Open Source JavaScript Artificial Intelligence Software - Page 4
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JavaScript Artificial Intelligence Software
View 13050 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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Jimp
An image processing library written entirely in JavaScript for Node
An image processing library for Node written entirely in JavaScript, with zero native dependencies. If you're using this library with TypeScript the method of importing slightly differs from JavaScript. Instead of using require, you must import it with ES6 default import scheme. If you're using a web bundles (webpack, rollup, parcel) you can benefit from using the module build of jimp. Using the module build will allow your bundler to understand your code better and exclude things you aren't using. If you're using webpack you can set process.browser to true and your build of jimp will exclude certain parts, making it load faster. The static Jimp.read method takes the path to a file, URL, dimensions, a Jimp instance or a buffer and returns a Promise. In some cases, you need to pass additional parameters with an image's URL. -
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LLM Course
Course to get into Large Language Models (LLMs)
LLM Course is a hands-on, notebook-driven path for learning how large language models work in practice, from data curation to training, fine-tuning, evaluating, and deploying. It emphasizes reproducible experiments: each step is demonstrated with runnable code, clear dependencies, and references to commonly used open-source models and libraries. Learners get exposure to multiple adaptation strategies—LoRA/QLoRA, instruction fine-tuning, and alignment techniques—so they can choose approaches that fit their hardware and budgets. The materials also cover inference optimization and quantization to make serving LLMs feasible on commodity GPUs or even CPUs, which is crucial for side projects and startups. Evaluation is treated as a first-class topic, with examples of automatic and human-in-the-loop methods to catch regressions and verify quality beyond simple loss values. By the end, students have a mental model and a practical toolkit for iterating on datasets, training configs, etc. -
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Learn Prompting
This website is a free, open-source guide on prompt engineering
This website is a free, open-source guide on prompt engineering. Contributions are welcome! Harsh criticism is welcome too. We launched the first ever prompt hacking competition designed to enhance AI safety and education by challenging participants to outsmart large language models from May 5th to June 3rd! The competition featured 10 increasingly difficult levels of prompt hacking defenses and the chance to win over $35,000 in prizes. Coding is a great skill to learn alongside prompt engineering. We recommend learning Python, as it is a popular language for AI and machine learning. Be among the first to access the certification program as soon as it launches. -
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MCP Server Playwright
MCP server for browser automation using Playwright
An MCP (Model Context Protocol) server that leverages Playwright to provide browser automation capabilities, enabling large language models (LLMs) to interact with web pages, take screenshots, and execute JavaScript within a real browser environment. -
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MCP YouTube
A Model-Context Protocol Server for YouTube
The YouTube MCP Server uses yt-dlp to download subtitles from YouTube videos and connects to claude.ai via the Model Context Protocol. It enables AI assistants to summarize YouTube videos by accessing their subtitles. -
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Machine Learning Systems
Introduction to Machine Learning Systems
Machine Learning Systems is an open educational repository that serves as the source and learning stack for the Machine Learning Systems textbook, a project focused on teaching how to engineer AI systems that work reliably in real-world environments. Rather than concentrating only on model training, the material emphasizes the broader discipline of AI engineering, covering efficiency, reliability, deployment, and evaluation across the full lifecycle of intelligent systems. The repository includes textbook content, supporting labs, and companion tools such as TinyTorch to help learners move from theory to hands-on experimentation. Its mission is to establish AI systems engineering as a foundational discipline alongside traditional software and computer engineering. The project is structured to guide users through reading, building, and deploying workflows, including running labs on edge devices like Arduino and Raspberry Pi. -
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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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NSFWJS
Client-side indecent content checking powered by TensorFlow.js
NSFWJS is a simple JavaScript library that can quickly and quite accurately identify NSFW images, all in the client's browser. It is powered by TensorFlow.js and the NSFW detection model, and delivers around 90% accuracy that is improving each time. NSFWJS classifies images with percentages under five categories, namely: drawing and neutral, which are both safe for work; sexy, which includes sexually explicit images; and hentai and porn, which are pornographic drawings and images. NSFWJS offers a 'browserified' version, an NSFW filter web extension that filters out NSFW images from your browser, and also has a separate React Native app. -
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Node.js Telegram Bot API
Telegram Bot API for NodeJS
TelegramBot is an EventEmitter that emits several events. Message, received a new incoming Message of any kind. Depending on the properties of the Message, one of these events may ALSO be emitted, text, audio, document, photo, sticker, video, voice, contact, location, new_chat_members, left_chat_member, new_chat_title, new_chat_photo, delete_chat_photo, group_chat_created, game, pinned_message, poll, dice, migrate_from_chat_id, migrate_to_chat_id, channel_chat_created, supergroup_chat_created, successful_payment, invoice, video_note, etc. Its much better to listen a specific event rather than on message in order to stay safe from the content. Bot must be enabled on inline mode for receive some messages.T elegram only supports HTTPS connections to WebHooks. Therefore, in order to set a WebHook, you will need a SSL certificate. The library makes it easy to get started sending files. By default, you may provide a file-path and the library will handle reading it for you. -
