Search Results for "java runtime environment"
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Showing 173 open source projects for "java runtime environment"
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Next-Gen Encryption for Post-Quantum Security | CLEAR by Quantum KnightCLEAR by Quantum Knight is a FIPS-140-3 validated encryption SDK engineered for enterprises requiring top-tier security. Offering robust post-quantum cryptography, CLEAR secures files, streaming media, databases, and networks with ease across over 30 modern platforms. Its compact design, smaller than a single smartphone image, ensures maximum efficiency and low energy consumption.
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Rezku Point of SaleRezku is an all-inclusive ordering platform and management solution for all types of restaurant and bar concepts. You can now get a fully custom branded downloadable smartphone ordering app for your restaurant exclusively from Rezku.
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AgentScope Java
Agent-Oriented Programming for Building LLM Applications
...The framework includes runtime controls such as safe interruption and graceful cancellation to manage agent execution robustly in production environments. It also supports human-in-the-loop intervention, allowing developers or users to inject guidance at any point during reasoning while preserving state and tool context. Built with enterprise needs in mind, AgentScope Java integrates into traditional Java stacks and provides structured abstractions for memory, workflows, and tool invocation. -
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AnyClaw
Android app running two AI coding agents with a built-in Linux runtime
...Through the embedded runtime, the agents can read codebases, write code, and execute shell commands within the packaged Linux environment. It also supports parallel conversations with separate working contexts, enabling multi-threaded development workflows on a mobile device. -
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SmythOS
Cloud-native runtime for agentic AI
SmythOS SRE (Smyth Runtime Environment) is an open-source runtime and development platform designed for building and operating production-grade AI agents. It provides a foundational infrastructure layer that functions similarly to an operating system for agentic AI systems, managing resources such as language models, storage, vector databases, and caching through a unified interface. -
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IREE
A retargetable MLIR-based machine learning compiler runtime toolkit
IREE (Intermediate Representation Execution Environment, pronounced as "eerie") is an MLIR-based end-to-end compiler and runtime that lowers Machine Learning (ML) models to a unified IR that scales up to meet the needs of the data center and down to satisfy the constraints and special considerations of mobile and edge deployments. -
Skillfully - The future of skills based hiringSkillfully transforms hiring through AI-powered skill simulations that show you how candidates actually perform before you hire them. Our platform helps companies cut through AI-generated resumes and rehearsed interviews by validating real capabilities in action. Through dynamic job specific simulations and skill-based assessments, companies like Bloomberg and McKinsey have cut screening time by 50% while dramatically improving hire quality.
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WorkAny
Desktop Agent for Any Task
WorkAny is an open-source desktop AI agent application that executes generic tasks through natural language commands, effectively bringing intelligent automation into everyday workflows without needing to write code manually. It acts as a unified environment where users can ask the AI to generate documents, presentations, websites, spreadsheets, organize files, or write code — all with real-time streaming outputs directly in the app, so you see results as the AI produces them. Powered by a combination of Claude Code as the primary runtime agent and a sandbox execution environment for safety, WorkAny integrates an agent SDK, MCP (Model Context Protocol) support, and custom skills to handle diverse tasks with contextual understanding. ... -
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Unity MCP
AI-powered bridge connecting LLMs and advanced AI agents
Unity-MCP is an open-source integration that connects artificial intelligence assistants with the Unity game development environment through the Model Context Protocol. The project enables AI tools such as coding assistants and autonomous agents to interact directly with Unity projects, allowing them to analyze scenes, modify assets, and generate code within the development environment. By exposing Unity editor functionality through MCP tools, the plugin allows external AI systems to understand the structure of a game project and manipulate it programmatically. ... -
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NVIDIA FLARE
NVIDIA Federated Learning Application Runtime Environment
NVIDIA Federated Learning Application Runtime Environment NVIDIA FLARE is a domain-agnostic, open-source, extensible SDK that allows researchers and data scientists to adapt existing ML/DL workflows(PyTorch, TensorFlow, Scikit-learn, XGBoost etc.) to a federated paradigm. It enables platform developers to build a secure, privacy-preserving offering for a distributed multi-party collaboration. -
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OpenFang
Open-source Agent Operating System
OpenFang is an open-source agent operating system designed to orchestrate autonomous AI agents and workflows in a structured, production-oriented environment. Written primarily in Rust, the project focuses on building a high-performance runtime where multiple specialized agents can collaborate to complete complex computational or development tasks. It aims to move beyond simple chat-based agents by providing infrastructure for persistent agent memory, task coordination, and scalable execution. ... -
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Ralph AI Agent
AI agent loop that runs repeatedly until all PRD items are complete
Ralph is a Rust-based AI agent runtime that focuses on safe, modular, and programmable autonomous behavior. It provides a reactive loop where agents can repeatedly assess the current context, reason about the next best action using large language models, and execute actions across integrated tools and services. The runtime emphasizes safety boundaries by sandboxing operations, enforcing time and token limits, and isolating execution layers to prevent unpredictable side effects. ... -
Turn traffic into pipeline and prospects into customersDocket is an AI-powered sales enablement platform designed to unify go-to-market (GTM) data through its proprietary Sales Knowledge Lake™ and activate it with intelligent AI agents. The platform helps marketing teams increase pipeline generation by 15% by engaging website visitors in human-like conversations and qualifying leads. For sales teams, Docket improves seller efficiency by 33% by providing instant product knowledge, retrieving collateral, and creating personalized documents. Built for GTM teams, Docket integrates with over 100 tools across the revenue tech stack and offers enterprise-grade security with SOC 2 Type II, GDPR, and ISO 27001 compliance. Customers report improved win rates, shorter sales cycles, and dramatically reduced response times. Docket’s scalable, accurate, and fast AI agents deliver reliable answers with confidence scores, empowering teams to close deals faster.
