🌟 dyad | TypeScript
🎯 Primary Use Case:
Building AI applications locally and privately.
✨ Key Features:
• Local operation
• Bring your own API keys
• Cross-platform compatibility
📖 Summary:
Dyad is a local, open-source AI app builder that allows users to create AI applications on their own machines. It emphasizes privacy, control, and the ability to use your own AI API keys, offering a fast and flexible development experience without vendor lock-in. Dyad is cross-platform, supporting both Mac and Windows.
🔗 Links:
• View Project
• Homepage
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🔓 Open Source
🎯 Primary Use Case:
Building AI applications locally and privately.
✨ Key Features:
• Local operation
• Bring your own API keys
• Cross-platform compatibility
📖 Summary:
Dyad is a local, open-source AI app builder that allows users to create AI applications on their own machines. It emphasizes privacy, control, and the ability to use your own AI API keys, offering a fast and flexible development experience without vendor lock-in. Dyad is cross-platform, supporting both Mac and Windows.
🔗 Links:
• View Project
• Homepage
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🔓 Open Source
🚀 helix-db | Rust
🎯 Primary Use Case:
Intelligent data storage for Retrieval Augmented Generation (RAG) and AI applications, leveraging both graph and vector data.
✨ Key Features:
• Fast & Efficient performance compared to other graph and vector databases
• Native support for graph and vector data types for RAG applications
• Reliable storage powered by LMDB
• ACID Compliant for data integrity
📖 Summary:
HelixDB is a graph-vector database built in Rust, designed for RAG and AI applications. It combines graph relationships with vector embeddings, providing a powerful solution for knowledge representation and retrieval. HelixDB utilizes LMDB for reliable storage and offers ACID compliance, ensuring data integrity.
🔗 Links:
• View Project
• Homepage
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🔓 Open Source
🎯 Primary Use Case:
Intelligent data storage for Retrieval Augmented Generation (RAG) and AI applications, leveraging both graph and vector data.
✨ Key Features:
• Fast & Efficient performance compared to other graph and vector databases
• Native support for graph and vector data types for RAG applications
• Reliable storage powered by LMDB
• ACID Compliant for data integrity
📖 Summary:
HelixDB is a graph-vector database built in Rust, designed for RAG and AI applications. It combines graph relationships with vector embeddings, providing a powerful solution for knowledge representation and retrieval. HelixDB utilizes LMDB for reliable storage and offers ACID compliance, ensuring data integrity.
🔗 Links:
• View Project
• Homepage
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🔓 Open Source
🔥 hash | TypeScript
🎯 Primary Use Case:
Building a self-structuring knowledge graph from various data sources.
✨ Key Features:
• Self-building database
• Open-source
• Multi-tenant
• Real-time data integration
• Autonomous agents for data management
📖 Summary:
The HASH repository provides an open-source, multi-tenant, self-building knowledge graph. It automatically integrates and structures data from various sources in real-time, allowing users to visually browse and manage both data and schemas. Intelligent agents can be deployed to maintain the database, ensuring data quality and integrity.
🔗 Links:
• View Project
• Homepage
================
🔓 Open Source
🎯 Primary Use Case:
Building a self-structuring knowledge graph from various data sources.
✨ Key Features:
• Self-building database
• Open-source
• Multi-tenant
• Real-time data integration
• Autonomous agents for data management
📖 Summary:
The HASH repository provides an open-source, multi-tenant, self-building knowledge graph. It automatically integrates and structures data from various sources in real-time, allowing users to visually browse and manage both data and schemas. Intelligent agents can be deployed to maintain the database, ensuring data quality and integrity.
🔗 Links:
• View Project
• Homepage
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🔓 Open Source
✨ Smart_Segments | Python
🎯 Primary Use Case:
Intelligent object detection and selection in Krita using AI-powered segmentation.
✨ Key Features:
• AI-Powered Segmentation
• Interactive Selection
• Real-time Preview
• Smart Tools Integration
• Artist-Friendly Design
📖 Summary:
Smart Segments is a Krita plugin that leverages AI to provide intelligent, one-click object detection and selection. It allows artists to quickly and easily segment their artwork, offering features like real-time preview and seamless integration with Krita's native tools, streamlining the digital art workflow.
🔗 Links:
• View Project
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🔓 Open Source
🎯 Primary Use Case:
Intelligent object detection and selection in Krita using AI-powered segmentation.
