Open Source TypeScript Artificial Intelligence Software - Page 4
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TypeScript Artificial Intelligence Software
View 13574 business solutionsBrowse free open source TypeScript Artificial Intelligence Software and projects below. Use the toggles on the left to filter open source TypeScript Artificial Intelligence Software by OS, license, language, programming language, and project status.
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Collect! is a highly configurable debt collection softwareThe flexible & scalable debt collection software built to automate your workflow. From startup to enterprise, we have the solution for you.
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Iris Powered By Generali - Iris puts your customer in control of their identity.Iris Identity Protection API sends identity monitoring and alerts data into your existing digital environment – an ideal solution for businesses that are looking to offer their customers identity protection services without having to build a new product or app from scratch.
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Gemini Next Chat
Deploy your private Gemini application for free with one click
Gemini Next Chat is an open-source web application that allows you to deploy your own private chat interface powered by Google’s Gemini models (e.g., Gemini 1.5, Gemini 2.0, etc.). It is built with Next.js/TypeScript and targets developers and hobbyists who want a self-hosted solution for interacting with advanced multimodal models (text, image, voice). It supports features like image recognition, voice-based conversation, plugins (web search, ArXiv search, weather, etc.), and client apps (tray app) for greater convenience. The project emphasizes “one-click” deployment, aiming to make it easy to spin up a custom chat front end without deep infra-setup. It’s licensed under MIT and has an active community of contributors; documentation and release notes note support for newer features like mixed image+text generation. The README warns of security configurations and customizing environment variables for model access. -
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MCP Browser Kit
MCP Server for interacting with manifest v2 compatible browsers
An MCP server that integrates with browser extensions to enable AI assistants to interact with the user's browser, allowing actions like starring repositories on GitHub through natural language commands. -
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Midscene
Vision-based AI framework for cross-platform UI automation tasks
Midscene.js is an open source AI-driven UI automation framework designed to control user interfaces across multiple platforms using natural language instructions. 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. Midscene also provides debugging and development tools. -
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Operit AI
Powerful Android AI agent with tools, automation, and Linux shell
Operit is a full-featured AI assistant and agent platform designed specifically for Android devices, aiming to go far beyond traditional chat-based interfaces. It integrates deep system-level capabilities with a wide range of tools, allowing the AI to perform real tasks such as file management, automation, and system control directly on the device. A standout aspect of the project is its built-in Ubuntu 24 environment, which enables users to run Linux commands, scripts, and development tools in a mobile context. Operit supports both local and remote AI models, including offline execution through frameworks like llama.cpp and MNN, helping preserve user privacy while maintaining flexibility. Operit also includes an intelligent memory system that stores, organizes, and retrieves user interactions to provide more personalized and context-aware responses. In addition, it offers workflow automation, plugin extensibility, & a rich tool ecosystem, making it suitable for advanced productivity. -
The Most Powerful Software Platform for EHSQ and ESG ManagementChoose from a complete set of software solutions across EHSQ that address all aspects of top performing Environmental, Health and Safety, and Quality management programs.
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Read Frog
Open Source Immersive Translate
Read Frog is an open-source browser extension designed to transform everyday web reading into an immersive language learning experience powered by artificial intelligence. The tool integrates translation, contextual explanations, and content analysis directly into the browsing workflow so users can learn languages naturally while reading authentic online content. Instead of forcing learners to switch between translation tools and the original text, the extension displays translations alongside the source language, making comprehension immediate and continuous. The system automatically extracts the main content of an article using intelligent parsing techniques, allowing users to focus on the most relevant text without distractions. AI models are used to generate summaries, introductions, and explanations for words, phrases, and sentences based on the learner’s language level, making the experience personalized and adaptive. -
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Auto-Photoshop-StableDiffusion-Plugin
Plug-in that makes it easy to generate stable diffusion images
Auto-Photoshop-StableDiffusion-Plugin is an open-source extension that seamlessly integrates Stable Diffusion image generation directly into Adobe Photoshop, allowing artists and designers to generate, edit, and refine AI-generated imagery without leaving the Photoshop environment. It bridges Photoshop with popular diffusion backends like AUTOMATIC1111 or ComfyUI, effectively embedding powerful generative tools into a familiar creative workflow so users can apply AI creation to layers, selections, and masks while retaining Photoshop’s full editing capabilities. With this plugin, users can generate new visuals from text prompts, use selectable areas for inpainting or outpainting, and adjust images using AI features while still leveraging traditional design tools such as brushes, filters, and adjustment layers. The integration dramatically reduces context switching between standalone AI tools and professional design software, empowering more efficient experimentation and iteration. -
