as parallel execution, memory reuse, and hardware-accelerated operations to improve inference speed. -
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React Native AI
Full stack framework for building cross-platform mobile AI apps
React Native AI is a full-stack framework designed to simplify the development of AI-powered mobile applications using React Native. The project provides a ready-to-use infrastructure for building cross-platform apps that integrate large language models and other AI services. It supports real-time streaming responses from multiple AI providers and enables developers to build chat interfaces, AI-driven image generation tools, and natural language features within mobile apps. ... -
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Kitten TTS
State-of-the-art TTS model under 25MB
KittenTTS is an open-source, ultra-lightweight, and high-quality text-to-speech model featuring just 15 million parameters and a binary size under 25 MB. It is designed for real-time CPU-based deployment across diverse platforms. Ultra-lightweight, model size less than 25MB. CPU-optimized, runs without GPU on any device. High-quality voices, several premium voice options available. Fast inference, optimized for real-time speech synthesis. -
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DeepSeek R1
Open-source, high-performance AI model with advanced reasoning
DeepSeek-R1 is an open-source large language model developed by DeepSeek, designed to excel in complex reasoning tasks across domains such as mathematics, coding, and language. DeepSeek R1 offers unrestricted access for both commercial and academic use. The model employs a Mixture of Experts (MoE) architecture, comprising 671 billion total parameters with 37 billion active parameters per token, and supports a context length of up to 128,000 tokens. DeepSeek-R1's training regimen uniquely... -
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Android Use
Automate native Android apps with AI using accessibility APIs
android-action-kernel is an open source Python library designed to let AI agents control and automate native Android applications running on real devices or emulators. It fills a gap in automation tooling by focusing on mobile-first workflows where traditional browser or desktop-based automation doesn’t work; such as logistics, gig work, field operations, and other industries reliant on phones or tablets. The project works by using Android’s accessibility API to extract structured UI state (as XML) from the device, which is then fed to a large language model (LLM) like OpenAI’s models for decision-making, and actions are executed via the Android Debug Bridge (ADB). ... -
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AppAgent
Multimodal Agents as Smartphone Users, an LLM-based multimodal agent
AppAgent is an open-source multimodal agent framework designed to enable large language models to operate smartphone applications through natural interactions with graphical user interfaces. The system allows an AI agent to interpret visual information from the screen and translate natural language instructions into actions such as tapping, swiping, and navigating between application screens. Instead of requiring backend access to application APIs, the framework interacts with apps the same way a human user would, making it compatible with a wide variety of mobile applications. -
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Generative AI for beginners with JS
Join a time-traveling adventure where you meet history’s legends
...Topics covered include prompt engineering, building AI-powered applications, working with structured outputs, integrating retrieval-augmented generation, and enabling tool or function calling in AI systems. The repository focuses specifically on how generative AI can be integrated into web, mobile, or desktop applications using JavaScript frameworks and APIs. -
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LiteRT-LM
LiteRT-LM is Google's production-ready inference framework
LiteRT-LM is Google’s open-source inference framework for deploying large language models on edge devices. It is built for production-oriented local LLM execution across Android, iOS, desktop, web, embedded, and IoT environments. The framework focuses on performance, hardware acceleration, and efficient model serving close to the user instead of relying only on remote cloud inference. It supports CPU execution across major platforms and adds GPU or NPU acceleration where available. LiteRT-LM... -
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Amical
Open Source AI Dictation App
Amical is an open source, AI-powered desktop dictation and note-taking application that enables users to dictate hands-free, transcribe meetings, and capture notes effortlessly with unmatched speed, accuracy, and privacy. It leverages both local and cloud-based AI models, letting users seamlessly switch between providers for the ideal balance of speed, precision, and control, and understands the context of each app in use to automatically format text in a tone and style appropriate to the... -
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Flutter Agent Skills
Agent skills for Flutter, maintained by the Flutter team
Flutter Skills is an educational repository from the Flutter ecosystem that provides structured hands-on exercises, tutorials, and learning paths for improving Flutter and Dart development skills. The project focuses on practical learning through guided coding challenges, interactive examples, and real-world mobile application scenarios rather than purely theoretical documentation. It covers topics such as UI construction, state management, animations, asynchronous programming, architecture patterns, and testing workflows within Flutter applications. The repository is designed for developers at different experience levels, offering incremental progression from foundational concepts to more advanced mobile engineering techniques. ... -
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Midscene
Vision-based AI framework for cross-platform UI automation tasks
...Instead of relying on traditional selectors, DOM structures, or accessibility attributes, it uses a vision-first approach where screenshots are analyzed by visual-language models to identify interface elements and perform actions. It allows developers to automate interactions on web applications, desktop software, and mobile devices without needing platform-specific automation logic. Developers can describe tasks such as clicking buttons, filling forms, or extracting information, and the system interprets these commands to interact with the interface accordingly. Midscene.js includes SDKs, scripting options, and integration capabilities that allow automation workflows to be written in JavaScript, TypeScript, or YAML-based scripts. ... -
