Open Source JavaScript Artificial Intelligence Software - Page 4
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JavaScript Artificial Intelligence Software
View 14339 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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AI-Media2Doc
AI tool converting video/audio into structured documents instantly
AI-Media2Doc is a web-based application that uses large language models to convert video and audio content into structured, readable documents in a single workflow. It is designed to transform multimedia inputs into formats such as knowledge notes, summaries, mind maps, and social-style articles, making content easier to review and reuse. AI-Media2Doc emphasizes privacy by processing media locally in the browser using WebAssembly-based ffmpeg, ensuring that original video files are not uploaded externally. It separates client-side media handling from backend AI processing, reducing data exposure while still enabling transcription and document generation. AI-Media2Doc supports flexible customization through prompts, allowing users to tailor output styles based on their needs. It also includes features like subtitle export and AI-assisted follow-up questioning for deeper interaction with the generated content. -
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AIGCPanel
One-stop AI digital human system with video voice synthesis tools
AIGCPanel is an open source desktop application designed as a comprehensive, all-in-one platform for creating AI-powered digital humans and media content. It integrates multiple capabilities such as video synthesis, voice synthesis, and voice cloning into a unified interface, allowing users to generate realistic audiovisual outputs with minimal setup. AIGCPanel focuses heavily on simplifying the management of local AI models by providing streamlined workflows for importing, configuring, and running different models with minimal manual effort. It supports one-click model deployment, making it accessible even to beginners who may not be familiar with complex AI environments. AIGCPanel also includes tools for synchronizing lip movements with generated speech, enabling more realistic digital avatar videos. Built using modern desktop technologies, it delivers a cross-platform experience while maintaining a graphical interface for monitoring tasks and logs. -
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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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Bot Framework Web Chat
A highly-customizable web-based client for Azure Bot Services
This repository contains code for the Bot Framework Web Chat component. The Bot Framework Web Chat component is a highly-customizable web-based client for the Bot Framework V4 SDK. The Bot Framework SDK v4 enables developers to model conversation and build sophisticated bot applications. This repo is part of the Microsoft Bot Framework, a comprehensive framework for building enterprise-grade conversational AI experiences. Create a bot with the ability to speak, listen, understand, and learn from your users with Azure Cognitive Services. Benefit from open source SDK and tools to build, test, and connect bots that interact naturally with users, wherever they are. Build secure, global, scalable solutions that integrate with your existing IT ecosystem. Create an AI experience that can extend your brand and keep you in control of your own data. -
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Chatwoot
Open-source customer engagement suite, an alternative to Intercom
If you have questions, are confused, or just want to understand our product better, we've got your back. Customer engagement suite, an open-source alternative to Intercom, Zendesk, Salesforce Service Cloud etc. Chatwoot is an open-source, self-hosted customer engagement suite. Chatwoot lets you view and manage your customer data, communicate with them irrespective of which medium they use, and re-engage them based on their profile. Talk to your customers using our live chat widget and make use of our SDK to identify a user and provide contextual support. Connect your Facebook pages and start replying to the direct messages to your page. Connect your Instagram profile and start replying to the direct messages. Connect your Twitter profiles and reply to direct messages or the tweets where you are mentioned. Connect your Telegram bot and reply to your customers right from a single dashboard. -
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DeepCamera
Open-Source AI Camera. Empower any camera/CCTV
DeepCamera empowers your traditional surveillance cameras and CCTV/NVR with machine learning technologies. It provides open-source facial recognition-based intrusion detection, fall detection, and parking lot monitoring with the inference engine on your local device. SharpAI-hub is the cloud hosting for AI applications that helps you deploy AI applications with your CCTV camera on your edge device in minutes. SharpAI yolov7_reid is an open-source Python application that leverages AI technologies to detect intruders with traditional surveillance cameras. The source code is here It leverages Yolov7 as a person detector, FastReID for person feature extraction, Milvus the local vector database for self-supervised learning to identify unseen persons, Labelstudio to host images locally and for further usage such as label data and train your own classifier. It also integrates with Home-Assistant to empower smart homes with AI technology. -
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Lemon AI
Full-stack Open-source Self-Evolving General AI Agent
