Open Source Rust Artificial Intelligence Software
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Rust Artificial Intelligence Software
View 17033 business solutionsBrowse free open source Rust Artificial Intelligence Software and projects below. Use the toggles on the left to filter open source Rust Artificial Intelligence Software by OS, license, language, programming language, and project status.
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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ArtCraft
Crafting engine for artists, designers, and filmmakers
ArtCraft is an open-source desktop creative environment designed as an IDE for interactive AI-driven image and video creation, with the goal of transforming traditional prompting into a more hands-on crafting workflow. The project positions itself as an intentional “crafting engine” for artists, designers, and filmmakers who want deeper control over generative media pipelines. Rather than relying purely on text prompts, ArtCraft emphasizes visual manipulation, compositional control, and iterative refinement so creators can treat AI output more like a malleable creative medium. The application is built with performance and responsiveness in mind, enabling users to move between different creative canvases and asset workflows within a unified interface. It aims to support complex multimedia generation workflows including image, video, and potentially 3D content creation, making it useful for experimental filmmaking and advanced visual design. -
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ChatGPT Desktop Application
🔮 ChatGPT Desktop Application (Mac, Windows and Linux)
ChatGPT Desktop Application (Mac, Windows and Linux) -
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OpenLess
AI-polished text appears at your cursor in any app
OpenLess is an open-source voice input application for macOS and Windows that turns spoken ideas into polished text at the current cursor position. Users press a global hotkey, speak naturally, and release the key to receive cleaned-up text inside apps such as ChatGPT, Claude, Cursor, Notion, email clients, or chat boxes. Unlike basic dictation tools, it is designed to restructure loose speech into more useful writing, especially AI prompts with clearer context and constraints. The app follows a local-first and open-source approach, while allowing users to bring their own cloud credentials for speech recognition and chat completion services. It also tries to preserve input by copying output to the clipboard if direct insertion fails. OpenLess is best suited for people who think faster by speaking and want cleaner text without manually rewriting every rough thought. -
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DeepSeek TUI
Coding agent for DeepSeek models that runs in your terminal
DeepSeek-TUI is a terminal-based user interface designed to interact with DeepSeek language models in a lightweight and efficient way. It provides a text-based chat experience directly within the command line, making it ideal for developers who prefer minimal interfaces. The tool supports streaming responses, allowing real-time interaction with the model. It includes features for managing prompts, sessions, and conversation history within the terminal environment. DeepSeek-TUI emphasizes speed and simplicity, avoiding heavy graphical dependencies. It is particularly useful for local or remote environments where graphical interfaces are impractical. Overall, it delivers an efficient CLI-first experience for AI interaction. -
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abtop
Like htop, but for AI coding agents. Monitor Claude Code & Codex CLI
abtop is a terminal monitoring tool for AI coding agents, inspired by system monitors like htop and btop. It gives users a real-time view of active Claude Code, Codex CLI, and OpenCode sessions from local process and file state. The dashboard helps developers track token usage, context window percentage, rate limits, child processes, open ports, and multiple active profiles. It is read-only, so it does not require API keys or authentication and does not control the agents it observes. abtop is especially useful for developers running several agents across projects who need quick visibility into cost, quota pressure, context growth, and orphaned processes. Its main value is bringing operational observability to AI coding-agent workflows directly inside the terminal. -
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OpenAI Codex CLI
Lightweight coding agent that runs in your terminal
OpenAI Codex CLI is a lightweight, open-source coding assistant that runs directly in your terminal, designed to bring ChatGPT-level reasoning to your code workflows. It allows developers to interactively query, edit, and generate code within their repositories, all while maintaining version control. The CLI can scaffold new files, run code in sandboxed environments, install dependencies, and commit changes automatically, streamlining chat-driven development. It supports various approval modes—from suggestion-only to full automation—ensuring safe and controlled code execution. Codex CLI can also handle multimodal inputs like screenshots and diagrams to implement features intelligently. The tool includes built-in sandboxing & security measures, such as network restrictions and directory confinement, to protect your system during code execution. With extensive configuration options, including multiple AI providers and custom guidance files, it fits seamlessly into developer environments. -
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OpenHuman
Your Personal AI super intelligence. Private, simple and powerful
