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Showing 19194 open source projects for "simple-scan"
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Pendulum
Python datetimes made easy
...Pendulum gives access to more attributes and properties than the default datetime class. The __str__ magic method is defined to allow DateTime instances to be printed as a pretty date string when used in a string context. Simple comparison is offered up via the basic operators. -
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URQL
The highly customizable and versatile GraphQL client
The highly customizable and versatile GraphQL client with which you add on features like normalized caching as you grow. urql is a highly customizable and versatile GraphQL client with which you add on features like normalized caching as you grow. It's built to be both easy to use for newcomers to GraphQL, and extensible, to grow to support dynamic single-app applications and highly customized GraphQL infrastructure. In short, urql prioritizes usability and adaptability. As you're adopting... -
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two.js
A renderer agnostic two-dimensional drawing api for the web
...This means that when you draw or create an object (a Two.Path or Two.Group), two actually stores and remembers that. After you make the object you can apply any number of operations to it. Two.js has a built in animation loop. It is simple in nature and can be automated or paired with another animation library. Two.js features a Scalable Vector Graphics Interpreter. This means developers and designers alike can create SVG elements in commercial applications like Adobe Illustrator and bring them into your two.js scene. -
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AVA
Node.js test runner that lets you develop with confidence
AVA is a test runner for Node.js that’s minimal and fast, and lets you develop with confidence. AVA is equipped with a concise API, detailed error output, process isolation and many other great features that set it apart from others. It is able to run tests concurrently, enforces the writing of atomic tests and includes TypeScript definitions. One of the key features it has is Magic Assert, wherein only certain values are displayed and highlighted for better viewing and easier comparison. It... -
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
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Passive-Network-Scan-L2/3
Passive network discovery tool focused on Layer 2 and Layer 3 packets
Passive-Network-Scan-L2/3 is a lightweight, passive network discovery tool that listens on a network interface in promiscuous mode and collects Layer 2 and Layer 3 signalling (ARP, STP, DHCP, mDNS, SSDP). It aggregates discovered hosts by MAC address, attempts to measure passive RTTs for request/response protocols, maintains per-protocol RTT histories and simple service hints, and can emit structured events and a final table in JSON or CSV formats. -
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Ollama Telegram Bot
Ollama Telegram bot, with advanced configuration
Ollama Telegram Bot is a Python-based Telegram bot that enables users to interact with locally hosted large language models through a familiar messaging interface. The project is designed to provide a simple but configurable way to bring AI chat capabilities into Telegram, supporting both individual and group conversations. It includes access control features such as user whitelists and admin roles, allowing fine-grained control over who can interact with the bot and manage its behavior. The bot connects to a local or remote Ollama server, enabling users to run models on their own hardware while maintaining full privacy. ... -
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App Store Screenshots Generator
End to end app store screenshot creation using AI
...It works by guiding developers through a structured prompt process where they describe their app’s features, branding, and style preferences, and then automatically builds a screenshot generation system using a Next.js-based framework. The tool emphasizes persuasive design, treating screenshots as advertisements with strong copywriting and visual hierarchy rather than simple previews of functionality. It supports multiple device resolutions and exports assets in all required Apple formats, significantly reducing the manual effort typically involved in App Store submission preparation. The system also includes localization capabilities, enabling developers to create region-specific screenshot sets with translated copy and layout adjustments. -
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BeeAI Framework
Build production-ready AI agents in both Python and Typescript
BeeAI Framework is an open-source, production-grade toolkit designed for building intelligent AI agents and complex multi-agent systems that can reason, act, and collaborate to solve real-world problems at scale. It goes beyond simple prompt-based interactions by introducing rule-based governance and constraint enforcement, enabling developers to create agents with predictable and controllable behavior while still preserving advanced reasoning capabilities. The framework supports both Python and TypeScript with full feature parity, making it accessible to a wide range of developers and teams. ... -
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Interactive Machine Learning Experiments
Interactive Machine Learning experiments
...The project combines Jupyter or Colab notebooks with browser-based visual demos that allow users to see trained models operating in real time. Many experiments involve tasks such as image classification, object detection, gesture recognition, and simple generative models. The models are typically trained in Python using TensorFlow and then exported for interactive demonstrations in a web environment using JavaScript and TensorFlow.js. Because the project focuses on experimentation rather than production systems, it acts as a sandbox where developers can explore machine learning concepts and observe model behavior. ... -