LemonAI is an open-source full-stack framework for building autonomous AI agents capable of performing complex tasks such as research, programming, data analysis, and document processing. The platform is designed to run primarily on local infrastructure, providing a privacy-focused alternative to cloud-dependent agent platforms. It integrates with local large language models through tools such as Ollama, vLLM, and other model runtimes while also allowing optional connections to external cloud models. The system includes a multi-agent architecture that supports planning, action execution, reflection, and memory, allowing the agent to reason through tasks and refine results iteratively. A key component of the framework is a virtual machine sandbox environment that safely executes code generated by the agent without affecting the host system. -
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MCP Toolbox for Databases
Open source MCP server that exposes database tools for AI agents
GenAI Toolbox, also known as MCP Toolbox for Databases, is an open source server designed to simplify how generative AI applications interact with databases. It provides a central service that exposes database operations as reusable tools that can be consumed by AI agents and developer workflows. It handles common infrastructure concerns such as authentication, connection pooling, and performance optimization so developers do not have to implement them individually in each application. By defining tools and data sources through configuration files, developers can standardize how AI systems access and operate on database resources. GenAI Toolbox is designed to integrate with agent frameworks and development environments so that AI assistants can execute database-related tasks with proper context and security. It also supports observability through built-in metrics and tracing capabilities, allowing developers to monitor how tools are used and debug interactions. -
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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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Open SaaS
Open source SaaS boilerplate for React, NodeJS apps with Wasp stack
Open SaaS is a free and open source starter template designed to help developers quickly build and launch Software-as-a-Service applications. It is built on the Wasp full stack framework, which combines React, NodeJS, and Prisma to manage both client and server code within a unified architecture. Open SaaS provides a production-ready foundation that includes common SaaS functionality such as authentication, payments, analytics, and file uploads. Developers can use it as a boilerplate to avoid writing repetitive setup code and instead focus on building product features. It integrates several commonly used services and tools, including payment processing systems, email providers, analytics platforms, and AI integrations. It also includes an admin dashboard, testing setup, and deployment configuration to streamline development workflows. By bundling these components together, Open SaaS aims to reduce development time and make it easier to create scalable web applications. -
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PapersGPT
A powerful Zotero AI and MCP plugin with ChatGPT, Gemini 3.1, Claude
PapersGPT is an AI-powered plugin that integrates directly into Zotero to transform how researchers interact with academic papers and literature collections. It enables users to chat with individual PDFs or entire collections, allowing them to extract insights, generate summaries, and explore connections between documents without leaving the Zotero environment. The plugin supports a wide range of state-of-the-art language models, including GPT, Claude, Gemini, and open-source alternatives, giving users flexibility in choosing performance, cost, and privacy trade-offs. One of its most powerful features is its ability to process large volumes of academic content quickly, enabling tasks such as literature reviews, theoretical analysis, and research synthesis to be completed significantly faster. It also supports multi-document querying, allowing users to compare findings across multiple papers and generate comprehensive overviews of research topics. -
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Scribe.js
JavaScript OCR and text extraction for images and PDFs
Scribe.js is a JavaScript library that provides Optical Character Recognition (OCR) and text extraction capabilities for both images and PDF documents, aimed at developers who want to build OCR features directly into their applications. The library can take image files (such as PNG or JPEG) and recognize the text they contain, and it can also extract text from PDF files that either already contain text or are image-based scans, using modern web standards and WebAssembly under the hood. In addition to simple text extraction, Scribe.js supports writing or injecting a high-quality invisible text layer back into PDFs, effectively making them searchable and improving usability for indexing or accessibility. It is written in modern ECMAScript Modules (ESM), so it can be imported in both browser and Node.js environments without a build step, though browser usage requires same-origin hosting of the files. -
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SmallCode
AI coding agent optimized for small LLMs. 87% benchmark