✨ Key Features:
• AI-Powered Segmentation
• Interactive Selection
• Real-time Preview
• Smart Tools Integration
• Artist-Friendly Design
📖 Summary:
Smart Segments is a Krita plugin that leverages AI to provide intelligent, one-click object detection and selection. It allows artists to quickly and easily segment their artwork, offering features like real-time preview and seamless integration with Krita's native tools, streamlining the digital art workflow.
🔗 Links:
• View Project
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🔓 Open Source
💡 TubeSummary | TypeScript
🎯 Primary Use Case:
Summarizing YouTube videos using AI to quickly extract key insights.
✨ Key Features:
• Summarize YouTube videos instantly with a single click
• AI-powered follow-up Q&A below the video
• Support for multiple LLM providers (OpenAI-compatible)
• Prompts and provider credentials fully customizable
• Works on latest Firefox, Chrome, and more
📖 Summary:
TubeSummary is a browser extension that uses AI to generate summaries of YouTube videos. It allows users to quickly understand the content of a video without watching the entire thing. The extension supports multiple LLM providers and offers customizable prompts and credentials.
🔗 Links:
• View Project
================
🔓 Open Source
🎯 Primary Use Case:
Summarizing YouTube videos using AI to quickly extract key insights.
✨ Key Features:
• Summarize YouTube videos instantly with a single click
• AI-powered follow-up Q&A below the video
• Support for multiple LLM providers (OpenAI-compatible)
• Prompts and provider credentials fully customizable
• Works on latest Firefox, Chrome, and more
📖 Summary:
TubeSummary is a browser extension that uses AI to generate summaries of YouTube videos. It allows users to quickly understand the content of a video without watching the entire thing. The extension supports multiple LLM providers and offers customizable prompts and credentials.
🔗 Links:
• View Project
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🔓 Open Source
✨ Twocast | TypeScript
🎯 Primary Use Case:
AI-powered generation of bilingual, two-person podcasts from various input sources like topics, links, documents, and list pages.
✨ Key Features:
• Two-person Podcast generation
• Generates 3-5 minute podcasts with one click
• Supports multiple generation methods: Topic, Link, Document (doc/pdf/txt), List Page
• Multi-language support
📖 Summary:
Twocast is an AI podcast generator that creates bilingual, two-person podcasts. It supports multiple input methods, including topics, links, documents, and list pages, and generates podcasts with downloadable audio, outlines, and scripts. The platform integrates with Fish Audio, Minimax, and Google Gemini for voice synthesis and language processing.
🔗 Links:
• View Project
• Homepage
================
🔓 Open Source
🎯 Primary Use Case:
AI-powered generation of bilingual, two-person podcasts from various input sources like topics, links, documents, and list pages.
✨ Key Features:
• Two-person Podcast generation
• Generates 3-5 minute podcasts with one click
• Supports multiple generation methods: Topic, Link, Document (doc/pdf/txt), List Page
• Multi-language support
📖 Summary:
Twocast is an AI podcast generator that creates bilingual, two-person podcasts. It supports multiple input methods, including topics, links, documents, and list pages, and generates podcasts with downloadable audio, outlines, and scripts. The platform integrates with Fish Audio, Minimax, and Google Gemini for voice synthesis and language processing.
🔗 Links:
• View Project
• Homepage
================
🔓 Open Source
✨ BookLore | Java
🎯 Primary Use Case:
Managing and reading personal book and comic collections in a self-hosted environment.
✨ Key Features:
• Powerful Book Organization with Libraries and Shelves
• Intelligent Metadata Management from multiple sources
• Multi-User Access with Permissions
• Built-in PDF, ePub, and CBX Reader
• OPDS 1.2 Integration
📖 Summary:
BookLore is a self-hosted web application designed for organizing, managing, and reading personal book and comic collections. It offers features such as metadata management, multi-user support with permission controls, built-in readers for various ebook formats, and OPDS integration, providing a comprehensive solution for building and exploring a personal digital library.
🔗 Links:
• View Project
================
🔓 Open Source
🎯 Primary Use Case:
Managing and reading personal book and comic collections in a self-hosted environment.
