Open Source JavaScript Artificial Intelligence Software - Page 15
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JavaScript Artificial Intelligence Software
View 17349 business solutionsBrowse free open source JavaScript Artificial Intelligence Software and projects below. Use the toggles on the left to filter open source JavaScript Artificial Intelligence Software by OS, license, language, programming language, and project status.
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MCP UI
SDK for building interactive UI components over MCP for AI tools
mcp-ui is a software development kit designed to bring interactive user interface capabilities to applications built on the Model Context Protocol (MCP). It enables developers to create rich, dynamic UI components that can be delivered from an MCP server and rendered seamlessly by a compatible client. Instead of returning only text responses, tools can provide structured UI resources such as HTML or remote-rendered components, allowing more engaging and functional interactions. mcp-ui introduces a standardized approach where tools and their associated interfaces are linked through metadata, enabling clients to automatically discover and display the correct UI. It includes both client-side and server-side SDKs, making it possible to define UI elements on the backend and handle user interactions on the frontend. It supports multiple programming environments, including TypeScript, Python, and Ruby, broadening its accessibility for developers. -
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MITRE Annotation Toolkit
A toolkit for managing and manipulating text annotations
The MITRE Annotation Toolkit (MAT) is a suite of tools which can be used for automated and human tagging of annotations. Annotation is a process, used mostly by researchers in natural language processing, of enhancing documents with information about the various phrase types the documents contain. MAT supports both UI interaction and command-line interaction, and provides various levels of control over the overall annotation process. It can be customized for specific tasks (e.g., named entity identification, de-identification of medical records). The goal of MAT is not to help you configure your training engine (in the default case, the Carafe CRF system) to achieve the best possible performance on your data. MAT is for "everything else": all the tools you end up wishing you had. -
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Machine Learning Yearning
Machine Learning Yearning
Artificial intelligence, machine learning and deep learning are transforming numerous industries. Professor Andrew Ng is currently writing a book on how to build machine learning projects. The point of this book is not to teach traditional machine learning algorithms, but to teach you how to make machine learning algorithms work. Some technical courses in AI will give you a tool, and this book will teach you how to use those tools. If you aspire to be a technical leader in AI and want to learn how to set a direction for your team, this book will help. This book is still a sample draft. In order to make the corresponding Chinese content available to you as soon as possible, the translation time is rushed, and some of the content is inevitably oversight. You can enter the warehouse address through the Github icon in the upper right corner, and make certain modification suggestions. -
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Machine-Learning-Flappy-Bird
Machine Learning for Flappy Bird using Neural Network
Machine-Learning-Flappy-Bird is an educational machine learning project that demonstrates how an artificial intelligence agent can learn to play the Flappy Bird game using neural networks and evolutionary algorithms. The system simulates a population of birds that each possess their own neural network, which acts as a decision-making controller during gameplay. The neural network receives input features representing the bird’s position relative to the next obstacle and determines whether the bird should flap or remain idle. Over successive generations, a genetic algorithm evolves the neural networks by selecting high-performing agents and recombining their parameters to produce improved offspring. This process allows the AI agents to gradually learn better strategies for navigating the obstacles and surviving longer in the game environment. -
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Magnitude
Vision AI browser agent for automation, testing, and extraction
Browser Agent by Magnitude is an open source, vision-first browser automation framework that enables users to control web interfaces using natural language instructions. It leverages visually grounded AI models to interpret and interact with web pages based on what is seen on the screen rather than relying solely on the DOM structure. This approach allows the agent to generalize better across complex and modern websites, making it more robust than traditional selector-based automation tools. Browser Agent by Magnitude supports a wide range of capabilities including navigation, interaction, data extraction, and automated verification through built-in testing features. Developers can use it to automate repetitive web tasks, integrate services without APIs, or build advanced browser-based agents. It also provides flexible abstraction levels, allowing both high-level task execution and precise low-level control of actions like mouse movements and keyboard input. -
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Manifold ML
A model-agnostic visual debugging tool for machine learning
Manifold is a model-agnostic visual debugging tool for machine learning. Understanding ML model performance and behavior is a non-trivial process, given the intrisic opacity of ML algorithms. Performance summary statistics such as AUC, RMSE, and others are not instructive enough to identify what went wrong with a model or how to improve it. As a visual analytics tool, Manifold allows ML practitioners to look beyond overall summary metrics to detect which subset of data a model is inaccurately predicting. Manifold also explains the potential cause of poor model performance by surfacing the feature distribution difference between better and worse-performing subsets of data. -
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Markdownify MCP Server
Convert files and web content into clean, usable Markdown easily
Markdownify MCP is a Model Context Protocol server that converts many types of files and web content into clean Markdown. It supports formats such as PDFs, images, audio with transcription, DOCX, XLSX, and PPTX, along with web sources like YouTube transcripts, Bing results, and general webpages. Markdownify MCP is designed to simplify content extraction and make data easier to read, share, and reuse in structured workflows. Developers can install dependencies, build, and run the server locally, then extend functionality by modifying its TypeScript-based tools and server logic. It also allows retrieval of existing Markdown files, making it useful for documentation, research, and AI-assisted workflows. By standardizing content into Markdown, it helps unify inputs across different sources for better processing and integration with AI tools and developer environments. -
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Medical decision making algorithm tool. Visual design tool generates Tcl/Tk code. Non-programmers can design interactive algorithms. Generates notes for inclusion in medical record. Runs freestanding or in Tcl Plugin.