OpenHuman is an open-source personal AI assistant built to operate as a daily-life agent rather than a simple chatbot. It focuses on a private, desktop-first experience with a friendly interface, onboarding flows, and a persistent assistant that can remember context over time. The project connects to common productivity tools, gathers fresh information from integrations, and organizes user knowledge into a local memory system. It also includes practical agent tools such as web search, web fetching, file access, coding utilities, voice input, text-to-speech, and model routing. Its goal is to make an AI assistant feel continuously useful across meetings, messages, documents, tasks, and personal workflows. Since it is still in early beta, it is best suited for technical users and early adopters who want to experiment with a customizable personal AI environment. -
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GaiaNet
Install and run your own AI agent service
Gaia is building an active, intelligent ecosystem that supports applications that learn, improve and grow over time. Put your knowledge to work and watch it evolve by creating a node on Gaia or by contributing to a domain supporting an existing knowledge base. Gaia’s decentralized platform ensures robust protection for user data and IP. Gaia allows secure ownership and monetization of IP without compromising privacy. Gaia’s living knowledge organisms continuously adapt and grow in real-time, keeping solutions relevant and cutting-edge. Developers can build applications that evolve and improve over time. -
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tuicr
A code review TUI with vim keybindings
tuicr is a terminal user interface for reviewing code changes with Vim-style keyboard controls. It presents all changed files as one continuous GitHub-like diff that developers can navigate without leaving the terminal. Reviewers can attach comments to individual lines, line ranges, files, or the entire review. Progress can be tracked at the file or hunk level and restored across later sessions. The tool can inspect uncommitted changes, commit ranges, GitHub pull requests, and GitLab merge requests. It works with Git, Jujutsu, and Mercurial repositories and can automatically detect the active version-control system. Finished reviews can be submitted to GitHub or GitLab, copied as structured Markdown, or written to standard output for use by people or coding agents. -
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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Obscura
The headless browser for AI agents and web scraping
Obscura is a security-focused project aimed at providing tools and techniques for enhancing privacy, anonymity, and operational security in digital environments. It is designed for users who need to obscure their digital footprint and reduce traceability across systems. The project typically includes utilities for masking identity, managing secure communication, and mitigating surveillance risks. It emphasizes practical implementations of privacy-preserving workflows rather than purely theoretical approaches. Obscura is particularly relevant for researchers, security professionals, and privacy-conscious users. Its architecture focuses on modular tools that can be adapted to different threat models. The project reflects modern concerns around digital surveillance and data exposure. -
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Goose
AI coding agent that's more than suggestions - install, execute, edit+
Goose is an open-source, extensible AI agent that enhances the software development process by going beyond traditional code suggestions. It allows developers to install, execute, edit, and test code with any large language model (LLM), facilitating a more efficient and streamlined workflow. Designed to operate locally within a developer's environment, Goose integrates seamlessly with various tools and platforms, providing a customizable and powerful assistant for coding tasks. Its architecture supports extensibility, enabling users to tailor the agent to their specific needs and preferences. By leveraging Goose, developers can improve productivity and code quality through advanced AI-driven assistance. -
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mistral.rs
Fast, flexible LLM inference
mistral.rs is a fast and flexible LLM inference engine implemented in Rust, designed to run and serve modern language models with an emphasis on performance and practical deployment. It provides multiple entry points for developers, including a CLI for running models locally and an HTTP server that exposes an OpenAI-compatible API surface for easy integration with existing clients. The project includes hardware-aware tooling that can benchmark a system and choose sensible quantization and device-mapping strategies, helping users get strong performance without manual tuning. It also supports serving multiple models from the same server process, enabling routing or quick switching between models depending on workload needs. For user-facing testing, mistral.rs can provide a built-in web UI, and it also offers a dedicated lightweight web chat interface that supports richer interaction patterns. -
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Zed
High-performance, multiplayer code editor from the creators of Atom
Zed is a next-generation code editor designed for high-performance collaboration with humans and AI. Written from scratch in Rust to efficiently leverage multiple CPU cores and your GPU. Integrate upcoming LLMs into your workflow to generate, transform, and analyze code. Chat with teammates, write notes together, and share your screen and project. Multibuffers compose excerpts from across the codebase in one editable surface. Evaluate code inline via Jupyter runtimes and collaboratively edit notebooks. Support for many languages via Tree-sitter, WebAssembly, and the Language Server Protocol. Fast native terminal tightly integrates with Zed's language-aware task runner and AI capabilities. First-class modal editing via Vim bindings, including features like text objects and marks. Zed is built by a global community of thousands of developers. Boost your Zed experience by choosing from hundreds of extensions that broaden language support, offer different themes, and more. -