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chatd
Chat with your documents using local AI
...The software focuses on privacy and security by ensuring that all document processing and inference occur entirely on the user’s computer without sending data to external cloud services. It includes a built-in integration with the Ollama runtime, which provides a cross-platform environment for running large language models locally. The application typically runs models such as Mistral-7B and allows users to load and analyze documents while asking questions in natural language. Unlike many document-chat tools that require manual installation of model servers, chatd packages the model runner with the application so that users can start interacting with documents immediately after launching the program. -
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Agentic Coding Flywheel Setup
System tool for beginners wanting agentic engineering capabilities
Agentic Coding Flywheel Setup (ACFS) is a comprehensive environment bootstrap project that configures a full stack of tools for autonomous AI-assisted coding workflows. With a single shell installer, ACFS transforms a fresh compute environment into a ready-to-use development setup that includes modern shells, language runtimes, AI coding agents (like Claude Code, Codex CLI, and Gemini CLI), and a coordinated toolchain for orchestration and safety. The system is designed for developers who... -
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OneFileLLM
Specify a github or local repo, github pull request
...The concept behind the project is to eliminate the complexity normally associated with deploying AI systems, which often require multiple dependencies, frameworks, and configuration steps. Instead, the entire runtime environment, model interface, and application logic are bundled together into a single executable artifact. This design allows developers to share AI tools in a format that can be easily distributed and executed across different machines without complicated installation procedures. Such packaging strategies help make AI software easier to use in educational settings, demonstrations, and lightweight deployments. -
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OpenShell
OpenShell is the safe, private runtime for autonomous AI agents.
OpenShell is an open-source runtime designed to safely run autonomous AI agents in isolated environments. Developed by NVIDIA, it provides sandboxed execution spaces that protect system resources, credentials, and data from unauthorized access. Each agent runs inside a containerized sandbox governed by declarative YAML security policies that control network access, file permissions, and process behavior. -
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Office Agents
Agent plugins for Microsoft Office but BYOK for any model and provider
...It enables users to interact with large language models inside tools like Excel, Word, and PowerPoint, allowing real-time automation, content generation, and data manipulation within familiar productivity environments. The system is built as a monorepo with multiple packages, including a core SDK for agent runtime, a React-based chat interface, and specialized add-ins tailored to each Office application. It supports a bring-your-own-key model, allowing users to connect to a wide range of AI providers, including OpenAI, Anthropic, and other compatible APIs. The framework also includes advanced capabilities such as a sandboxed execution environment, virtual file systems, and extensible skill modules that expand agent functionality. -
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Crabtalk
Agents daemon that hides nothing
...CrabTalk emphasizes simplicity by avoiding unnecessary abstractions, allowing developers to maintain full control over how agents operate and interact with their environment. One of its key design goals is to address common issues in multi-agent systems, such as context fragmentation and coordination inefficiencies, by providing clearer structure and tighter control over execution. -
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Cog
Package and deploy machine learning models using Docker containers
...It simplifies the process of deploying models by automatically generating Docker images based on a simple configuration file, eliminating the need to manually write complex Dockerfiles. Developers can define the runtime environment, dependencies, and Python versions required for their models, allowing Cog to build a consistent container environment that follows best practices. Cog also resolves compatibility issues between frameworks and GPU libraries by automatically selecting compatible combinations of CUDA, cuDNN, and machine learning frameworks such as PyTorch or TensorFlow. ... -
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MLX Engine
LM Studio Apple MLX engine
MLX Engine is the Apple MLX-based inference backend used by LM Studio to run large language models efficiently on Apple Silicon hardware. Built on top of the mlx-lm and mlx-vlm ecosystems, the engine provides a unified architecture capable of supporting both text-only and multimodal models. Its design focuses on high-performance on-device inference, leveraging Apple’s MLX stack to accelerate computation on M-series chips. The project introduces modular VisionAddOn components that allow image... -