✨ Key Features:
• Powerful Book Organization with Libraries and Shelves
• Intelligent Metadata Management from multiple sources
• Multi-User Access with Permissions
• Built-in PDF, ePub, and CBX Reader
• OPDS 1.2 Integration
📖 Summary:
BookLore is a self-hosted web application designed for organizing, managing, and reading personal book and comic collections. It offers features such as metadata management, multi-user support with permission controls, built-in readers for various ebook formats, and OPDS integration, providing a comprehensive solution for building and exploring a personal digital library.
🔗 Links:
• View Project
================
🔓 Open Source
🌟 OpenCut | TypeScript
🎯 Primary Use Case:
Open-source video editing
✨ Key Features:
• Timeline-based editing
• Multi-track support
• Real-time preview
• No watermarks or subscriptions
📖 Summary:
OpenCut is an open-source video editor designed as an alternative to CapCut. It offers timeline-based editing, multi-track support, and real-time preview capabilities without watermarks or subscriptions. The project aims to provide a simple and privacy-focused video editing solution for web, desktop, and mobile platforms.
🔗 Links:
• View Project
• Homepage
================
🔓 Open Source
🎯 Primary Use Case:
Open-source video editing
✨ Key Features:
• Timeline-based editing
• Multi-track support
• Real-time preview
• No watermarks or subscriptions
📖 Summary:
OpenCut is an open-source video editor designed as an alternative to CapCut. It offers timeline-based editing, multi-track support, and real-time preview capabilities without watermarks or subscriptions. The project aims to provide a simple and privacy-focused video editing solution for web, desktop, and mobile platforms.
🔗 Links:
• View Project
• Homepage
================
🔓 Open Source
🌟 binwalk | Rust
🎯 Primary Use Case:
Firmware analysis
✨ Key Features:
• Identifies embedded files and data.
• Extracts embedded files and data.
• Supports a wide variety of file types.
• Performs entropy analysis to identify compression or encryption.
• Can be integrated into Rust projects.
📖 Summary:
Binwalk is a firmware analysis tool written in Rust that identifies and extracts embedded files and data from various file types. It utilizes entropy analysis to detect compression or encryption and can be integrated into other Rust projects. The tool aims to provide fast and detailed analysis results.
🔗 Links:
• View Project
================
🔓 Open Source
🎯 Primary Use Case:
Firmware analysis
✨ Key Features:
• Identifies embedded files and data.
• Extracts embedded files and data.
• Supports a wide variety of file types.
• Performs entropy analysis to identify compression or encryption.
• Can be integrated into Rust projects.
📖 Summary:
Binwalk is a firmware analysis tool written in Rust that identifies and extracts embedded files and data from various file types. It utilizes entropy analysis to detect compression or encryption and can be integrated into other Rust projects. The tool aims to provide fast and detailed analysis results.
🔗 Links:
• View Project
================
🔓 Open Source
🌟 desktop_homunculus | Rust
🎯 Primary Use Case:
A cross-platform desktop pet application that brings intelligent 3D VRM characters to life on your desktop, allowing for AI-powered conversations, custom animations, and interactions with your workflow.
✨ Key Features:
• AI-Powered Chat Integration (ChatGPT, VoiceVox)
• Advanced VRM Character System (Multiple Models, VRMA Support)
📖 Summary:
Desktop Homunculus is a Rust-based application that uses the Bevy game engine to create interactive desktop pets. It features AI-powered chat integration with ChatGPT and VoiceVox, advanced VRM character support, and an extensible MOD system for customization. The application aims to enhance the user experience by providing a personalized and engaging desktop companion.
🔗 Links:
• View Project
================
🔓 Open Source
🎯 Primary Use Case:
A cross-platform desktop pet application that brings intelligent 3D VRM characters to life on your desktop, allowing for AI-powered conversations, custom animations, and interactions with your workflow.
✨ Key Features:
• AI-Powered Chat Integration (ChatGPT, VoiceVox)
• Advanced VRM Character System (Multiple Models, VRMA Support)
📖 Summary:
Desktop Homunculus is a Rust-based application that uses the Bevy game engine to create interactive desktop pets. It features AI-powered chat integration with ChatGPT and VoiceVox, advanced VRM character support, and an extensible MOD system for customization. The application aims to enhance the user experience by providing a personalized and engaging desktop companion.
🔗 Links:
• View Project
================
🔓 Open Source
💡 rallies-cli | Python
🎯 Primary Use Case:
Intelligent investment research and analysis using real-time financial data and AI.