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MediaGlyphs
international glyph-based auxlang
MediaGlyphs: an international language based on multimedia ideograms. It allows to read, think or type in your own language sentences written with the shared mediaglyphs: a common writing system for the world, Simple Unambiguous Neutral & Universal. -
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MetaErg
Metagenome Annotation Pipeline
MetaErg is a stand-alone and fully automated metagenome and metaproteome annotation pipeline published at: https://www.frontiersin.org/articles/10.3389/fgene.2019.00999/full. If you are using this pipeline for your work, please cite: Dong X and Strous M (2019) An Integrated Pipeline for Annotation and Visualization of Metagenomic Contigs. Front. Genet. 10:999. doi: 10.3389/fgene.2019.00999 The instructions on configuring and running the MetaErg pipeline is available at GitHub repository: https://github.com/xiaoli-dong/metaerg -
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Microsoft Bot Framework SDK
Tool for building conversation applications
Bot Framework provides the most comprehensive experience for building conversation applications. With the Bot Framework SDK, developers can build bots that converse free-form or with guided interactions including using simple text or rich cards that contain text, images, and action buttons. Developers can model and build sophisticated conversation using their favorite programming languages including C#, JS, Python and Java or using Bot Framework Composer, an open-source, visual authoring canvas for developers and multi-disciplinary teams to design and build conversational experiences with Language Understanding, QnA Maker and sophisticated composition of bot replies (Language Generation). Checkout the Bot Framework ecosystem section to learn more about other tooling and services related to the Bot Framework SDK. The Bot Framework SDK v4 is an open source SDK that enable developers to model and build sophisticated conversation using their favorite programming language. -
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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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MindSearch
An LLM-based Multi-agent Framework of Web Search Engine
MindSearch is an AI-powered search engine based on large language models (LLMs) designed for deep semantic search and retrieval. It leverages InternLM's language model to understand complex queries and retrieve highly relevant answers from large datasets. -
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Mito
AI-powered Jupyter spreadsheet that converts workflows into Python
Mito is an open source set of Jupyter extensions designed to speed up Python workflows and data analysis. It combines a spreadsheet-style interface with AI-assisted coding, allowing users to explore, clean, and transform data without switching tools. Mito includes a context-aware AI assistant that helps generate code, debug errors, and guide workflows directly inside Jupyter. Its spreadsheet layer supports familiar functions such as filters, pivot tables, and formulas, while automatically converting every action into production-ready Python code. This removes the need to manually translate spreadsheet logic into scripts. Mito also integrates with tools like Streamlit and Dash, enabling users to embed interactive spreadsheet functionality into apps with minimal setup. Built for analysts, developers, and teams, it simplifies automation, reduces repetitive tasks, and accelerates the transition from data exploration to reusable code. -
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Model Context Protocol (MCP) Servers
Model Context Protocol Servers
The Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you’re building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need. -
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Model Explorer
A modern model graph visualizer and debugger
Model Explorer is a visual tool for exploring, debugging, and optimizing ML models deployed on edge devices. Developed by Google AI Edge, it offers a browser-based interface to inspect layer-wise performance, memory usage, and inference timing of TensorFlow Lite and other supported models. It’s a powerful utility for developers optimizing models for constrained environments. -
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MongoDB Lens
MongoDB Lens: Full Featured MCP Server for MongoDB Databases
MongoDB Lens is a local Model Context Protocol (MCP) server offering full-featured access to MongoDB databases using natural language via large language models (LLMs). It enables users to perform queries, run aggregations, optimize performance, and more through conversational interactions. -
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Monk Computer Vision
A low code unified framework for computer vision and deep learning
Monk is an open source low code programming environment to reduce the cognitive load faced by entry level programmers while catering to the needs of Expert Deep Learning engineers. There are three libraries in this opensource set. - Monk Classiciation- https://monkai.org. A Unified wrapper over major deep learning frameworks. Our core focus area is at the intersection of Computer Vision and Deep Learning algorithms. - Monk Object Detection - https://github.com/Tessellate-Imaging/Monk_Object_Detection. Monk object detection is our take on assembling state of the art object detection, image segmentation, pose estimation algorithms at one place, making them low code and easily configurable on any machine. - Monk GUI - https://github.com/Tessellate-Imaging/Monk_Gui. An interface over these low code tools for non coders. -