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NemoClaw
NVIDIA plugin for secure installation of OpenClaw
NVIDIA NemoClaw is an open-source tool designed to simplify the deployment and management of always-on AI assistants using the OpenClaw ecosystem. It installs and configures the NVIDIA OpenShell runtime, which provides a secure environment for running autonomous AI agents. NemoClaw enables users to launch sandboxed agent environments that control network access, file permissions, and inference requests through policy-based security. The platform integrates with AI models such as NVIDIA Nemotron and supports multiple inference backends including cloud APIs, local NIM deployments, and vLLM. ... -
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Agent Stack
Deploy and share agents with open infrastructure
Agent Stack is an open infrastructure platform designed to take AI agents from prototype to production, no matter how they were built. It includes a runtime environment, multi-tenant web UI, catalog of agents, and deployment flow that seeks to remove vendor lock-in and provide greater autonomy. Under the hood it’s built on the “Agent2Agent” (A2A) protocol, enabling interoperability between different agent ecosystems, runtime services, and frameworks. The platform supports agents built in frameworks like LangChain, CrewAI, etc., enabling them to be hosted, managed and shared through a unified interface. ... -
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lms
LM Studio CLI
...Through the CLI, users can load and unload models, start or stop local inference servers, and inspect the inputs and outputs generated by language models. LMS is built using the LM Studio JavaScript SDK and integrates tightly with the LM Studio runtime environment. The interface is designed to simplify automation workflows and scripting tasks related to local AI deployment. By exposing model management capabilities through command-line commands, the tool enables developers to integrate local LLM operations into development pipelines and backend services. As a result, LMS acts as a bridge between interactive local AI tools and automated software development workflows. -
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AWorld
Build, evaluate and train General Multi-Agent Assistance with ease
AWorld (Agent World) is an agent runtime/framework. It supports building, evaluating, and training self-improving intelligent agents and multi-agent systems (MAS). It is designed to provide infrastructure for agent orchestration, iterative learning, and environment interaction at scale. Scalable training across environments and distributed setups. Support for multi-agent collaboration/orchestration (MAS). -
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Emscripten
Emscripten: An LLVM-to-WebAssembly Compiler
Emscripten is a complete open-source compiler toolchain that transforms C, C++, and other LLVM-based source code into WebAssembly (and JavaScript), enabling native‑like applications to run in web browsers, Node.js, and other Wasm environments. While Emscripten mostly focuses on compiling C and C++ using Clang, it can be integrated with other LLVM-using compilers (for example, Rust has Emscripten integration, with the wasm32-unknown-emscripten and asmjs-unknown-emscripten targets). Emscripten... -
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SageMaker Training Toolkit
Train machine learning models within Docker containers
...To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime and reliable training process. The SageMaker Training Toolkit can be easily added to any Docker container, making it compatible with SageMaker for training models. If you use a prebuilt SageMaker Docker image for training, this library may already be included. Write a training script (eg. train.py). ... -
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Solon
Java enterprise application development framework
Solon is a full-scenario Java enterprise application framework that positions itself as a lean, high-performance alternative to heavy stacks. It advertises large concurrency gains, lower memory use, much faster startup, and dramatically smaller packages while remaining compatible from Java 8 through Java 24. The framework focuses on restrained APIs and an open ecosystem, with modules that cover web, data, cloud, and microservice patterns. Its messaging emphasizes “replaceable Spring”... -
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SWIFT LLM
Use PEFT or Full-parameter to CPT/SFT/DPO/GRPO 600+ LLMs
...The platform provides a full machine learning pipeline that supports tasks ranging from model pre-training to reinforcement learning alignment techniques. It integrates with popular inference engines such as vLLM and LMDeploy to accelerate deployment and runtime performance. The framework also includes support for many modern training strategies, including preference learning methods and parameter-efficient fine-tuning techniques. ms-swift is designed to work with hundreds of language and multimodal models, providing a unified environment for experimentation and production deployment.