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PyGPT
Open source personal AI Assistant for Linux, Windows and Mac
PyGPT is a desktop application that allows you to talk to OpenAI's LLM models such as GPT4 and GPT3 using your own computer and OpenAI API. It allows you to talk in chat mode and in completion mode, as well as generate images using DALL-E 2. PyGPT also adds access to the Internet for GPT via Google Custom Search API and Wikipedia API and includes voice synthesis using Microsoft Azure Text-to-Speech API. Moreover, the application has implemented context memory support, context storage, history of contexts, which can be restored at any time and e.g. continue the conversation from point in history, and also has a convenient and intuitive system of presets that allows you to quickly and pleasantly create and manage your prompts. Plugins support is also available. -
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Sulla
Javascript Whatsapp API library for chatbots
Sulla is a javascript library that provides a high-level API control to Whatsapp so it can be configured to automatize responses or any data that goes through Whatsapp effortlessly. As of version 2.3.5 it seems that sulla has reached a very rich and stable functionality and architecture. As much as I would love to, I cannot dedicate a lot of time to this project so please consider checking out forked versions of sulla where other developers can dedicate more time and support to it. After executing create() function, sulla will create an instance of WhatsApp web. If you are not logged in, it will print a QR code in the terminal. Scan it with your phone and you are ready to go! Sulla will remember the session so there is no need to authenticate every time. By default QR code will appear on the terminal. The decryption is being done as fast as possible (outruns native methods). Supports big files! -
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Superagent
Superagent protects your AI applications
Superagent is an open-source AI safety platform built to protect applications from prompt injections, data leaks, and harmful outputs. It embeds real-time safety directly into AI workflows, helping teams secure models before threats cause damage. Superagent provides guardrails that block jailbreaks, prompt manipulation, and sensitive data exfiltration. It includes redaction tools to remove PII, PHI, and secrets automatically from text. The platform also scans code repositories to detect AI-specific attack vectors like repo poisoning. Superagent is designed for low-latency production environments and works with any major LLM provider. It enables teams to prove compliance with modern AI security and regulatory standards. -
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Supertonic
Lightning-fast, on-device TTS, running natively via ONNX
Supertonic is a lightning-fast, on-device text-to-speech system built around ONNX Runtime for maximum speed and portability. It focuses on running entirely locally, eliminating the need for cloud APIs and providing low latency and strong privacy guarantees, even on constrained devices like Raspberry Pi boards and e-readers. The core model is highly compact at around 66 million parameters, yet benchmarks show it can generate speech up to 167× faster than real time on modern consumer hardware and significantly outpace popular cloud TTS APIs in throughput and real-time factor. Supertonic is designed to handle real-world text gracefully, including numbers, dates, currency symbols, abbreviations, and technical units, without requiring heavy pre-processing or custom text normalization. The repository provides complete reference implementations across many programming ecosystems—Python, Node.js, browser (WebGPU/WASM), Java, C++, C#, Go, Swift, iOS, Rust, and Flutter. -
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The Web MCP
A powerful Model Context Protocol (MCP) server
Bright Data’s Web MCP server gives AI assistants robust, real-time web capabilities through an MCP interface designed to avoid blocks, rate limits, and CAPTCHAs. It presents search, crawl, navigate, and extraction tools that agents can call directly, replacing brittle scraping prompts with typed operations. The README markets it as a “gateway” to the live web so assistants don’t fall back to stale training data. Bright Data also advertises a getting-started tier with a free monthly allotment, plus options for remote or self-hosted operation depending on governance needs. Ecosystem materials and examples show how it plugs into MCP-capable runtimes and agent frameworks. Overall, the project is aimed at making web intelligence a reliable building block for agent workflows. -
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Transformer Explainer
Learn How LLM Transformer Models Work with Interactive Visualization
Transformer Explainer is an interactive visualization tool created to help users understand how transformer-based language models operate internally. The platform runs a lightweight GPT-2 model directly in the user’s browser and allows users to experiment with text prompts while observing the model’s internal operations. Through visual diagrams and interactive interfaces, the tool reveals how tokens are processed through layers such as embeddings, attention mechanisms, and feed-forward networks. Users can observe how attention weights change as the model predicts the next token, offering insight into how transformer architectures capture relationships between words. The design of the platform emphasizes educational accessibility, allowing students, researchers, and developers to explore complex machine learning concepts without requiring specialized hardware or installations. -
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Universal Data Tool
Collaborate & label any type of data, images, text, or documents etc.