SmallCode is a terminal-native AI coding agent optimized for local models running on consumer hardware. It is designed to extract useful coding performance from smaller LLMs, especially models in the 7B to 20B range. The project focuses on making local coding assistance practical without requiring massive cloud-hosted models for every task. Its workflow is built around terminal usage, which makes it suitable for developers who prefer command-line control and local project context. smallcode emphasizes efficient agent behavior, careful tool use, and benchmark-driven improvements for constrained models. Its main value is giving developers a compact coding-agent environment that treats small local models as first-class tools. -
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WarriorJS
JavaScript coding game where players program a warrior to win battles
WarriorJS is an educational programming game designed to teach and challenge JavaScript skills through interactive gameplay. In the game, players control a warrior who must climb a tower filled with enemies, captives, and obstacles in pursuit of a legendary JavaScript Sword located at the top. Each floor of the tower presents a new challenge that requires players to write JavaScript code to instruct the warrior on how to move, fight enemies, rescue captives, and safely reach the stairs to the next level. WarriorJS combines game mechanics with programming concepts, allowing players to experiment with logic, algorithms, and problem solving while progressing through increasingly difficult levels. WarriorJS can be played through a command line interface, enabling developers to interact with the game directly in a terminal environment. It is organized as a modular monorepo containing several packages that implement the core game engine. -
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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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Agili Hacker Podcast
AI tool that turns Hacker News posts into daily podcast updates
Hacker Podcast is an AI-powered project that turns top Hacker News stories into a Chinese podcast. It automatically fetches trending posts each day, processes the content with AI, and generates concise summaries before converting them into audio. This creates a hands-free way to stay updated on tech, startups, and developer discussions without reading long threads. Hacker Podcast combines content aggregation, natural language processing, and text-to-speech to deliver clear and digestible updates. Users can listen through web interfaces or podcast platforms, while also accessing written summaries for deeper reading. Built with modern web technologies, the project focuses on automation, speed, and accessibility. It supports continuous updates, allowing listeners to receive fresh insights daily. As an open-source tool, it also encourages community contributions and customization for developers who want to adapt or extend its workflow for similar AI-driven content pipelines. -
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ChatLab
Local-first AI chat analysis tool for insights from conversation data
ChatLab is an open source desktop application designed to help users analyze and better understand their personal chat histories through structured data exploration and AI-assisted insights. It enables users to import chat exports from multiple messaging platforms and transform them into a unified data model for consistent analysis. By combining a flexible SQL engine with AI agents, the tool allows users to query, summarize, and explore conversation patterns in a more interactive and intelligent way. ChatLab emphasizes a local-first approach, meaning all chat data is processed and stored on the user’s device rather than being uploaded to external servers. It supports large-scale datasets through streaming parsing and multi-worker processing, allowing it to handle millions of messages efficiently. ChatLab also includes visualization features that present trends, activity patterns, and interaction metrics in a clear and accessible format. -
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Claude-Flow
The leading agent orchestration platform for Claude
Claude-Flow v2 Alpha is an advanced AI orchestration and automation framework designed for enterprise-grade, large-scale AI-driven development. It enables developers to coordinate multiple specialized AI agents in real time through a hive-mind architecture, combining swarm intelligence, neural reasoning, and a powerful set of 87 Modular Control Protocol (MCP) tools. The platform supports both quick swarm tasks and persistent multi-agent sessions known as hives, facilitating distributed AI collaboration with persistent contextual memory. At its core, Claude-Flow integrates Dynamic Agent Architecture (DAA) for self-organizing agent management, neural pattern recognition accelerated by WebAssembly SIMD, and a SQLite-based memory system for context retention and knowledge persistence across tasks. It automates development workflows via pre- and post-operation hooks, providing seamless coordination, code formatting, validation, and performance optimization. -
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Codex plugin for Claude Code
Use Codex from Claude Code to review code or delegate tasks
Codex plugin for Claude Code is an integration layer that connects OpenAI Codex-style capabilities with agent-based coding environments, enabling seamless execution of coding tasks through structured plugins. The project is designed to extend the functionality of coding agents by allowing them to delegate tasks to Codex or similar models in a controlled and modular way. It likely provides abstractions for handling code generation, editing, and analysis while maintaining consistency across workflows. The system emphasizes interoperability, allowing developers to plug Codex capabilities into broader agent ecosystems without rewriting core logic. It may also include mechanisms for managing execution context, permissions, and tool access, ensuring that generated code can be safely applied. This makes it particularly useful for complex development pipelines where multiple agents or tools need to collaborate. -