✨ Key Features:
• AI-powered investment research
• Real-time financial data integration
• ChatGPT-like conversational interface for trading and investment analysis
📖 Summary:
Rallies-cli is an AI-powered investment research tool that combines the conversational abilities of AI with real-time financial data. It allows traders and investors to perform complex queries, analyze market trends, and gain insights that are not readily available with traditional tools like ChatGPT due to their lack of real-time data. The tool provides functionalities for technical analysis, news monitoring, and advanced market analysis.
🔗 Links:
• View Project
• Homepage
================
🔓 Open Source
🎯 Primary Use Case:
Intelligent investment research and analysis using real-time financial data and AI.
✨ Key Features:
• AI-powered investment research
• Real-time financial data integration
• ChatGPT-like conversational interface for trading and investment analysis
📖 Summary:
Rallies-cli is an AI-powered investment research tool that combines the conversational abilities of AI with real-time financial data. It allows traders and investors to perform complex queries, analyze market trends, and gain insights that are not readily available with traditional tools like ChatGPT due to their lack of real-time data. The tool provides functionalities for technical analysis, news monitoring, and advanced market analysis.
🔗 Links:
• View Project
• Homepage
================
🔓 Open Source
🚀 AgentGuard | JavaScript
🎯 Primary Use Case:
Preventing runaway costs in AI agent development by monitoring token usage and terminating processes when a defined budget is exceeded.
✨ Key Features:
• Real-time monitoring of AI API costs
• Automatic process termination when budget limit is reached
• Multiple protection modes (throw, notify, kill)
• Detailed savings reports
📖 Summary:
AgentGuard is a real-time guardrail for AI agents that monitors token spend and automatically stops execution when a defined cost limit is reached. It helps developers avoid unexpected high costs due to infinite loops or other bugs in their AI workflows by providing immediate feedback and control over API usage.
🔗 Links:
• View Project
================
🔓 Open Source
🎯 Primary Use Case:
Preventing runaway costs in AI agent development by monitoring token usage and terminating processes when a defined budget is exceeded.
✨ Key Features:
• Real-time monitoring of AI API costs
• Automatic process termination when budget limit is reached
• Multiple protection modes (throw, notify, kill)
• Detailed savings reports
📖 Summary:
AgentGuard is a real-time guardrail for AI agents that monitors token spend and automatically stops execution when a defined cost limit is reached. It helps developers avoid unexpected high costs due to infinite loops or other bugs in their AI workflows by providing immediate feedback and control over API usage.
🔗 Links:
• View Project
================
🔓 Open Source
🔥 Bella | JavaScript
🎯 Primary Use Case:
A digital companion that provides voice-based interaction, visual expression, and AI-powered dialogue.
✨ Key Features:
• Voice Perception (Whisper ASR)
• Visual Expression (video playback with cross-fading)
• User Interface (elegant and responsive)
• AI Core Architecture (modular design)
• Web Service (HTTP server, CORS support)
📖 Summary:
Bella AI is a digital companion built with JavaScript, Node.js, and AI models like Whisper and a local LLM. It offers voice perception, visual expression, and enhanced LLM dialogue, aiming to create a personalized and interactive experience. The project envisions a digital friend that evolves and grows with the user.
🔗 Links:
• View Project
================
🔓 Open Source
🎯 Primary Use Case:
A digital companion that provides voice-based interaction, visual expression, and AI-powered dialogue.
✨ Key Features:
• Voice Perception (Whisper ASR)
• Visual Expression (video playback with cross-fading)
• User Interface (elegant and responsive)
• AI Core Architecture (modular design)
• Web Service (HTTP server, CORS support)
📖 Summary:
Bella AI is a digital companion built with JavaScript, Node.js, and AI models like Whisper and a local LLM. It offers voice perception, visual expression, and enhanced LLM dialogue, aiming to create a personalized and interactive experience. The project envisions a digital friend that evolves and grows with the user.
🔗 Links:
• View Project
================
🔓 Open Source
🔥 say | TypeScript
🎯 Primary Use Case:
Voice transcription and note-taking within a browser environment.
✨ Key Features:
• Browser-based Recording
• ML-Powered Transcription
• Rich Text Editing
• Audio Visualization
• Local Storage
📖 Summary:
Say is a voice transcription app that converts speech to text using machine learning directly in the browser. It offers features such as browser-based recording, rich text editing, audio visualization, and local storage, all within a modern and responsive user interface. The app is built with React, TypeScript, and utilizes technologies like Transformers.js and Tailwind CSS.