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Basic Memory
Persistent AI memory using local Markdown knowledge graphs
Basic Memory is an open source knowledge system that turns AI conversations into persistent, structured knowledge you control. Instead of losing context after each chat, it stores information as simple Markdown files on your device, allowing both you and AI to read and write to the same knowledge base. It uses the Model Context Protocol (MCP) so compatible AI tools can access, update, and build on your notes across sessions. Basic Memory creates a semantic knowledge graph by linking related ideas, making it easier to retrieve, expand, and connect information over time. With a local-first design, your data stays private and portable, while optional cloud sync enables cross-device access. It combines simplicity with powerful indexing and search, giving you a flexible way to build long-term memory for projects, research, and workflows. -
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Dev Janitor
Your Vibe Coding Toolkit A cross-platform desktop application
Dev Janitor is an open-source developer productivity tool designed to automatically clean up stale, unused, or poorly maintained code patterns in a codebase, helping teams keep their repositories tidy without consuming engineering time manually pruning technical debt. The tool analyzes project files and identifies opportunities to perform cleanup tasks such as removing dead imports, fixing outdated syntax, simplifying redundant expressions, and consolidating duplicated logic, all while observing established conventions for the languages it supports. Through a pluggable rule system, it allows teams to enforce their own style guides or cleanup policies, enabling tailored automation that fits each codebase’s unique needs. It is built for integration into continuous integration and deployment (CI/CD) pipelines or pre-commit workflows, so cleanup suggestions can be surfaced and applied incrementally rather than as a massive refactor. -
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Harbor LLM
Run a full local LLM stack with one command using Docker
Harbor is an open source, containerized toolkit designed to simplify running local large language model (LLM) environments. It combines a CLI and companion app to launch backends, frontends, and supporting services with minimal setup. With a single command, users can start preconfigured tools like Ollama and Open WebUI, enabling chat, workflows, and integrations immediately. Harbor supports multiple inference engines, including llama.cpp and vLLM, and connects them seamlessly to user interfaces. It also includes tools for web retrieval, image generation, voice interaction, and workflow automation. Built on Docker, Harbor allows services to run in isolated containers while communicating over a local network. It is intended for local development and experimentation rather than production deployment, giving developers a flexible way to explore AI systems, test configurations, and manage complex LLM stacks without manual wiring or setup overhead. -
AestheticsPro Medical Spa SoftwareAestheticsPro is the most complete Aesthetics Software on the market today. HIPAA Cloud Compliant with electronic charting, integrated POS, targeted marketing and results driven reporting; AestheticsPro delivers the tools you need to manage your medical spa business. It is our mission To Provide an All-in-One Cutting Edge Software to the Aesthetics Industry.
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LLM Wiki
Open Source Implementation of Karpathy's LLM Wiki
LLM Wiki is a knowledge management and documentation system designed to organize, generate, and maintain structured information using large language models. It allows users to create interconnected knowledge bases that function similarly to a wiki but are enhanced with AI-driven content generation and summarization. The system emphasizes linking and context, enabling information to be connected across pages and topics for better navigation and understanding. It likely includes features for automatic content updates, ensuring that information remains relevant as new data becomes available. The architecture supports both manual editing and automated generation, providing flexibility in how knowledge is curated. It is particularly useful for teams or individuals managing large amounts of information across domains. Overall, llmwiki transforms static documentation into a dynamic, AI-assisted knowledge system. -
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OpenClaw CN
The Chinese version of OpenClaw
OpenClaw-CN is a Chinese language community adaptation and localization of the OpenClaw project, focused on making a powerful open-source agent framework usable and understandable for Chinese-speaking developers. It includes translated documentation, localized examples, and language-specific nuances so that developers in the Chinese ecosystem can adopt and contribute without a language barrier. The repository mirrors the structure of the upstream project but adds Chinese translations of core workflows, prompts, guidelines, and best practices for building multi-agent systems or AI applications. Beyond simple translation, the project often curates region-specific integrations or tooling recommendations that resonate with local developer environments and platforms. It helps accelerate adoption by providing readable guides, sample configurations, and annotated code that aligns with Chinese developer preferences and tooling conventions. -
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OpenClaw Control Center
Turn OpenClaw from a black box into a local control center
OpenClaw Control Center is a centralized management interface designed to oversee, configure, and monitor agent-based systems, particularly those built within the OpenClaw ecosystem. It provides a control layer that allows users to interact with agents, track their performance, and adjust operational parameters in real time. The system is likely built with usability in mind, offering dashboards or visualization tools that make complex agent behaviors easier to understand and manage. It may also include logging, debugging, and orchestration features that support large-scale deployments of autonomous systems. The project emphasizes coordination and observability, ensuring that users maintain control over distributed agent processes. Overall, it functions as the operational backbone for managing advanced AI agent infrastructures. -
