Open Source Linux Artificial Intelligence Software - Page 66
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BoofCV
BoofCV is an open source Java library for real-time computer vision.
BoofCV is an open source Java library for real-time computer vision and robotics applications. Written from scratch for ease of use and high performance, it provides both basic and advanced features needed for creating a computer vision system. Functionality include optimized low level image processing routines (e.g. convolution, interpolation, gradient) to high level functionality such as image stabilization. Released under an Apache 2.0 license for both academic and commercial use. -
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Jadex is a Belief Desire Intention (BDI) reasoning engine that allows for programming intelligent software agents in XML and Java. The resoning engine is very flexible.
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IDP
Declarative knowledge representation and reasoning
This is the old release page of the IDP system, please visit http://dtai.cs.kuleuven.be/software/idp/try for the most recent release. -
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Common Resource Grep - crgrep
Common Resource Grep
CRGREP searches for matching text in databases, various document formats, archives and other difficult to access resources. A command line tool for name and content text matching in database tables, plain files, MS Office documents, PDF, archives, MP3 audio, image meta-data, scanned documents, maven dependencies and web resources. CRGREP will search resources within resources of any arbitrary combination or depth, so text within a document within a zip archive, and so on. Here you will find binary downloads and discussion (https://sourceforge.net/p/crgrep/discussion/) . The actual development and issue tracking can be found here: https://bitbucket.org/cryanfuse/crgrep -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Translation of Selected text or Clipboard contents powered by Google. HotKeys Paste/Change Text auto translated. View in Balloon/Window the result of translation, besides being sent to the clipboard. Screen Capture of Desktop/Game > OCR > Translated.
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/last30days
Claude Code skill that researches any topic across Reddit + X
/last30days is a specialized Claude Code skill designed to research current trends and practices across Reddit, X, and the wider web from the last 30 days, synthesize that data, and produce copy-paste-ready prompts or summaries that reflect what the community is actually talking about now. Rather than returning generic model responses, it intelligently analyzes social media and community discussions to identify what’s genuinely trending or working in practice across topics ranging from prompt techniques to tool usage or cultural trends. This makes it particularly useful for prompt engineers, content creators, and developers who want up-to-date prompts and insights that align with the most recent consensus and shared best practices in fast-moving fields like AI tooling. -
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A.I.G (AI-Infra-Guard)
A full-stack AI Red Teaming platform securing AI ecosystems
AI-Infra-Guard is an open-source AI red teaming platform for evaluating security risks across modern AI ecosystems. It combines scanning for AI agents, agent skills, MCP servers, AI infrastructure, and OpenClaw deployments. Its infrastructure scanner fingerprints AI services and checks them against a large library of known vulnerabilities. Agent and skill analysis detects risks involving malicious instructions, unsafe code execution, privilege abuse, compromised tools, and insecure dependencies. Jailbreak evaluation tests language models against multiple prompt-based attack methods and enables cross-model comparison. The platform also provides a web interface, standalone scanning tools, APIs, Docker deployment, and integrations for incorporating security checks into AI workflows. -
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AG KIT
Antigravity-first agent engineering kit with rules, skills
AG Kit is an open-source engineering toolkit designed primarily for Google Antigravity agent workspaces. It installs a structured .agents environment containing rules, skills, workflows, specialist agents, and persistent memory. The toolkit provides intelligent routing across 20 role definitions and includes repeatable commands for planning, debugging, testing, deploying, and orchestration. MCP configuration guidance helps agents connect to external tools while preserving reviewable workspace settings. A native pre-tool safety gate blocks high-confidence destructive commands without interfering with normal project cleanup. Merge-aware updates preserve local changes, create backups, and support rollback. Built-in validation, doctor checks, regression tests, and reproducible manifests help teams maintain reliable agent configurations. -
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AG-UI
The Agent-User Interaction Protocol
AG-UI is an open, lightweight protocol for connecting AI agents to user-facing applications through a standardized event-based interface. It is designed to make agent behavior visible, interactive, and controllable inside real-time front-end experiences. Instead of treating an AI agent as a black-box chat endpoint, AG-UI defines structured events for messages, tool calls, state changes, lifecycle updates, and user interactions. This makes it easier for developers to build agent-powered apps that stream progress, request human input, update UI state, and coordinate complex workflows. The project is especially useful for teams building copilots, workflow assistants, multi-agent products, or custom AI interfaces. Overall, AG-UI provides a shared communication layer between autonomous systems and the interfaces where people actually use them. -
AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
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AI Code Translator
Use AI to translate code from one language to another
AI Code Translator is a web-based tool that leverages AI to translate source code from one programming language to another, making cross-language porting or code conversion significantly easier — useful when migrating codebases, experimenting across languages, or learning how code patterns map across languages. The UI is built with Next.js + TypeScript, plus modern tooling like Tailwind CSS, giving a clean frontend experience where you paste or upload code, select target language, and get output quickly. Because it uses AI under the hood, the translation can handle not just syntax but also adapt idioms or patterns appropriately for the target language (though with the usual caveats around AI output correctness). The project is open-source under MIT license, so you can self-host it, integrate into internal tools, or customize language-options and prompts to match your team’s style or language preferences. -