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GPU Hot
Real-time NVIDIA GPU dashboard
GPU Hot is an open-source, lightweight monitoring dashboard designed to provide real-time visibility into NVIDIA GPU performance across single machines or entire clusters. The project offers a self-hosted web interface that streams hardware metrics directly from GPU servers, enabling developers, ML engineers, and system administrators to observe GPU utilization and system behavior in real time through a browser. The dashboard collects and displays a wide range of performance metrics including temperature, memory usage, power consumption, clock speeds, fan speed, and active processes. It can scale from monitoring a single GPU workstation to large distributed environments with dozens or even hundreds of GPUs by running lightweight containers on each node and aggregating the data centrally. -
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Get Shit Done
A light-weight and powerful meta-prompting, context engineering
Get Shit Done is a high-impact, open-source meta-prompting and spec-driven development system designed to streamline building software with AI assistants like Claude Code, OpenCode, and Gemini CLI. It solves “context rot” — the degradation of AI quality as a chat session grows — by structuring your idea into precise, context-engineered steps that are researched, scoped, planned, executed, and verified with clear commands and outputs instead of ad-hoc prompts. The project emphasizes simplicity and effectiveness over bureaucratic workflows like story points, sprint ceremonies, or enterprise processes, making it especially useful for solo developers or small teams aiming to get reliable execution without overhead. GSD breaks down big goals into atomic plans, keeps AI context fresh, and automates task execution while generating standardized documentation, roadmaps, and commit histories. -
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GitDiagram
AI tool that converts GitHub repositories into interactive diagrams
GitDiagram is an open source web application designed to help developers quickly understand the structure and architecture of GitHub repositories by automatically generating interactive diagrams. It analyzes repository metadata such as the file tree and project documentation to build a visual representation of how different components of a project relate to one another. It uses an AI-powered pipeline to interpret repository structure and transform that information into system design diagrams rendered with Mermaid visualization. These diagrams provide a high-level overview of a codebase, making it easier for developers to explore unfamiliar projects or understand large and complex repositories. Users can interact with the generated diagrams by clicking components to navigate directly to related files or directories within the repository. GitDiagram combines a modern web frontend with a backend service that processes repository data and generates diagrams dynamically. -
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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. -
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HumanLayer
Open source IDE for orchestrating AI coding agents in large codebases
HumanLayer is an open source development environment designed to help developers orchestrate and manage AI coding agents working within complex software projects. It provides a framework and tooling that allow AI agents to research, plan, and implement changes in large codebases while maintaining structured workflows. It focuses on enabling AI-assisted development through coordinated agent workflows rather than isolated code generation tasks. HumanLayer integrates with modern AI models and coding assistants to automate tasks such as code research, planning, and implementation while maintaining a structured development process. HumanLayer introduces advanced context management techniques that help AI agents understand large repositories and operate effectively across multiple tasks. It also supports collaborative workflows where developers and AI agents can work together with human oversight and control. -
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LLM Datasets
Curated list of datasets and tools for post-training
LLM Datasets curates and standardizes datasets commonly used to train and fine-tune large language models, reducing the overhead of hunting down sources and normalizing formats. The repository aims to make datasets easy to inspect and transform, with scripts for downloading, deduping, cleaning, and converting to formats like JSONL that slot into training pipelines. It highlights instruction-tuning and conversation-style corpora while also pointing to code, math, or domain-specific sets for targeted capabilities. Quality is a recurring theme: examples and utilities help filter low-value samples, enforce length limits, and split train/validation consistently so results are comparable. Licensing and provenance are surfaced to encourage compliant usage and to guide dataset selection in commercial settings. For practitioners, the repo is a practical “starting pantry” that accelerates experimentation and helps keep data wrangling from dominating the project timeline.