Search Results for "java runtime environment"
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Showing 12 open source projects for "java runtime environment"
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Chidori
A reactive runtime for building durable AI agents
A reactive runtime for building durable AI agents. Chidori is an open-source orchestrator, runtime, and IDE for building software in symbiosis with modern AI tools. When using Chidori, you author code with python or javascript, we provide a layer for interfacing with the complexities of AI models in long-running workflows. We have avoided the need for declaring a new language or SDK in order to provide these capabilities so that you can leverage software patterns that you are already... -
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OpenConnector
Open-source auth gateway connecting 1000+ SaaS providers to AI agents
...It exposes a shared catalog of more than 1,000 providers and over 10,000 predefined actions. Applications can call those actions through a TypeScript SDK, command-line relay, MCP, HTTP endpoints, or generated OpenAPI specifications. The runtime manages OAuth, API keys, custom credentials, scopes, tokens, policies, temporary files, and redacted logs. A web console helps administrators browse connectors, configure accounts, create runtime tokens, and inspect activity. It can run locally with Node.js or Docker, on Fly.io, on Cloudflare-compatible infrastructure, or through OOMOL's hosted environment. ... -
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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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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. ... -
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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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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Kun
AI agent workspace with Code and Write modes built into your apps
...The application includes a Code workspace for real repositories and a Write workspace for Markdown writing, editing, previewing, and exporting. It uses DeepSeek, Xiaomi MiMo, and MiniMax as its default model combination while still allowing custom providers. Kun includes a local runtime through kun serve, local session storage, tool approvals, permission modes, inline diffs, and change review panels. It is useful for users who want an AI coding environment that treats planning, documentation, implementation, and acceptance review as one continuous workflow. -
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E2B
Secure open source cloud runtime for AI apps & AI agents
E2B's Code Interpreter SDK allows you to add code-interpreting capabilities to your AI apps. E2B Sandbox is a secure sandboxed cloud environment made for AI agents and AI apps. Sandboxes allow AI agents and apps to have long-running cloud secure environments. In these environments, large language models can use the same tools as humans do. -
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Poco Claw
A more beautiful and easier-to-use alternative to OpenClaw
...It focuses on improving usability by providing a modern web interface combined with enhanced interaction capabilities such as built-in messaging and project organization tools. The system operates on a sandboxed runtime, ensuring that tasks executed by the agent are isolated from the host environment, which improves security and reliability. It extends beyond simple chatbot functionality by supporting structured workflows, task planning modes, and multi-step execution pipelines. The platform also allows users to manage files and contexts directly within the interface, enabling more complex interactions with data and projects. ... -
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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. ... -
Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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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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Moltis
A Rust-native claw you can trust
Moltis is an open-source personal AI assistant platform written in Rust that is designed to run as a fully self-hosted, local-first agent environment. It compiles the entire assistant stack, including the web interface, model routing, memory, and tools, into a single self-contained binary with no external runtime dependencies. The system supports multiple large language model providers alongside local models, enabling users to maintain privacy while still accessing cloud capabilities when needed. ... -
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Cumora
Where agent teams gather. Cross-platform team chat
...Agents can maintain personas and memory, claim tasks, coordinate with one another, send and receive email, and use shared Kanban and calendar views. Teams can run agents through Cumora Cloud or bring their own Claude Code or Codex environment from a Mac or VPS. Cloud agents receive isolated runtime pods with access to tools such as shell commands, files, browsers, email, memory, and skills. Coordination safeguards help prevent agents from duplicating or overwriting one another's work. The interface is available across desktop, web, iOS, and Android clients built from a shared React-based frontend.
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