Search Results for "linux windows agent"
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Showing 6325 open source projects for "linux windows agent"
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any-agent
A single interface to use and evaluate different agent frameworks
any-agent is a Python library that provides a unified interface for working with multiple agent frameworks, allowing developers to create, run, and evaluate AI agents without being locked into a single ecosystem. It abstracts the differences between frameworks such as LangChain, LlamaIndex, OpenAI Agents, and others, enabling users to switch between them with minimal configuration changes. The library is designed to simplify experimentation and benchmarking, making it easier to compare agent... -
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Agent-Native
A framework for building agentic apps
Agent-Native is an open-source TypeScript framework for building AI agents with purpose-built application interfaces. Each capability is defined once as an action that can be called by both the agent and the user interface. The same actions can also be exposed through HTTP, MCP, A2A, and command-line interfaces. Shared data and application state let agents see relevant UI context and immediately surface their work back to users. The framework includes chat, authentication, permissions,... -
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Xata Agent
AI agent expert in PostgreSQL
Xata Agent is a local development tool that provides a seamless integration experience for developers working with Xata, a serverless database platform. It runs a local proxy that mimics production behavior, allowing developers to test and develop with local credentials, preview branches, and schema changes. The agent is built for productivity, enabling tight CLI and Git integration for data workflows. -
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Bee Agent Framework
The framework for building scalable agentic applications
Open-source framework for building, deploying, and serving powerful agentic workflows at scale. The Bee Agent Framework makes it easy to build scalable agent-based workflows with your model of choice. The framework is been designed to perform robustly with IBM Granite and Llama 3.x models, and we’re actively working on optimizing its performance with other popular LLMs. Our goal is to empower developers to adopt the latest open-source and proprietary models with minimal changes to their... -
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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bu-agent-sdk
An agent is just a for-loop
The bu-agent-sdk from the Browser Use project is a minimalistic Python framework that defines an AI agent as a simple loop of tool calls, aiming to keep abstractions low so developers can build autonomous agents without unnecessary complexity. At its core, the agent loop repeatedly queries a large language model, interprets its output, and executes defined “tools” — functions annotated with task names — to perform actions, allowing the agent to complete tasks like arithmetic,... -
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Neuro SAN Studio
A playground for neuro-san
Neuro SAN Studio is a development environment and playground for building, testing, and deploying multi-agent AI systems using the Neuro SAN framework. It provides a hands-on interface where users can design agent networks, run experiments, and observe how multiple agents collaborate to solve complex tasks. The platform is built around a data-driven approach, where entire agent systems can be defined using configuration files rather than extensive code, making it accessible to both... -
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Windows Presentation Foundation (WPF)
Framework for building Windows desktop applications
Windows Presentation Foundation (WPF) is a UI framework for building Windows desktop applications. WPF supports a broad set of application development features, including an application model, resources, controls, graphics, layout, data binding and documents. WPF uses the Extensible Application Markup Language (XAML) to provide a declarative model for application programming. WPF applications are based on a vector graphics architecture. This enables applications to look great on high DPI... -
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Stakpak
Ship your code, on autopilot. An open source agent
Stakpak is an open-source autonomous DevOps agent designed to run continuously on a machine, managing infrastructure, deployments, and operational tasks with minimal human intervention. It acts as a persistent system-level assistant that monitors applications, executes DevOps workflows, and only alerts humans when necessary, effectively automating routine operational responsibilities. The agent is built with strong safety considerations, including guardrails that prevent destructive actions... -
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Holochain
The current, performant & industrial strength version of Holochain
Holochain is a post-blockchain framework for building agent-centric, distributed applications. Instead of using global consensus, Holochain enables each agent (user) to maintain their own local state while validating actions with a shared set of rules. This allows for scalable, secure, and resilient apps where data is owned and controlled by users. Ideal for social apps, cooperatives, and data sovereignty platforms, Holochain focuses on enabling collaboration without central servers or... -
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Agents.jl
Agent-based modeling framework in Julia
Agents.jl is a pure Julia framework for agent-based modeling (ABM): a computational simulation methodology where autonomous agents react to their environment (including other agents) given a predefined set of rules. The simplicity of Agents.jl is due to the intuitive space-agnostic modeling approach we have implemented: agent actions are specified using generically named functions (such as "move agent" or "find nearby agents") that do not depend on the actual space the agents exist in, nor... -
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SIA
AI framework to autonomously improve the performance of any AI system
SIA is a self-improving AI framework designed to improve the performance of models or agents on benchmark tasks. It uses an iterative loop where a meta-agent creates or updates a task-specific target agent, while a feedback agent studies results and proposes improvements. The framework can refine both the harness around the task and the agent implementation itself. It is aimed at research and experimentation across tasks such as machine learning benchmarks, legal classification, code... -
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OWL
Optimized Workforce Learning for General Multi-Agent Assistance