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Short Video Factory
AI tool for automatic batch short video creation and editing
Short Video Factory is an open source desktop application designed to simplify the creation of short-form videos using AI-driven automation. It enables users to generate product marketing clips and general content videos by combining simple prompt-based input with pre-prepared media assets. Short Video Factory integrates multiple stages of video production, including script generation, voice synthesis, video editing, and subtitle effects, into a single streamlined workflow. By leveraging AI technologies, it significantly reduces the manual effort required to produce high-quality short videos at scale. Short Video Factory supports batch processing, allowing users to automatically generate multiple videos based on predefined templates and configurations. It is built as a cross-platform desktop solution with a focus on usability, making it accessible to both beginners and content creators who need fast turnaround times. -
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Telegram Search
AI-powered Telegram chat backup and semantic search tool system
Telegram Search is a self-hosted tool designed to export, back up, and intelligently search Telegram chat histories using modern AI techniques. It addresses the limitations of Telegram’s native search by enabling accurate retrieval of messages across languages through advanced tokenization and semantic understanding. Telegram Search processes chat data into searchable formats, including vector embeddings, which allow users to perform fuzzy and meaning-based searches instead of relying solely on exact keyword matches. It supports continuous synchronization of messages, ensuring that newly received chats are automatically indexed and available for querying. It also incorporates AI-driven capabilities such as contextual question answering and unread message summarization, allowing users to interact with their message history in a more natural way. Additionally, it provides media handling features, including backup and semantic image search, enhancing discoverability. -
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claude-devtools
A desktop app that reconstructs exactly what Claude Code did
claude-devtools is an open-source desktop observability tool designed to provide deep visibility into Claude Code sessions by reconstructing execution activity directly from local session logs. Rather than acting as a wrapper or modifying Claude Code behavior, the application passively reads the logs stored in the user’s environment and rebuilds a structured, searchable timeline of what actually occurred during each session. The tool was created to address the loss of detail in the standard CLI output, which often summarizes actions without exposing the full underlying operations. It surfaces granular information such as file reads, edits, tool calls, token consumption, and subagent activity, enabling developers to understand exactly how the AI interacted with their codebase. Because it runs entirely locally and makes no network calls, it requires no API keys or configuration and works with any previously recorded sessions. -
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n8n-MCP
A MCP for Claude Desktop / Claude Code / Windsurf / Cursor
n8n-mcp is a Model Context Protocol (MCP) server that turns the n8n workflow platform into a set of first-class, typed tools an AI assistant can understand and operate. It exposes structured knowledge of n8n nodes and operations so an agent can reason about workflows, parameters, and executions without scraping docs or guessing API shapes. The server focuses on making Claude Desktop (and other MCP-capable clients) “n8n-literate,” enabling tasks such as inspecting existing workflows, proposing node chains, and validating configuration before runs. It ships with organized resources and tool definitions that map cleanly to n8n’s ecosystem, improving reliability compared with ad-hoc prompt patterns. The project targets practical agent ops: safer mutations, better error reporting, and predictable behavior when automating or refactoring automations. Community posts highlight the goal of giving agents accurate knowledge of hundreds of n8n nodes and keeping that knowledge fresh as n8n evolves. -
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ALLWEONE
AI tool that generates custom presentations with real-time editing
Presentation AI by ALLWEONE is an open source tool that uses artificial intelligence to generate complete slide decks from a simple prompt. It helps users create professional presentations quickly, with support for customizable themes, layouts, and styles. You can define slide count, language, and tone, then review or edit the AI-generated outline before finalising. Slides are built in real time, allowing you to watch content develop as the system works. Presentation AI by ALLWEONE includes image generation, rich text editing, and drag-and-drop functionality for easy adjustments. It also supports presentation mode, so you can present directly within the app. Built with modern technologies like Next.js, React, and Tailwind CSS, it integrates AI services such as OpenAI for content generation. It is fully open source under the MIT licence, making it suitable for developers who want to customise or extend its capabilities. -
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Deta Surf
Personal AI Notebooks. Organize files & webpages and generate notes
Surf is an open-source AI-driven development tool designed to simplify the process of building and experimenting with artificial intelligence applications. The platform provides a streamlined development environment where developers can test models, run experiments, and deploy small AI services with minimal infrastructure overhead. It focuses on simplicity and speed, allowing developers to prototype ideas quickly without managing complex cloud configurations. Surf integrates modern AI workflows such as prompt-based applications, lightweight APIs, and automated deployment pipelines. The platform is particularly useful for developers who want to experiment with AI models locally while maintaining the option to deploy them in production environments later. Its architecture is designed to minimize setup complexity while still supporting scalable application structures. -