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Codex-X
Codex Switch & Instruct desktop manager
Codex-X is a cross-platform desktop manager for OpenAI Codex Desktop and Codex CLI configurations. It replaces repeated manual file editing with a visual interface for prompts, providers, sessions, skills, MCP servers, and TOML settings. Users can categorize, import, edit, enable, disable, cache, and synchronize Markdown instruction templates. Provider tools store multiple API configurations, test connections, retrieve models, and switch between official and third-party services. Session management can search, group, inspect, synchronize, and permanently delete local Codex histories. The application also displays authentication and configuration files while creating backups before important changes. Packages are offered for macOS, Windows, and Linux through a Tauri-based desktop application. -
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Qdrant
Vector Database for the next generation of AI applications
Qdrant is a vector similarity engine & vector database. It deploys as an API service providing search for the nearest high-dimensional vectors. With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications for matching, searching, recommending, and much more! Provides the OpenAPI v3 specification to generate a client library in almost any programming language. Alternatively, utilize ready-made client for Python or other programming languages with additional functionality. Implement a unique custom modification of the HNSW algorithm for the Approximate Nearest Neighbor Search. Search with a State-of-the-Art speed and apply search filters without compromising on results. Support additional payload associated with vectors. Not only stores payload but also allows filter results based on payload values. Unlike Elasticsearch post-filtering, Qdrant guarantees all relevant vectors are retrieved. -
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CubeSandbox
Instant, Concurrent, Secure & Lightweight Sandbox for AI Agents
CubeSandbox is a lightweight, high-performance sandboxing environment designed to securely run AI agents and untrusted code in isolated containers. Built in Rust, it focuses on enabling concurrent execution while maintaining strong isolation and low overhead. The system is optimized for scenarios where multiple AI agents need to execute tasks in parallel without compromising system integrity. It provides fast startup times and efficient resource management, making it suitable for large-scale agent orchestration. CubeSandbox integrates well with cloud-native workflows and modern infrastructure pipelines. Its design prioritizes security, concurrency, and performance in AI-driven environments. It is particularly useful for agent frameworks requiring safe execution of generated code. -
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jcode
Coding Agent Harness
jcode is a lightweight developer tool designed to streamline Java coding workflows by simplifying compilation, execution, and testing processes. It provides a structured interface for managing Java programs without requiring complex IDE setups, making it ideal for quick experimentation and learning. The tool focuses on reducing friction for developers who want to run code snippets or small projects efficiently. It supports automation of repetitive tasks such as compiling and executing Java files in a consistent environment. JCode is especially useful for beginners or developers working in minimal setups where full IDEs are unnecessary. Its design emphasizes speed, simplicity, and ease of integration into command-line workflows. Overall, it serves as a productivity enhancer for Java development in lightweight environments. -
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forkd
Fork() for AI agent microVMs
forkd is a microVM sandbox runtime designed for high-speed AI agent fan-out. Instead of cold-booting a separate virtual machine for every worker, it forks children from a warmed parent snapshot and uses copy-on-write behavior to share the initial memory state. This makes it useful for spawning many isolated agent environments quickly during parallel research, testing, or code execution. The project is focused on runtime performance, sandbox isolation, and efficient branching from a live or prepared VM state. It is especially relevant for developers building agent infrastructure where many short-lived execution branches need to run safely. forkd is best understood as a low-level systems tool for scalable, isolated AI-agent workloads. -
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Meetily
Privacy first, AI meeting assistant with 4x faster Parakeet/Whisper
This project is a privacy-first AI meeting assistant that captures meeting audio, produces real-time transcripts, and generates summaries while keeping processing entirely on your own machine or infrastructure. It’s built for organizations that want meeting intelligence without sending recordings or transcripts to third-party cloud services, which helps address compliance and data sovereignty requirements. The app supports live transcription with local model options (including Whisper- and Parakeet-based workflows) and presents the transcript as the meeting happens, making it useful both for note-taking and accessibility. After or during the session, it can produce structured, AI-generated summaries, and it’s designed to be flexible about where that summarization comes from, supporting local providers as well as external endpoints when allowed by policy. -
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llmfit
157 models, 30 providers, one command to find what runs on hardware
