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Showing 1051 open source projects for "support"
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ralph-loop-agent
Continuous Autonomy for the AI SDK
ralph-loop-agent is an experimental autonomous agent framework from Vercel Labs that brings continuous autonomy to the AI SDK, enabling AI solutions to perform long-running, iterative tasks without manual stop/start intervention. Rather than simply answering a single request and stopping, Ralph Loop implements a loop control architecture that allows an agent to repeatedly evaluate its progress, adjust its approach, and continue working toward a defined completion criteria until tasks are... -
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Figma Code Connect
A tool for connecting your design system components
Figma Code Connect is an open-source tool that enhances collaboration between designers and developers by synchronizing design components with source code in real time. Instead of treating design files and codebases as separate artifacts, it creates a continuous link so when a designer updates a UI element in Figma, developers see corresponding code changes or annotations immediately, making handoffs more precise and frictionless. The system supports multiple frameworks and languages,... -
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Menubar Electron
High level way to create menubar desktop applications with electron
Menubar Electron is a lightweight JavaScript library for creating desktop applications with persistent menu bar (Mac) or system tray (Windows/Linux) icons/interfaces, allowing developers to build utility apps that live in the user’s system bar and open a small window or popup when clicked. It serves as a wrapper around frameworks like Electron or Node GUI backends, abstracting common tasks such as positioning the popup window, handling click events, and integrating native tray interactions... -
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Visual Blocks
Visual Blocks for ML is a Google visual programming framework
Visual Blocks is a node-based, in-browser environment for building AI and data-processing workflows with drag-and-drop components. It lets you connect sources, transforms, models, and visualizers into a live graph, so changes propagate instantly and results are observable without writing glue code. Under the hood it leans on web-friendly runtimes (e.g., WebGPU/WebGL/WebNN or TensorFlow.js backends) to execute pipelines locally, which is great for demos, teaching, and privacy-sensitive... -
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Claude Code Subagents Command Collection
Claude Code Subagents & Commands Collection + CLI Tool
...It includes a CLI helper and documentation site that streamline installation, customization, and authoring of your own agents. The project’s framing mirrors modern software teams—delegate tasks to experts that can run in parallel under Claude’s subagent support. Frequent updates and community contributions keep the catalog current with new roles and best practices. -
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hmpl
Server-oriented customizable templating for JavaScript
...Reduce the size of your javascript files and display the same UI as if it was written in a modern framework. Using HMPL, you can multiply reduce the size of the application bundle. Full customization of the request based on the modern fetch standard, as well as support for all the functionality necessary for modern work in applications (request indicator, sending by event, automatic generation of body for the form, caching) and the syntax of the object in the markup, which requires a minimum number of characters, will help to build interaction with the server and client as efficiently as possible. -
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Ax
Build LLM powered Agents and "Agentic workflows"
Build intelligent agents quickly — inspired by the power of "Agentic workflows" and the Stanford DSPy paper. Seamlessly integrates with multiple LLMs and VectorDBs to build RAG pipelines or collaborative agents that can solve complex problems. Advanced features streaming validation, multi-modal DSPy, etc. We've renamed from "llmclient" to "ax" to highlight our focus on powering agentic workflows. We agree with many experts like "Andrew Ng" that agentic workflows are the key to unlocking the... -
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URQL GraphQL
GraphQL client with which you add on features like normalized caching
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 GraphQL, urql becomes your primary data layer and can handle content-heavy pages through "Document Caching" as well as dynamic and data-heavy apps through "Normalized Caching". urql can be understood as a collection of connected parts and packages. ... -
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Remix Project
Compiler and IDE that enables users to build Ethereum contracts
...It fosters a fast development cycle and has a rich set of plugins with intuitive GUIs. The IDE comes in 2 flavors and a VSCode extension. Supported browsers: Firefox v100.0.1 & Chrome v101.0.4951.64. No support for Remix's use on tablets or smartphones or telephones. The gh-pages branch of remix-live always has the latest stable build of Remix. It contains a ZIP file with the entire build. Download it to use offline. It contains the latest supported version of Solidity available at the time of the packaging. Other compiler versions can be used online only. -
Go From AI Idea to AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
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linaria
Zero-runtime CSS in JS library
Write CSS in JS and get real CSS files during build. Use dynamic prop-based styles with the React bindings and have them transpiled to CSS variables automatically. Great productivity with source maps and linting support. Write CSS in JS, but with zero runtime, CSS is extracted to CSS files during build. Use dynamic prop-based styles with the React bindings, uses CSS variables behind the scenes. Optionally use any CSS preprocessor such as Sass or PostCSS. Easily find where the style was defined with CSS source maps. Linaria currently supports webpack and Rollup to extract the CSS at build time. ... -
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TypeGraphQL
Create GraphQL schema and resolvers with TypeScript
...Use features like automatic validation, authorization guards, dependency injection, and plenty more. Implement queries and mutations as normal class methods! Dependency injection support and decorators abstraction provide great separation of business logic from the underlying transport layer. That gives you really easy testability, so you can just provide mocks of dependencies to prevent side effects and unit test your resolvers like simple services whose methods only take some parameters. -
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react-admin
Framework for building B2B applications running in the browser
A frontend Framework for building B2B applications running in the browser on top of REST/GraphQL APIs, using ES6, React and Material Design. React-admin supports most REST and GraphQL dialects, and writing your own adapter takes minutes. Choose among many variants, or replace any component by your own. Build API-based B2B applications using modern React and Material Design. Your first admin only needs 13 lines of code. Adapts to any backend (REST, GraphQL, SOAP, etc.). Powered by... -