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AI App Lab
Implementing large models into scenario-based applications
...The repository also contains a large collection of prototype applications that demonstrate how AI can be applied to scenarios such as customer service, education, content generation, and mobile automation. These examples allow developers to quickly replicate and customize solutions for their own business needs. -
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MLC LLM
Universal LLM Deployment Engine with ML Compilation
...It also provides OpenAI-compatible APIs that allow developers to integrate locally deployed models into existing AI applications without major code changes. -
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Easy-Vibe
Tutorial on Product Prototype, AI Capability Integration
Easy-Vibe is an open-source educational project designed to teach developers, product managers, and beginners how to build AI-powered applications using the emerging concept of “vibe coding,” a development approach that relies heavily on AI-assisted programming tools. The project provides a structured curriculum that guides learners from having no programming experience to building fully functional AI-integrated applications. Instead of focusing only on theoretical concepts, Easy-Vibe... -
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AndroidEnv
RL research on Android devices
android_env is a reinforcement learning (RL) environment developed by Google DeepMind that enables agents to interact with Android applications directly as a learning environment. It provides a standardized API for training agents to perform tasks on Android apps, supporting tasks ranging from games to productivity apps, making it suitable for research in real-world RL settings. -
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ProjectLearn.io
A curated list of project tutorials for project-based learning
ProjectLearn.io is an open-source repository that aggregates curated tutorials focused on project-based programming education. The project organizes learning resources where users build complete applications from scratch, helping learners acquire practical development experience rather than relying solely on theoretical tutorials. The repository includes projects across multiple domains such as web development, mobile development, machine learning, artificial intelligence, and game development. Each project entry typically links to external tutorials that guide learners through building a working application using modern frameworks and programming languages. ... -
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MediaPipe Solutions
Cross-platform, customizable ML solutions
...The system provides developers with tools and reusable components that allow them to combine multiple machine learning models with preprocessing and postprocessing logic into efficient perception pipelines. These pipelines can run on a wide variety of platforms including mobile devices, desktop systems, web browsers, and embedded edge devices. MediaPipe is widely used in computer vision and multimedia applications such as hand tracking, face detection, pose estimation, object recognition, and gesture analysis. The framework includes prebuilt solutions that developers can quickly integrate into applications as well as lower-level APIs that allow custom pipeline construction. -
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Cake
Distributed LLM and StableDiffusion inference
Cake is a compact, powerful toolkit that combines a flexible TCP/UDP proxy, port forwarding system, and connection manager designed for both development and penetration testing scenarios. It enables users to create complex networking flows where traffic can be proxied, relayed, and manipulated between endpoints — useful for debugging networked applications, inspecting protocols, or tunneling traffic through different hops. The tool is designed to work with multiple protocols and supports... -
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Lobe Icons
Brings AI/LLM brand logos to your React & React Native apps
Lobe Icons is an open-source icon library designed to provide developers with a comprehensive collection of logos and visual assets representing popular artificial intelligence platforms, language models, and related technologies. The project focuses on making it easy for developers to include recognizable AI brand icons in applications such as dashboards, AI tools, documentation sites, or developer portals. The library includes icons for a wide range of AI providers and models, allowing developers to visually represent integrations with tools such as large language models, AI APIs, and machine learning platforms. These icons are distributed in multiple formats including SVG, PNG, and WebP so they can be used in both web and mobile applications. -
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mllm
Fast Multimodal LLM on Mobile Devices
mllm is an open-source inference engine designed to run multimodal large language models efficiently on mobile devices and edge computing environments. The framework focuses on delivering high-performance AI inference in resource-constrained systems such as smartphones, embedded hardware, and lightweight computing platforms. Implemented primarily in C and C++, it is designed to operate with minimal external dependencies while taking advantage of hardware-specific acceleration technologies... -
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Live helper chat
Live support for your website. Featuring web and mobile apps
...Designed to handle high volumes of interactions, it can support thousands of concurrent conversations and multiple operators, making it suitable for enterprise-level deployments. The platform includes a web-based interface as well as mobile applications, allowing support teams to manage conversations from various environments. It supports a wide range of communication channels, including web chat widgets, email, and integrations with messaging platforms such as Facebook Messenger, Telegram, and WhatsApp. Advanced features such as chat automation, bots, proactive invitations, and analytics help businesses optimize customer engagement and response efficiency.
