34 dépôts
Development of AI applications that run search and inference locally on the user's hardware.
Distinct from AI Application Frameworks: Distinct from general AI frameworks: focuses specifically on the local, on-device execution environment.
Explore 34 awesome GitHub repositories matching artificial intelligence & ml · Local On-Device AI. Refine with filters or upvote what's useful.
Chat2DB is an AI-powered SQL client and multi-database GUI manager designed for managing various relational and NoSQL database systems. It serves as a visual database management tool and a natural language to SQL interface, allowing users to convert plain text descriptions into executable and optimized queries. The platform distinguishes itself through automated business intelligence capabilities, which include the generation of real-time data visualization dashboards and AI-driven data analysis from spreadsheets. To ensure data privacy, it supports secure local AI deployment, enabling large
Runs large language models on local hardware to process sensitive database metadata without external uploads.
MoneyPrinter is an automated short-form video creation pipeline that generates complete YouTube Shorts from a given topic. It combines local LLM-powered script generation with programmatic video assembly, all managed through a database-backed job queue for reliable, restart-tolerant processing. The system uses an Ollama-powered local language model to write video scripts and metadata entirely on-device, keeping data private and offline. It then produces the final video clip using MoviePy for compositing clips, text, and audio, creating a complete YouTube Shorts video without manual editing. V
Writes video scripts and metadata by querying a local Ollama language model, keeping all data processing on-device.
The simplest way to run LLaMA on your local machine
Downloads specific model variants by name from a CDN for local use.
This project is a local AI inpainting tool designed to erase hard-coded subtitles and watermarks from videos and images. It functions as a content-aware media restorer that uses deep learning to reconstruct missing pixels and preserve the original resolution of the source files. The software is distinguished by its local execution model, running inference on host hardware to process media without relying on external cloud APIs. It employs content-aware model selection, allowing the use of different generative algorithms based on media types, such as animation or live action, to optimize visua
Runs generative filling models on host hardware for local media inpainting without cloud APIs.
WasmEdge is an extensible WebAssembly runtime that executes WebAssembly bytecode in a secure sandbox for cloud, edge, and embedded applications. It functions as a multi-language compiler, compiling applications written in Rust, JavaScript, Go, and Python into WebAssembly bytecode for sandboxed execution, and as a server-side JavaScript runtime that runs JavaScript programs with ES6 modules, NPM packages, and Node.js-compatible APIs. The runtime also serves as an AI inference runtime, executing AI models from JavaScript using WASI-NN plug-ins for inference tasks on personal devices and edge har
Executes AI models on smart devices by running them inside a WebAssembly sandbox with GPU access.
Local Deep Researcher is a fully local web research assistant that uses any LLM hosted by Ollama or LMStudio. Give it a topic and it will generate a web search query, gather web search results, summarize the results of web search, reflect on the summary to examine knowledge gaps, generate a new…
Provides a research agent that runs entirely on local hardware using Ollama-hosted LLMs.
Reor is a local AI knowledge management application that stores, links, and searches personal notes using large language models and vector embeddings entirely on the user's device. It functions as a private AI note assistant, keeping all data and processing local for full privacy without relying on external cloud services. The application integrates with Ollama to manage the lifecycle of local LLMs and embedding models, handling downloads, updates, and execution. Notes are imported from markdown files, preserving existing file structure, and are automatically linked through vector-similarity
Downloads, updates, and executes LLMs and embedding models through the Ollama runtime for local AI processing.
Page Assist est un outil d'intégration d'IA pour navigateur qui fournit une interface latérale pour interagir avec des modèles d'IA tout en naviguant sur le web. Il se concentre sur le chat axé sur la confidentialité et l'analyse de contenu web, permettant aux utilisateurs d'extraire et d'interroger des informations à partir de pages web actives pour recevoir des réponses contextuelles. Le projet se distingue par son intégration locale de l'IA, permettant des connexions à des modèles hébergés localement ou à des endpoints d'API privés pour traiter les données sans dépendre de services cloud. Il prend également en charge les conversations IA collaboratives via des liens de partage publics ou une infrastructure de partage auto-hébergée pour un meilleur contrôle des données. Le système inclut des capacités d'automatisation de navigateur, telles que le contrôle des onglets et l'interaction avec les éléments de page en exposant la session du navigateur comme un ensemble d'outils. Il prend en outre en charge le traitement visuel via des captures d'écran de pages web et l'extraction de contenu basée sur le DOM pour une analyse complète des pages.
Provides a browser-integrated chat interface that connects to locally hosted AI models for privacy.
This project is an Android RPA framework designed for automating user interfaces and system tasks on rooted Android devices using Python and ADB. It provides a suite of tools for rooted device management, allowing for programmatic control of system settings, application lifecycles, and shell command execution via a remote API. The framework distinguishes itself through a combination of dynamic instrumentation and AI integration. It can inject scripts into running processes to hook Java interfaces and modifies application behavior in real time. Additionally, it supports large language model in
Executes machine learning tasks and semantic task executors directly on the Android device hardware.