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Dify
One API for plugins and datasets, one interface for prompt engineering
Dify is an easy-to-use LLMOps platform designed to empower more people to create sustainable, AI-native applications. With visual orchestration for various application types, Dify offers out-of-the-box, ready-to-use applications that can also serve as Backend-as-a-Service APIs. Unify your development process with one API for plugins and datasets integration, and streamline your operations using a single interface for prompt engineering, visual analytics, and continuous improvement. Out-of-the-box web sites supporting form mode and chat conversation mode A single API encompassing plugin capabilities, context enhancement, and more, saving you backend coding effort Visual data analysis, log review, and annotation for applications -
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Emdash
Emdash is the Open-Source Agentic Development Environment
Emdash is an open-source agentic development environment that allows developers to orchestrate multiple AI coding agents in parallel within a unified desktop application. It introduces a new paradigm where coding tasks are delegated to independent AI agents, each operating in its own isolated Git worktree, enabling concurrent development workflows without conflicts. The platform is provider-agnostic, supporting a wide range of CLI-based AI coding tools such as Claude Code, Codex, and others, allowing developers to switch or combine models based on their needs. Emdash integrates deeply with development workflows by enabling users to pass tasks directly from issue trackers like GitHub, Jira, or Linear to agents, which can then generate code, run tests, and create pull requests automatically. It also supports remote development through SSH, allowing agents to operate on remote servers while maintaining the same interface and workflow. -
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Flowise
Drag & drop UI to build your customized LLM flow
Open source UI visual tool to build your customized LLM flow using LangchainJS, written in Node Typescript/Javascript. Conversational agent for a chat model which utilizes chat-specific prompts and buffer memory. Open source is the core of Flowise, and it will always be free for commercial and personal usage. Flowise support different environment variables to configure your instance. You can specify the following variables in the .env file inside the packages/server folder. -
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Hyprnote
Local-first AI Notepad for Private Meetings
Hyprnote is an open-source, privacy-first AI notepad app designed for taking notes during meetings—transcribing audio (microphone and system) and generating context-rich summaries using on-device AI models like Whisper and HyprLLM, all without any data leaving your machine.(turn0search7, turn0search1). Listens to your meetings while you write. Crafts smart summaries based on your quick notes. Runs completely offline using open-source models like Whisper or HyprLLM. Use approved third-party APIs like Gemini, Claude, or Azure-hosted GPT. -
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OpenClaw Office
OpenClaw Office is the visual monitoring and management frontend
OpenClaw Office is a visual monitoring and management interface designed for the OpenClaw multi-agent system, providing an immersive and interactive way to observe and control autonomous AI agents. It presents agent activity through a virtual office environment, where each agent is represented as an animated entity within a 2D or 3D workspace. The platform enables real-time visualization of agent states, interactions, and workflows, making complex multi-agent coordination easier to understand and debug. Users can observe communication flows between agents through visual connections, track token usage and operational costs, and analyze performance through integrated dashboards and charts. The system also includes live chat capabilities, allowing users to monitor conversations and tool calls as they occur. -
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Quadratic
Data science spreadsheet with Python & SQL
Quadratic enables your team to work together on data analysis to deliver better results, faster. You already know how to use a spreadsheet, but you’ve never had this much power before. Quadratic is a Web-based spreadsheet application that runs in the browser and as a native app (via Electron). Our goal is to build a spreadsheet that enables you to pull your data from its source (SaaS, Database, CSV, API, etc) and then work with that data using the most popular data science tools today (Python, Pandas, SQL, JS, Excel Formulas, etc). Quadratic has no environment to configure. The grid runs entirely in the browser with no backend service. This makes our grids completely portable and very easy to share. Quadratic has Python library support built-in. Bring the latest open-source tools directly to your spreadsheet. Quickly write code and see the output in full detail. No more squinting into a tiny terminal to see your data output. -
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XcodeBuildMCP
A Model Context Protocol (MCP) server
XcodeBuildMCP is a Model Context Protocol server that exposes Xcode operations as typed tools and resources so AI assistants can build, test, and debug iOS apps programmatically. It’s organized with a modern plugin architecture and workflow-scoped tool directories, covering common developer actions across projects, schemes, targets, simulators, real devices, and Swift packages. The server aims to be “agent-ready,” surfacing capabilities (build, clean, test, archive, install, run, log collection) with explicit schemas instead of brittle prompt instructions. It supports MCP transports suitable for local IDEs and service deployments, and pairs with a public website that positions it as a bridge between Xcode and autonomous assistants. Documentation and marketing materials emphasize end-to-end flows such as fixing build errors, managing simulators, and deploying to devices via natural-language requests.