Build Agents and Models on One PlatformGemini 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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kimuraframework
AI-first Ruby framework for building fast, flexible web scraping spide
...Kimurai can use AI-assisted extraction to identify where data resides in HTML pages, automatically generating selectors that are cached for future use so subsequent scraping runs operate with pure Ruby performance. Kimurai supports scraping both static and JavaScript-rendered websites by working with multiple engines, including headless browsers and simple HTTP-based approaches. Developers can also interact with pages using browser automation features such as form filling, clicking elements, or navigating through dynamic content. It includes tools for scheduling, parallel scraping, and structured data output, making it suitable for building reliable large-scale crawlers. -
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videodl
Lightweight Python tool for downloading videos from many platforms
Videodl is a lightweight video downloader implemented entirely in Python that allows users to retrieve videos from a wide range of online media platforms. It focuses on providing a fast and simple way to parse video pages and download media files, often prioritizing high-definition versions without watermarks when available. It supports numerous video platforms across both Chinese and international streaming ecosystems, enabling users to fetch content from many popular services through a unified interface. Videodl works by implementing platform-specific client modules that extract video information and download links from supported services. ... -
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LLM-Pruner
On the Structural Pruning of Large Language Models
...The framework relies on gradient-based analysis to determine which parameters contribute least to model performance, enabling targeted structural pruning rather than simple weight removal. After pruning, the framework applies lightweight fine-tuning methods such as LoRA to recover performance using relatively small datasets and short training times. -
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CAG
Cache-Augmented Generation: A Simple, Efficient Alternative to RAG
CAG, or Cache-Augmented Generation, is an experimental framework that explores an alternative architecture for integrating external knowledge into large language model responses. Traditional retrieval-augmented generation systems rely on real-time retrieval of documents from databases or vector stores during inference. CAG proposes a different approach by preloading relevant knowledge into the model’s context window and precomputing the model’s key-value cache before queries are processed.... -
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shadcn Taxonomy
An open source application built using the new router
...The project was created by the shadcn-ui ecosystem as an experiment to explore modern architecture patterns such as server components, the Next.js app router, and modular UI component design. Rather than serving as a simple template, Taxonomy acts as a real application example that includes authentication, subscription management, documentation pages, and blogging functionality. The application uses a modern development stack including TypeScript, Tailwind CSS, and UI components based on Radix UI to build accessible and responsive interfaces. It also integrates backend functionality through Prisma ORM and database services while supporting API routes and middleware for server-side logic. -
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dLLM
dLLM: Simple Diffusion Language Modeling
dLLM is an open-source framework designed to simplify the development, training, and evaluation of diffusion-based large language models. Unlike traditional autoregressive models that generate text sequentially token by token, diffusion language models generate text through an iterative denoising process that refines masked tokens over multiple steps. This approach allows models to reason over the entire sequence simultaneously and potentially produce more coherent outputs with bidirectional... -
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MaxText
A simple, performant and scalable Jax LLM
MaxText is a high-performance, highly scalable open-source framework designed to train and fine-tune large language models using the JAX ecosystem. The project acts as both a reference implementation and a practical training library that demonstrates best practices for building and scaling transformer-based language models on modern accelerator hardware. It is optimized to run efficiently on Google Cloud TPUs and GPUs, enabling researchers and engineers to train models ranging from small... -
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Agent Chat UI
Web app for interacting with any LangGraph agent (PY & TS) via a chat
Agent Chat UI is an open-source web application that provides a graphical interface for interacting with AI agents built using LangGraph and related frameworks. The project is implemented as a modern Next.js application and allows users to chat with agent workflows running on remote or local LangGraph servers. Through a simple configuration process, developers can connect the interface to a deployed agent by specifying the server URL, assistant identifier, and authentication credentials. Once connected, the interface enables real-time conversations where messages are sent to the agent and responses are streamed back to the chat interface. The project is designed to serve as a flexible frontend for agent-based AI systems, allowing developers to test and deploy conversational interfaces quickly. ... -