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AI Copywriter
An AI copywriter that uses real copywriting skills + real marketing
AI Copywriter is a portable Markdown-based agent skill for producing persuasive marketing copy that still sounds human. It combines conversion-focused writing with a humanization process based on 33 recognizable patterns of machine-generated prose. Before drafting, the skill asks about the ideal customer, product category, and real story behind the message. It evaluates audience emotion, simplifies the explanation, and challenges vague inputs instead of hiding them behind generic language. The workflow can generate headlines, subject lines, descriptions, interface microcopy, social posts, and strategic articles. It refuses to invent product facts or unsupported numbers and requests stronger evidence when a claim needs proof. Because the core artifact is a single SKILL.md file, it can run in Claude Code, ChatGPT, Manus, and other instruction-compatible agent systems. -
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AI Employe
Create browser automation as if you were teaching a human using GPT-4
Try without Firebase authentication (temporary solution). Our stack consists of Next.js, Rust, Postgres, MeiliSearch, and Firebase Auth for authentication. Please sign up for a Firebase account and create a project. There are several techniques for this, ranging from sending a shortened form of HTML to GPT-3, creating a bounding box with IDs and sending it to GPT-4-vision to take actions, or directly asking GPT-4-vision to obtain the X and Y coordinates of the element. However, none of these methods were reliable; they all led to hallucinations. To prevent GPT from derailing from tasks, we use a technique that is akin to retrieval-augmented generation, but we kind of call it Actions Augmented Generation. Essentially, when a user creates a workflow, we don't record the screen, microphone, or camera, but we do record the DOM element changes for every action (clicking, typing, etc.) the user takes. -
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AI Logo Generator
A free + OSS logo generator powered by Flux on Together AI
AI Logo Generator is an open-source AI logo generator that lets you create professional-looking logos in seconds from a simple text prompt. It uses the Flux Pro 1.1 model hosted on Together AI to generate logos, so the heavy lifting is done by a state-of-the-art image model while the app focuses on UX and workflow. The project is built with Next.js and TypeScript, and it uses shadcn/ui plus Tailwind CSS for a modern, responsive interface that feels like a polished SaaS product rather than a demo. It integrates Clerk for authentication so users can sign in, save their logo history (planned via a dashboard), and potentially manage usage tied to their own API key. Upstash Redis is used for rate limiting, which is important for controlling API usage and preventing abuse when generating many images. Analytics and observability are baked in with Plausible and Helicone, so developers can monitor usage patterns and model behavior over time. -
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AOS Community Edition
AOS Community Edition: the open agent operating system
AOS Community Edition is an open agent operating system for building inspectable and composable agent environments. It provides the aos command-line interface, an HTTP API, community distributions, first-party capsules, provider and model controls, and Unicity Audit. The supported installer provisions a pinned runtime and a versioned collection of 21 Community Edition capsules. Local assets allow both standard and offline initialization, while coordinated upgrades preserve product compatibility. Signed release metadata, checksums, provenance attestations, and runtime compatibility files strengthen supply-chain verification. Its MCP service gives Codex, Claude, and Grok a shared product edge with constrained approval handling. Forge tooling helps agents inspect capability gaps and build least-privilege capsules for new functions. -
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APIPark
APIPark is the #1 open-source AI Gateway and Developer Portal
APIPark is an open-source, all-in-one AI gateway and API developer portal, that helps developers and enterprises easily manage, integrate, and deploy AI services. No matter which AI model you use, APIPark provides a one-stop integration solution. It unifies the management of all authentication information and tracks the costs of API calls. Standardize the request data format for all AI models. When switching AI models or modifying prompts, it won’t affect your app or microservices, simplifying your AI usage and reducing maintenance costs. You can quickly combine AI models and prompts into new APIs. For example, using OpenAI GPT-4 and custom prompts, you can create sentiment analysis APIs, translation APIs, or data analysis APIs. API lifecycle management helps standardize the process of managing APIs, including traffic forwarding, load balancing, and managing different versions of publicly accessible APIs. This improves API quality and maintainability. -
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AReal
Lightning-Fast RL for LLM Reasoning and Agents. Made Simple & Flexible
AReaL is an open source, fully asynchronous reinforcement learning training system. AReal is designed for large reasoning and agentic models. It works with models that perform reasoning over multiple steps, agents interacting with environments. It is developed by the AReaL Team at Ant Group (inclusionAI) and builds upon the ReaLHF project. Release of training details, datasets, and models for reproducibility. It is intended to facilitate reproducible RL training on reasoning / agentic tasks, supporting scaling from single nodes to large GPU clusters. It can streamline the development of AI agents and reasoning systems. Support for algorithm and system co-design optimizations (to improve efficiency and stability). -
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ASu-skills
Job-search workflow plugin suite
ASu-skills is a job-search workflow plugin suite designed for AI coding assistants. It provides specialized entry points for building verifiable experience, improving resume content, creating resumes, preparing for interviews, and tracking applications. Its contributor workflow helps users identify realistic open-source contributions and prepares changes for approval before submission. Resume tools can rewrite experience for target roles and generate editable HTML layouts with PDF export. Interview workflows analyze resume claims, predict likely questions, and probe knowledge gaps through follow-up questions. The suite supports Claude Code, Codex, and TraeWork while sharing common skills, assets, and reference materials. -