🔗 Links:
• View Project
• Homepage
================
🔓 Open Source
🎯 Primary Use Case:
Voice transcription and note-taking within a browser environment.
✨ Key Features:
• Browser-based Recording
• ML-Powered Transcription
• Rich Text Editing
• Audio Visualization
• Local Storage
📖 Summary:
Say is a voice transcription app that converts speech to text using machine learning directly in the browser. It offers features such as browser-based recording, rich text editing, audio visualization, and local storage, all within a modern and responsive user interface. The app is built with React, TypeScript, and utilizes technologies like Transformers.js and Tailwind CSS.
🔗 Links:
• View Project
• Homepage
================
🔓 Open Source
🌟 mcp-knowledge-graph | JavaScript
🎯 Primary Use Case:
Providing AI models with persistent memory by storing and retrieving information from a local knowledge graph.
✨ Key Features:
• Persistent memory for AI models
• Local knowledge graph storage
• Customizable memory path
• Entities, Relations, and Observations data model
• API for creating, deleting, and reading entities, relations, and observations
📖 Summary:
The `mcp-knowledge-graph` repository provides a local knowledge graph memory server for AI models, enabling persistent memory across chats. It utilizes entities, relations, and observations to structure knowledge and offers an API for managing the knowledge graph. This allows AI models to remember user information and context.
🔗 Links:
• View Project
================
🔓 Open Source
🎯 Primary Use Case:
Providing AI models with persistent memory by storing and retrieving information from a local knowledge graph.
✨ Key Features:
• Persistent memory for AI models
• Local knowledge graph storage
• Customizable memory path
• Entities, Relations, and Observations data model
• API for creating, deleting, and reading entities, relations, and observations
📖 Summary:
The `mcp-knowledge-graph` repository provides a local knowledge graph memory server for AI models, enabling persistent memory across chats. It utilizes entities, relations, and observations to structure knowledge and offers an API for managing the knowledge graph. This allows AI models to remember user information and context.
🔗 Links:
• View Project
================
🔓 Open Source
✨ crush | Go
🎯 Primary Use Case:
AI-assisted coding in the terminal
✨ Key Features:
• Multi-Model LLM support
• Flexible LLM switching
• Session-based context management
• LSP-enhanced context
• Extensible capabilities via MCPs
📖 Summary:
Crush is an AI coding agent designed to enhance the developer experience within the terminal. It offers features such as multi-model LLM support, session-based context management, and LSP integration to provide intelligent code suggestions and assistance. Crush aims to streamline coding workflows and improve developer productivity across various operating systems.
🔗 Links:
• View Project
================
🔓 Open Source
🎯 Primary Use Case:
AI-assisted coding in the terminal
✨ Key Features:
• Multi-Model LLM support
• Flexible LLM switching
• Session-based context management
• LSP-enhanced context
• Extensible capabilities via MCPs
📖 Summary:
Crush is an AI coding agent designed to enhance the developer experience within the terminal. It offers features such as multi-model LLM support, session-based context management, and LSP integration to provide intelligent code suggestions and assistance. Crush aims to streamline coding workflows and improve developer productivity across various operating systems.
🔗 Links:
• View Project
================
🔓 Open Source
💡 erys | Python
🎯 Primary Use Case:
Interacting with Jupyter Notebooks directly from the terminal.
✨ Key Features:
• Opening existing Jupyter Notebooks
• Creating, editing, and saving Jupyter Notebooks
• Executing Python code within code cells in the terminal
• Directory tree navigation for file management
• Saving notebooks in format version 4.5
📖 Summary:
Erys is a terminal interface for Jupyter Notebooks, enabling users to open, create, edit, run, and save notebooks and other text files directly from the terminal. It leverages Textual for the interface and jupyter_client for code execution, providing a streamlined workflow for developers who prefer a terminal-based environment.
🔗 Links:
• View Project
• Homepage
================
🔓 Open Source
🎯 Primary Use Case:
Interacting with Jupyter Notebooks directly from the terminal.
✨ Key Features:
• Opening existing Jupyter Notebooks
• Creating, editing, and saving Jupyter Notebooks
• Executing Python code within code cells in the terminal
• Directory tree navigation for file management
• Saving notebooks in format version 4.5
📖 Summary:
Erys is a terminal interface for Jupyter Notebooks, enabling users to open, create, edit, run, and save notebooks and other text files directly from the terminal. It leverages Textual for the interface and jupyter_client for code execution, providing a streamlined workflow for developers who prefer a terminal-based environment.