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Multi-Page Automation
Browser extension designed to automate OAuth authentication
Multi-Page Automation is a browser extension designed to automate OAuth authentication flows for AI coding tools and integrations. It simplifies the process of obtaining and managing authentication tokens required to access external APIs. The extension handles login steps, token retrieval, and session management automatically. It is particularly useful for developers working with AI tools that require repeated authentication. The project reduces friction in development workflows by eliminating manual login processes. It integrates directly into browser environments for ease of use. Overall, it streamlines secure access to external services in automated workflows. -
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NLP.js
An NLP library for building bots
NLP.js is an NLP library for building bots, with entity extraction, sentiment analysis, automatic language identifier, and much more. "NLP.js" is a general natural language utility for nodejs. Search the best substring of a string with less Levenshtein distance to a given pattern. Get stemmers and tokenizers for several languages. Sentiment Analysis for phrases (with negation support). Named Entity Recognition and management, multi-language support, and acceptance of similar strings, so the introduced text does not need to be exact. Natural Language Processing Classifier, to classify an utterance into intents. NLP Manager, a tool able to manage several languages, the Named Entities for each language, the utterances, and intents for the training of the classifier, and for a given utterance return the entity extraction, the intent classification and the sentiment analysis. -
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NLUX
The powerful Conversational AI JavaScript Library
NLUX, short for Natural Language User Experience, is an open-source JavaScript and React library designed to simplify the creation of conversational interfaces powered by large language models. The library provides developers with prebuilt components and utilities that make it easy to integrate chat-based AI functionality into web applications. By using NLUX, developers can connect their applications to models such as ChatGPT or other LLM providers and create interactive conversational interfaces with minimal setup. The framework supports both React components and standalone JavaScript implementations, giving developers flexibility in how they integrate AI functionality into existing applications. NLUX focuses on improving the user experience of AI-powered systems by providing structured messaging interfaces, streaming responses, and customizable conversational UI elements. -
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The first 3d search engine for text. Javascript only. Work in all browsers. Ajax downloads new words (and links between them) as you move mouse to control AI to learn what you're looking for (in context) and put it on screen. Includes Wikipedia data
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Turn-based strategy game for developers/technical experienced users, based on neural networks, algorithmic programming languages and other techniques.
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Node ChatGPT API
A client implementation for ChatGPT and Bing AI
A client implementation for ChatGPT and Bing AI. Available as a Node.js module, REST API server, and CLI app. Support for the official ChatGPT model has been added! You can now use the gpt-3.5-turbo model with the official OpenAI API, using ChatGPTClient. This is the same model that ChatGPT uses, and it's the most powerful model available right now. Usage of this model is not free, however it is 10x cheaper than text-davinci-003. The default model used in ChatGPTClient is now gpt-3.5-turbo. You can still set userLabel, chatGptLabel and promptPrefix (system instructions) as usual. Support for the official ChatGPT underlying model, gpt-3.5-turbo, via OpenAI's API. Replicates chat threads from the official ChatGPT website (with conversation IDs and message IDs), with persistent conversations using Keyv. Conversations are stored in memory by default, but you can optionally install a storage adapter to persist conversations to a database. -
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Node.js Client For NLP Cloud
NLP Cloud serves high performance pre-trained or custom models
This is the Node.js client (with Typescript types) for the NLP Cloud API. NLP Cloud serves high-performance pre-trained or custom models for NER, sentiment analysis, classification, summarization, dialogue summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and spelling correction, keywords and keyphrases extraction, text generation, image generation, blog post generation, text generation, question answering, automatic speech recognition, machine translation, language detection, semantic search, semantic similarity, tokenization, POS tagging, embeddings, and dependency parsing. It is ready for production, and served through a REST API. You can either use the NLP Cloud pre-trained models, fine-tune your own models, or deploy your own models.