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AI Agents From Scratch
Demystify AI agents by building them yourself. Local LLMs
AI Agents from Scratch is an educational repository designed to teach developers how to build autonomous AI agents using large language models and modern AI frameworks. The project walks through the process of constructing agents step by step, beginning with simple prompt-based interactions and gradually introducing more advanced capabilities such as planning, tool use, and memory. The repository provides example implementations that demonstrate how language models can interact with external systems, perform reasoning tasks, and execute structured workflows. It focuses on explaining the architecture of agent systems rather than simply providing finished code, making it useful for developers who want to understand how AI agents actually work internally. ... -
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vLLM Semantic Router
System Level Intelligent Router for Mixture-of-Models at Cloud
...Instead of sending every prompt to the same model, the system analyzes the intent and reasoning requirements of the request and dynamically selects the most appropriate model to process it. This approach allows developers to combine multiple models with different strengths, such as lightweight models for simple queries and more advanced reasoning models for complex tasks. The router operates as an intelligent layer between users and model infrastructure, capturing signals from prompts, responses, and contextual data to improve decision-making. It can also integrate safety and monitoring mechanisms that detect issues such as jailbreak attempts, hallucinations, or sensitive information exposure. -
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CUDA Agent
Large-Scale Agentic RL for High-Performance CUDA Kernel Generation
...Its architecture combines large-scale data synthesis, a skill-augmented CUDA development environment, and long-horizon reinforcement learning to build intrinsic optimization capability rather than relying on simple post-hoc tuning. The system operates in a ReAct-style loop where the agent profiles baseline implementations, writes CUDA code, compiles it in a sandbox, and iteratively refines performance. CUDA-Agent has demonstrated strong benchmark results, achieving high pass rates and significant speedups compared with compiler baselines such as torch.compile. -
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Build with Claude
A single hub to find Claude Skills, Agents, Commands, Hooks, Plugins
...It serves as a one-stop index where users can browse curated agent modules for tasks like blockchain development, code analysis, DevOps, documentation generation, and much more — all designed to be installed directly into Claude Code using a simple plugin system. The repository includes an organized collection of community-maintained plugins, searchable by category, and offers clear instructions on how to add and install marketplace content within Claude Code environments. Alongside agents, Build with Claude features hooks that can trigger actions on events, slash commands that automate developer tasks, and skill packages that bundle reusable AI behaviors for common problems. -
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AI Engineering Hub
In-depth tutorials on LLMs, RAGs and real-world AI agent applications
...It includes more than 90 production-ready projects across skill levels, organized into beginner, intermediate, and advanced categories to guide users progressively from simple experiments to complex AI workflows. Projects range from OCR applications and local chatbot UIs to multimodal RAG systems and multi-agent automation pipelines, making the hub valuable both as a learning resource and as a practical reference. The repository provides in-depth notebooks, example code, and integration patterns that illustrate how to implement, adapt, and scale AI features in real applications. -
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Dash Data Agent
Self-learning data agent that grounds its answers in layers of content
Dash is a self-learning data agent built by the Agno AI community that generates grounded answers to English queries over structured data by synthesizing SQL and reasoning based on six layers of context, improving automatically with each run. It sidesteps common limitations of simple text-to-SQL agents by incorporating multiple context layers — including schema structure, human annotations, known query patterns, institutional knowledge from docs, machine-discovered error patterns, and live runtime context — to generate SQL queries that are both technically correct and semantically meaningful. The system then executes those queries against a database and interprets the results, returning human-friendly insights not just raw rows, while learning from errors and successes to reduce repeated mistakes. -
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Softaworks Agent Skills
A curated collection of skills for AI coding agents
...It packages broad categories of modular skills that help with development automation, documentation creation, planning, architecture, testing, and soft professional workflows. Beyond simple skills, it also includes agents and CLI slash commands that help developers automate common tasks such as pattern finding, diagram generation, requirement drafting, and daily standup preparation. The toolkit’s modular design follows the Agent Skills format, making it easy for users to install only what’s needed via CLI installers or plugin marketplaces. ... -
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NVIDIA Earth2Studio
Open-source deep-learning framework
...Users can extend Earth2Studio with optional model packs, advanced data interfaces, statistical operators, and backend integrations that support flexible workflows from simple tests to large-scale operational inference.