🔗 Links:
• View Project
• Homepage
================
🔓 Open Source
🔥 unregistry | Go
🎯 Primary Use Case:
Deploying Docker images to remote servers without the overhead of managing a container registry.
✨ Key Features:
• Directly pushes Docker images to remote servers
• Eliminates the need for an external registry
• Transfers only missing layers for efficiency
• Uses SSH for secure transfer
📖 Summary:
Unregistry allows users to push Docker images directly to remote servers over SSH, bypassing the need for a container registry. It efficiently transfers only the missing layers, making the process faster and more resource-friendly than traditional methods like save/load or rebuilding remotely. This tool simplifies image deployment for scenarios where a full-fledged registry is unnecessary.
🔗 Links:
• View Project
• Homepage
================
🔓 Open Source
🎯 Primary Use Case:
Deploying Docker images to remote servers without the overhead of managing a container registry.
✨ Key Features:
• Directly pushes Docker images to remote servers
• Eliminates the need for an external registry
• Transfers only missing layers for efficiency
• Uses SSH for secure transfer
📖 Summary:
Unregistry allows users to push Docker images directly to remote servers over SSH, bypassing the need for a container registry. It efficiently transfers only the missing layers, making the process faster and more resource-friendly than traditional methods like save/load or rebuilding remotely. This tool simplifies image deployment for scenarios where a full-fledged registry is unnecessary.
🔗 Links:
• View Project
• Homepage
================
🔓 Open Source
🚀 Skywork-R1V | Python
🎯 Primary Use Case:
Multimodal reasoning and understanding, particularly for vision-language tasks.
✨ Key Features:
• Multimodal reasoning
• Vision-language understanding
• Reinforcement learning fine-tuning
• Quantized versions for efficient inference (AWQ, GGUF)
• State-of-the-art performance on multimodal reasoning benchmarks
📖 Summary:
Skywork-R1V is a multimodal AI model series specializing in vision-language reasoning. It leverages reinforcement learning for fine-tuning and achieves state-of-the-art performance on various multimodal reasoning benchmarks. Quantized versions are available for efficient inference on different hardware configurations.
🔗 Links:
• View Project
• Homepage
================
🔓 Open Source
🎯 Primary Use Case:
Multimodal reasoning and understanding, particularly for vision-language tasks.
✨ Key Features:
• Multimodal reasoning
• Vision-language understanding
• Reinforcement learning fine-tuning
• Quantized versions for efficient inference (AWQ, GGUF)
• State-of-the-art performance on multimodal reasoning benchmarks
📖 Summary:
Skywork-R1V is a multimodal AI model series specializing in vision-language reasoning. It leverages reinforcement learning for fine-tuning and achieves state-of-the-art performance on various multimodal reasoning benchmarks. Quantized versions are available for efficient inference on different hardware configurations.
🔗 Links:
• View Project
• Homepage
================
🔓 Open Source
💡 ui-experiments | TypeScript
🎯 Primary Use Case:
Providing developers with ready-to-use UI layouts and experiments built with Origin UI and shadcn/ui to accelerate development and inspire design.
✨ Key Features:
• Pre-designed layouts
• UI experiments
• shadcn/ui monorepo template
• Origin UI components
📖 Summary:
The ui-experiments repository offers a collection of beautifully designed, open-source UI layouts and experiments. It leverages Origin UI and shadcn/ui components, providing developers with practical examples and starting points for their projects. The repository also includes a shadcn/ui monorepo template for streamlined development.
🔗 Links:
• View Project
• Homepage
================
🔓 Open Source
🎯 Primary Use Case:
Providing developers with ready-to-use UI layouts and experiments built with Origin UI and shadcn/ui to accelerate development and inspire design.
✨ Key Features:
• Pre-designed layouts
• UI experiments
• shadcn/ui monorepo template
• Origin UI components
📖 Summary:
The ui-experiments repository offers a collection of beautifully designed, open-source UI layouts and experiments. It leverages Origin UI and shadcn/ui components, providing developers with practical examples and starting points for their projects. The repository also includes a shadcn/ui monorepo template for streamlined development.
🔗 Links:
• View Project
• Homepage
================
🔓 Open Source