Paddle-Lite is a deep learning inference engine and edge computing runtime designed to execute trained models on mobile and edge devices. It provides a hardware-accelerated inference framework and a decoupled runtime with a minimal binary footprint to operate in resource-constrained environments without third-party dependencies. The project includes a model quantization tool for reducing precision and size via static and dynamic quantization, as well as a computation graph optimizer. These tools reduce latency and memory usage by fusing operators and pruning the model intermediate representat
Refines computation graphs and fuses operators to lower latency for real-time AI applications on end-user devices.
FluentRead is an open-source browser translation plugin that displays original text alongside its translation directly on web pages. It supports bilingual reading through side-by-side rendering, gesture-triggered activation via mouse hover, double-click, or touch, and keeps all translation data stored locally on the user's device with publicly auditable source code for privacy protection. The plugin offers a multi-engine translation selection, supporting over 20 providers including traditional services and large language models, allowing users to balance accuracy, cost, and privacy for each t
Sets environment variables to allow browser extensions to send requests to a local Ollama instance, bypassing CORS restrictions.
sqlite-vec is a C-based vector library and SQLite extension that adds virtual tables for storing and querying high-dimensional embeddings. It functions as a database plugin for performing nearest neighbor searches using distance metrics such as L2, cosine, and Hamming distance. The project provides a portable embedding store that supports deployment across Android, iOS, desktop environments, and web browsers via WebAssembly. It distinguishes itself by converting numerical arrays into compact binary formats and utilizing quantization to reduce the memory footprint and storage size of vector in
Enables the building of AI-powered tools that perform vector search on-device or in the browser.
DeepChat is a desktop application that connects to multiple cloud and local AI model providers through a single unified chat interface, while also integrating external ACP-compatible coding and task agents as selectable models. It manages local AI agent sessions with project folders, permission modes, and resumable context for long-running tasks, and connects external tools and data sources via the Model Context Protocol using StreamableHTTP, SSE, or Stdio transports. The application distinguishes itself by supporting remote desktop session control, binding messaging app channels to sessions
Downloads, deploys, and runs Ollama models through a graphical interface without requiring command-line operations.
Enchanted est une interface de chat multiplateforme axée sur la confidentialité pour interagir avec des grands modèles de langage auto-hébergés sur iOS et macOS. Il sert de client natif pour communiquer avec des serveurs de modèles privés, fournissant spécifiquement une intégration pour l'API Ollama. L'application prend en charge les interactions multimodales, permettant aux utilisateurs de combiner texte, pièces jointes d'images et invites vocales. Elle fournit des outils pour la gestion locale des modèles IA, incluant la possibilité de définir des prompts système persistants et de basculer entre différents modèles pour des tâches spécifiques. L'interface inclut des capacités pour le rendu de tableaux et de blocs de code formatés en Markdown, la conversion des réponses textuelles en parole audible via une synthèse au niveau du système, et la gestion d'un magasin de persistance local pour l'historique des conversations.
Serves as a native Ollama chat client for interacting with self-hosted models via the Ollama API.
Enchanted is iOS and macOS app for chatting with private self hosted language models such as Llama2, Mistral or Vicuna using Ollama.
Provides a native macOS and iOS chat interface for self-hosted Ollama language models.
The free AI already on your Mac. CLI tool, OpenAI-compatible server, and interactive chat — all on-device via Apple Intelligence. No API keys, no cloud, no downloads.
Runs a local language model on a Mac for interactive conversations without cloud dependencies or API keys.
AidLearning-Framework is an integrated development platform for building and deploying AI applications on ARM-based devices. It combines Android and Linux operating systems running simultaneously on a single device, providing a unified runtime environment for cross-system AI development. The platform includes hardware acceleration across CPU, GPU, and NPU, with a unified API that automatically selects the optimal compute backend for inference. The framework distinguishes itself by enabling Python-based AI projects to be packaged directly into Android APK files for installation on mobile devic
Builds and deploys AI applications on ARM devices with hardware acceleration across CPU, GPU, and NPU.
Serge is a self-hosted web chat interface for running large language models locally using the llama.cpp inference engine. It loads GGUF-format model files directly on your own machine, removing the need for internet connectivity or external API keys, and streams responses to the browser in real time via WebSocket connections. The project is packaged for containerized deployment using Docker and Docker Compose, with a Traefik reverse proxy that handles HTTP and WebSocket routing along with automatic TLS certificate management. Ready-made Kubernetes manifests are also provided, enabling deploym
Provides a web chat interface that runs large language models locally using GGUF files, no internet or API keys required.
Dayflow is a privacy-focused productivity tool that records screen activity locally and analyzes it with on-device AI. It captures screen frames at one frame per second, stores everything in a local database, and processes all analysis entirely on the machine to keep data private. The system builds a searchable timeline of work activity and enables natural-language queries about past screen time. The tool distinguishes itself by offering runtime switching between local AI models and cloud providers, allowing users to balance accuracy, privacy, and performance. It automatically runs AI inferen
Runs AI analysis entirely on-device using local models to keep data private.
Electrobun is a desktop application framework and webview-based GUI toolkit used for building cross-platform desktop apps. It provides a TypeScript-based runtime and a native system webview to create interfaces that integrate embedded browser views with host-process logic. The project features a native GPU integration layer with direct FFI bindings, allowing for high-performance GPU surfaces and compute workloads to run within a desktop application. It also includes an inter-process communication bridge using a typed RPC system to exchange data and execute functions between the native backend
Manages and runs open weight AI models on a local device for private chat and coding assistance.