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AWS Agent Skills
AWS Skills for Agents
AWS Agent Skills is a repository that curates AWS-focused agent skills — capability modules that give AI assistants like Claude Code and Codex deep, practical knowledge across key Amazon Web Services domains. Instead of streaming giant documentation sets or relying on episodic web search, this project compresses AWS best practices, usage patterns, edge cases, and real-world engineering guides into pre-structured skill definitions that are token-efficient and tailored for reasoning. The skills cover critical AWS services such as IAM, Lambda, DynamoDB, S3, API Gateway, EKS, and many more, letting agents offer actionable advice on infrastructure as code, debugging, security configurations, and architectural workflows. Skills are kept up to date with weekly documentation checks, ensuring they reflect current AWS patterns and service changes. -
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Acme
A library of reinforcement learning components and agents
Acme is a framework from DeepMind for building scalable and reproducible reinforcement learning agents. It emphasizes modular components, distributed training, and ease of experimentation. -
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Aden Hive
Outcome driven agent development framework that evolves
Hive is an open-source agent development framework that helps developers build autonomous, reliable, self-improving AI agents by letting them describe goals in ordinary natural language instead of hand-coding detailed workflows. Rather than manually defining execution graphs, Hive’s coding agent generates the agent graph, connection code, and test cases based on your high-level objectives, enabling outcome-driven agent creation that fits real business processes. Once deployed, agents can capture failure data, evolve automatically to meet their success criteria, and redeploy without constant manual intervention, delivering continual improvement over time. The framework also includes human-in-the-loop nodes, credential management, cost and budget controls, and real-time observability so teams can monitor execution and intervene as needed. Hive is designed for production environments and supports a wide range of large language models, local models, and business system connectivity. -
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Agent Apprenticeship
The living ecosystem where AI agents complete tasks
Agent Apprenticeship is an open infrastructure project for turning real AI-agent work into reusable learning signals. It lets local agents complete tasks through iterative workflow loops, then records the process as experience that can improve future agents. Apprentice agents can be paired with mentor agents, human reviewers, or domain experts depending on the selected mode. The project supports Codex, Cursor, Claude Code, OpenClaw, OpenCode, Hermes Agent, and custom agent commands. Its seed dataset includes curated tasks, reusable lessons, execution traces, work episodes, and structured experience records. It is designed for long-horizon agent work, workflow evaluation, runtime training, and shared improvement across an agent ecosystem. -
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Agent Payments Protocol (AP2)
Building a Secure and Interoperable Future for AI-Driven Payments
AP2 is a project released by Google’s “Agentic Commerce” initiative, focusing on a protocol and reference implementation for agent-driven or AI-mediated payments. In effect, AP2 aims to define a secure, interoperable protocol that allows software agents to act on behalf of users—making payments or shopping decisions autonomously—while preserving necessary security, auditability, and trust. The repository contains sample scenarios (in Python, Android, etc.) that illustrate how agents, servers, and payments flows would work under the protocol. It includes “types” definitions (the core message and object schema) and example agent implementations to demonstrate the mechanics of agent-to-agent and agent-to-server interactions. The design emphasizes flexibility: although their samples use a particular Agent Development Kit (ADK) or runtime, the protocol is intended to be independent of those choices. -
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Agent Skills Tech Leads Club
The secure, validated skill registry for professional AI coding agents
Agent Skills is a managed registry of reusable instruction packages for professional AI coding agents. Skills bundle prompts, templates, references, and specialized workflows that can be installed into tools such as Claude Code, Cursor, Copilot, Codex, Cline, and others. The project emphasizes security through open-source content, static analysis, content hashing, lockfiles, path isolation, and audit logging. Its CLI can browse, install, update, remove, cache, and inspect skills at local or global scope. An interactive wizard helps users choose skills, target agents, and installation methods. A companion MCP server exposes the catalog through search-first, on-demand retrieval. The registry covers development, cloud, browser automation, design, security review, and other engineering tasks. -
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AgentScript
Build AI agents that think in code
AgentScript is a TypeScript SDK for building reliable AI agents that express their plans as code, enabling stop/start workflows, tool-level state management, and enhanced observability. -
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Agentspan
Durable, Distributed runtime for ALL of your agents
Agentspan is a distributed runtime designed to run AI agents reliably across machines while maintaining long-lived execution states. It enables agents to persist beyond process crashes, allowing workflows to continue even after interruptions or restarts. The system is built for durability, meaning tasks can pause for extended periods, including waiting for human approval, and then resume seamlessly. It supports scaling across multiple environments, making it suitable for production-grade agent orchestration. Agentspan includes a local server and visual interface that allow developers to inspect execution flows and debug agent behavior. It also integrates with multiple model providers, enabling flexibility in selecting underlying AI systems. Overall, it provides infrastructure for building resilient, long-running AI agents rather than short-lived scripts.