An open-source tool and library for creating and labeling datasets of images, audio, text, documents and video in an open data format. The Universal Data Tool can be used by anyone on your team, no data or programming skills needed. Simplicity without sacrificing any powerful developer features and integrations. Use the Universal Data Tool directly from a web browser or with a Windows, Mac or Linux desktop application. Join a link to a collaborative session and see dataset samples from team members complete in real-time. Import from your S3 buckets easily with IAM or Cognito authentication. Working together, we can accomplish more. The Universal Data Tool was built to bring together the best ideas from different machine learning communities. Upload your dataset to Courses to create a training course. Testing and exercises validate that your workforce knows exactly how the data should be labeled. Get started in less than a minute. Courses uses administrator links. No sign up needed. -
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Wink-NLP
Developer friendly Natural Language Processing
Wink-NLP is a lightweight and fast natural language processing library for JavaScript, optimized for browser and Node.js environments. -
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Wiseflow
Enhance any agent's browser use skill
Wiseflow is an open-source information extraction and knowledge discovery system designed to collect, filter, and organize valuable information from large volumes of online content. The platform continuously monitors specified sources such as websites, social platforms, and other digital channels to identify relevant data according to user-defined interests or topics. By combining web crawling, content parsing, and large language model analysis, the system extracts concise insights from raw information streams and converts them into structured data that can be stored or analyzed. This automated workflow helps reduce the noise associated with large information ecosystems and highlights the most important insights for users. Wiseflow can automatically categorize extracted content, assign tags, and upload processed results into databases or knowledge systems for further use. -
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Zenbot
A command-line cryptocurrency trading bot
Zenbot is a command-line cryptocurrency trading bot using Node.js and MongoDB. Fully-automated technical-analysis-based trading approach. Full support for Binance, Bitfinex, Bitstamp, Bittrex, CEX.IO, GDAX, Gemini, HitBTC, Kraken, Poloniexand TheRockTrading, work on further exchange support is ongoing. Plugin architecture for implementing exchange support, or writing new strategies. Simulator for backtesting strategies against historical data. "Paper" trading mode, operates on a simulated balance while watching the live market. Configurable sell stops, buy stops, and (trailing) profit stops. Flexible sampling period and trade frequency - averages 1-2 trades/day with 1h period, 15-50/day with 5m period. Crypto-currency is still an experiment, and therefore so is Zenbot. Meaning, both may fail at any time. Running a bot, and trading in general requires careful study of the risks and parameters involved. A wrong setting can cause you a major loss. -
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fastText
Library for fast text classification and representation
FastText is an open-source, free, lightweight library that allows users to learn text representations and text classifiers. It works on standard, generic hardware. Models can later be reduced in size to even fit on mobile devices. ext classification is a core problem to many applications, like spam detection, sentiment analysis or smart replies. In this tutorial, we describe how to build a text classifier with the fastText tool. The goal of text classification is to assign documents (such as emails, posts, text messages, product reviews, etc...) to one or multiple categories. Such categories can be review scores, spam v.s. non-spam, or the language in which the document was typed. Nowadays, the dominant approach to build such classifiers is machine learning, that is learning classification rules from examples. In order to build such classifiers, we need labeled data, which consists of documents and their corresponding categories (or tags, or labels). -
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franc
Natural language detection
Franc is a lightweight language detection library for JavaScript that supports multiple languages and scripts. It is designed for detecting text language efficiently in various applications. -
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rep+
Burp-style HTTP Repeater for Chrome DevTools with built‑in AI
rep+ is a lightweight browser extension for Chrome DevTools that brings a Burp Suite-style HTTP repeater directly into the developer console, enhanced with built-in AI to help explain requests and suggest tests. It captures HTTP traffic from the inspected page without needing a proxy, allowing users to replay, modify, and analyze individual requests with fine-grained control over headers, bodies, and methods. The tool offers hierarchical grouping, tagging, and filtering of captured requests so that developers and security testers can manage complex traffic flows efficiently. It includes AI-assisted insights, where contextual explanations and attack vector suggestions help interpret request outcomes or propose modifications. Additional productivity features like exporting/importing requests, various representation modes (pretty/raw/hex), and bulk replay mechanisms make it suitable for debugging, performance checking, or security probing. -
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tmi.js
Javascript library for the Twitch Messaging Interface
Connect to and interact with Twitch chat (IRC) from Node.js or a browser. Control the delay in milliseconds between JOIN requests when using the channels array option. Minimum of 300 milliseconds. If the identity has special permission from Twitch for a higher join rate then you should implement your own calls to the client.join method. Disable receiving JOIN/PART events for other users. Good for decreasing network traffic when joining lots of channels or you don't care about this data. After a threshold per channel Twitch stops sending this data so it may not be necessary for all cases. Channels to automatically join upon connecting. The rate of joins is controlled by the options.joinInterval option. Automatically reconnect the client if it gets disconnected for any reason. Sometimes Twitch will request the client to reconnect and tmi.js will disconnect and reconnect even if this option is set to false. -
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xgplayer
A HTML5 video player with a parser that saves traffic
xgplayer is a web-friendly, open-source media player library maintained by ByteDance, designed for playing audio/video streams in browsers or web applications with robust control, flexibility, and extensibility. It abstracts many of the lower-level complexities of HTML5 media, providing a consistent API for playback control, custom UI overlays, adaptive streaming, plugin hooks, and cross-browser compatibility. Because of its emphasis on modularity and extensibility, xgplayer can be embedded into modern web projects and customized — developers can add controls, custom buffering strategies, subtitle handling, adaptive bitrate streaming, or integrate with other web-based video infrastructures. It seeks to provide a smooth, stable viewing experience even on varied devices or network conditions, and is particularly appealing for web apps that need more control than vanilla video tags offer.