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Claude Code Video Vision
Give Claude the ability to watch and understand videos
Claude Video Vision is a plugin designed for Claude Code that enables large language models to process and understand video content by transforming it into multimodal inputs the model can reason over. Instead of attempting to directly interpret raw video streams, the system extracts key frames using tools like ffmpeg and processes audio through transcription engines, converting both visual and auditory signals into structured inputs for the model. The result is a perception layer that feeds... -
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DeepAudit
AI multi-agent platform for automated code security auditing system
DeepAudit is an open source code security auditing platform that uses a multi-agent architecture to analyze and identify vulnerabilities in software projects. Instead of relying solely on traditional static analysis, it simulates the reasoning process of security experts through coordinated agents responsible for orchestration, reconnaissance, analysis, and verification. DeepAudit performs deep semantic understanding of code, enabling it to detect complex vulnerabilities that span multiple... -
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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. The framework... -
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Nanocoder
A beautiful local-first coding agent running in your terminal
Nanocoder is an open-source, local-first coding assistant that runs in the command line and allows developers to use AI models to assist with programming tasks directly from their terminal environment. The tool is designed as a privacy-focused alternative to proprietary AI coding assistants, allowing users to run local models or connect to external APIs while keeping full control over their data and development workflow. Built with TypeScript and distributed as a CLI application, nanocoder... -
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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... -
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Farfalle
AI search engine - self-host with local or cloud LLMs
Farfalle is an open-source AI-powered search engine designed to provide an answer-centric search experience similar to modern conversational search systems. The project integrates large language models with multiple search APIs so that the system can gather information from external sources and synthesize responses into concise answers. It can run either with local language models or with cloud-based providers, allowing developers to deploy it privately or integrate with hosted AI services.... -
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Actionbook
Browser action engine for AI agents. 10× faster, resilient by design
...This design makes browsing up to 10× faster and far more resilient than ad-hoc approaches that break on minor page changes, because the action manuals codify expected flows and DOM targets. It provides multiple integration paths — a Rust-based CLI, MCP server support for AI IDEs, and a JavaScript SDK — so developers can plug it into a wide range of agent pipelines and toolchains. -
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Acontext
Context data platform for building observable, self-learning AI agents
Acontext is a cloud-native context data platform designed to support the development and operation of advanced AI agents. It provides a unified system to store and manage contexts, multimodal messages, artifacts, and task workflows, enabling developers to engineer context effectively for their agent products. The platform observes agent tasks and user feedback in real time, offering robust observability into workflows and helping teams understand how agents perform over time. -
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Chatbot UI
AI chat for any model
Chatbot UI is an open-source, full-featured chat interface for AI models that aims to lower the barrier for anyone wanting to run their own AI-powered chatbot — whether using remote LLM APIs or local/self-hosted models. It bundles a modern frontend (Next.js + TypeScript + Tailwind) with a backend (Supabase by default) for persistent storage of chats, history, and user settings, replacing earlier local-storage-only approaches. The project supports multiple models/providers (e.g. OpenAI, local... -
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OpenAI CS Agents Demo
Demo of a customer service use case implemented with the OpenAI Agents
This repository is a customer service agent demo built using the OpenAI Agents SDK to showcase how to build a production-style conversational assistant for use cases like airline customer support. It consists of two major parts: a Python backend that orchestrates agent logic (tool calls, handoffs, memory, routing) and a Next.js UI for chat interaction and visualizing agent state. The demo covers tasks you’d expect in customer service: changing flights, checking status, answering FAQs, etc. It shows how multiple subagents can be coordinated under a triage agent that decides which specialized agent should handle a given request. ... -
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GraphQL Tools
Build, mock, and stitch a GraphQL schema using the schema language
GraphQL Tools is a set of NPM packages and an opinionated structure for how to build a GraphQL schema and resolvers in JavaScript, following the GraphQL-first development workflow. Use the GraphQL schema definition language to generate a schema with full support for resolvers, interfaces, unions, and custom scalars. With GraphQL Tools, you can mock your GraphQL API with fine-grained per-type mocking for fast prototyping without any data sources. Automatically stitch multiple schemas together into one larger API in a simple, fast and powerful way. You can develop your JavaScript-based GraphQL API with graphql-tools and GraphQL Yoga together: One to write the schema and resolver code, and the other to connect it to a web server. ... -
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NorthStar
Simplifies your work and ensures consistent, predictable experiences
...Using a shared design language, screen flows and standardized components means they can quickly understand how they should interact with new UI experiences and features, decreasing the effort associated with feature adoption and confusion. NorthStar provides out-of-the-box support for accessibility, responsive design, and broad browser coverage. -
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Framelink MCP for Figma
MCP server enabling AI coding tools to access Figma design data
...This transformation reduces unnecessary metadata and focuses on the most relevant design attributes, helping AI coding agents produce more accurate UI implementations. Developers can integrate the server with compatible tools such as AI-assisted IDE environments that support MCP-based integrations. When a developer provides a Figma file, frame, or element reference, the AI client can request design data from the server and generate code based on that structure.