llmfit is a terminal-based utility that helps developers determine which large language models can realistically run on their local hardware by analyzing system resources and model requirements. The tool automatically detects CPU, RAM, GPU, and VRAM specifications, then ranks available models based on performance factors such as speed, quality, and memory fit. It provides both an interactive terminal user interface and a traditional CLI mode, enabling flexible workflows for different user preferences. llmfit also supports advanced configurations including multi-GPU setups, mixture-of-experts architectures, and dynamic quantization recommendations. By presenting clear performance estimates and compatibility guidance, the project reduces the trial-and-error typically involved in local LLM experimentation. Overall, llmfit serves as a practical decision assistant for developers who want to run language models efficiently on their own machines. -
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Buzz
A hive mind communication platform
Buzz is a self-hostable collaboration workspace where human teammates and AI agents work together in the same channels. It records messages, reactions, workflow steps, approvals, and Git activity as cryptographically signed Nostr events in a shared log. The platform includes channels, threads, direct messages, canvases, media sharing, full-text search, and a tamper-evident audit trail. Agents receive their own identities and memberships, allowing them to answer questions, review patches, manage workspaces, and run tools without impersonating users. YAML workflows can respond to messages, reactions, schedules, and webhooks while preserving execution traces. Buzz provides a Tauri desktop client, browser access, a JSON-oriented CLI, MCP support, and ACP integrations for popular coding agents. Teams can run their own relay and keep the workspace, history, automation, and repositories under their control. -
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herdr
Agent multiplexer that lives in your terminal
herdr is a terminal-native multiplexer built specifically for running AI coding agents. It gives every agent a real terminal pane instead of a simulated terminal inside a desktop wrapper. Users can organize agent sessions into workspaces, tabs, and split panes while keeping visibility into what each agent is doing. The sidebar shows whether agents are blocked, working, done, or idle, so large multi-agent workflows are easier to supervise. Sessions continue running after detach, which allows users to reconnect later from another terminal or over SSH. The project is distributed as a lightweight Rust binary for Linux, macOS, and beta Windows support. It also includes a local socket API and CLI so agents can create panes, read output, and orchestrate terminal workflows themselves. -
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ZeroClaw
Fast, small, and fully autonomous AI assistant infrastructure
ZeroClaw is a Rust-native autonomous AI agent framework engineered for teams and developers who need highly efficient, secure, and modular AI automation infrastructure that can run reliably in both production and self-hosted environments. It is designed around a trait-based architecture so that model providers, communication channels, memory systems, and tooling integrations can be swapped or extended without rewriting core components, giving engineers flexibility and long-term maintainability. The framework features a compact single binary with fast cold and warm startup times and very low memory overhead, making it suitable even for resource-constrained hardware like small servers or edge devices. Security is a first-class concern, with sandbox controls, encrypted secrets, allowlisted operations, and scoped filesystem access by default, helping reduce risk when running autonomous agents. -
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MusicGPT
Generate music based on natural language prompts using LLMs
MusicGPT is an open-source application designed to generate music from natural language prompts using locally executed artificial intelligence models. The software allows users to run advanced music generation systems directly on their own devices without requiring heavy dependencies such as Python or full machine learning frameworks. Instead, it provides a lightweight environment capable of executing music generation models locally on CPUs or GPUs while maintaining strong performance across operating systems including Windows, macOS, and Linux. Users can describe a musical style, mood, or instrumentation using text prompts, and the system produces original audio samples based on those instructions. The application currently integrates with models such as MusicGen and is designed to support additional models transparently in the future. In addition to a command-line interface, the project includes a web-based interface that enables conversational interaction with the AI model. -
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Sail
A drop-in Apache Spark replacement written in Rust
Sail is an open-source distributed computation framework designed to unify batch processing, stream processing, and AI workloads into a single, high-performance engine. It is built entirely in Rust, eliminating JVM overhead and enabling predictable performance, fast startup times, and improved memory safety compared to traditional big data frameworks. Sail is compatible with the Spark Connect protocol, which means existing Spark SQL and DataFrame workloads can run without code changes, making adoption seamless for teams already using Spark-based pipelines. The framework is designed to operate across a variety of environments, including local machines, Kubernetes clusters, and cloud deployments, allowing flexible scaling based on workload requirements. It also emphasizes cost efficiency, with benchmarks showing significant performance improvements and reduced infrastructure usage compared to traditional systems.