OWL (Optimized Workforce Learning) is a sophisticated open-source framework built on the CAMEL-AI ecosystem for orchestrating teams of AI agents to collaboratively solve complex, real-world tasks with dynamic planning and automation capabilities. Unlike single-agent systems, it treats task completion as a collaborative workforce where agents take on specialized roles (planning, execution, analysis) and coordinate via a modular multi-agent architecture that supports flexible teamwork across... -
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Make It heavy
A Python framework that emulates Grok Heavy functionality
Make It heavy is a Python framework for producing deeper AI analysis through multi-agent orchestration. It is designed to emulate the style of Grok Heavy by splitting a user query into several specialized research angles. The system runs four agents in parallel so each one can explore the problem from a different perspective. It then combines their outputs into one unified answer through an intelligent synthesis step. The framework uses OpenRouter for model access and can also run in... -
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Armbian Linux Build Framework
Armbian Linux Build Framework
Powerful menu-driven configuration tool along with stock Debian utilities. BASH shell and lightweight XFCE-based desktop. Standard boot, config, and update methods with minimal user-space footprint. Special config utilities are optional. A distributed image is compressed to its real data size which starts below 1G. Login is possible via serial, HDMI/VGA or SSH. Boot loader and kernel optimizations, memory caching, ZRAM swap, and video acceleration where applicable. Images are made fully... -
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OpenAI Agents JS
A lightweight, powerful framework for multi-agent workflows
openai-agents-js is the JavaScript/TypeScript version of the OpenAI Agents SDK, designed to give developers a lightweight but powerful framework for building agentic workflows, voice agents, and tool-augmented LLM systems in JS/TS environments. The SDK is provider-agnostic, meaning while it’s deeply compatible with OpenAI’s APIs, you can also adapt it to use other backends or extension layers. At its core, it introduces primitives like Agents, Tools, Guardrails, and Handoffs, letting you... -
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TradingAgents
Chinese Financial Trading Framework Based on Multi-Agent LLM
TradingAgents-CN is a Chinese-enhanced, multi-agent LLM framework aimed at building financial analysis and trading-oriented workflows, with an emphasis on collaboration between specialized agents rather than a single monolithic prompt. It organizes market-related tasks into roles and stages so different agents can contribute research, reasoning, aggregation, and decision support in a structured pipeline. The project is oriented toward practical usage, including a stack that can be run in a... -
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BotSharp
AI Multi-Agent Framework in .NET
Conversation as a platform (CaaP) is the future, so it's perfect that we're already offering the whole toolkits to our .NET developers using the BotSharp AI BOT Platform Builder to build a CaaP. It opens up as much learning power as possible for your own robots and precisely control every step of the AI processing pipeline. BotSharp is an open source machine learning framework for AI Bot platform builder. This project involves natural language understanding, computer vision and audio... -
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PydanticAI
Agent Framework / shim to use Pydantic with LLMs
When I first found FastAPI, I got it immediately. I was excited to find something so innovative and ergonomic built on Pydantic. Virtually every Agent Framework and LLM library in Python uses Pydantic, but when we began to use LLMs in Pydantic Logfire, I couldn't find anything that gave me the same feeling. PydanticAI is a Python Agent Framework designed to make it less painful to build production-grade applications with Generative AI. Built by the team behind Pydantic (the validation layer... -
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e2e
Next generation e2e testing framework for web and mobile apps
e2e is an agentic end-to-end testing framework for web and mobile applications. Tests can describe user goals in natural language while still using conventional locators and assertions for verification. Agent actions that lead to verified results are recorded and replayed on later runs without additional model calls unless the application changes. Its web engine supports Chromium, Firefox, and WebKit through Playwright. Mobile testing targets iOS simulators and Android emulators, with hosted... -
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Trellis AI
All-in-one AI framework & toolkit for Claude Code & Cursor
Trellis is an advanced workflow and agent orchestration framework designed for building, managing, and scaling intelligent applications that coordinate numerous autonomous components. At its core, Trellis lets developers define units of work — called tasks or agents — and compose them into rich workflows that can operate with concurrency, conditional logic, and dynamic branching, all without sacrificing readability or control. It emphasizes modular design, encouraging users to encapsulate... -
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NUnit 3 Framework
NUnit 3 Framework
NUnit is a unit-testing framework for all .Net languages. Initially ported from JUnit, the current production release, version 3, has been completely rewritten with many new features and support for a wide range of .NET platforms. NUnit is intended to be extensible. We can't do everything for everybody but we want to make it reasonably easy to extend NUnit. In many cases, users will be able to implement a special feature outside of our scope by simply creating a new attribute that embeds the... -
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AI Berkshire
AI-era Berkshire: a value investing research framework
AI Berkshire is an AI-assisted value investing research framework designed for Claude Code and Codex workflows. It turns the investment methods of Warren Buffett, Charlie Munger, Duan Yongping, and Li Lu into structured research agents. The project is meant to improve research depth, decision discipline, and analytical consistency compared with asking a general AI model for a one-off stock opinion. It uses parallel agent analysis, adversarial viewpoints, financial rigor checks, and... -
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Kreuzberg
Polyglot document intelligence framework
Kreuzberg is a flexible task orchestration and agent workflow platform designed to help developers build, coordinate, and scale intelligent agents or automation pipelines that interact with external services, runtime environments, and multi-step business workflows. It emphasizes modular design so that developers can define discrete tasks or “actions” and then compose them into complex flows where dependencies, parallel steps, and error handling are declaratively managed. This structure makes... -
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Motia
Multi-Language Backend Framework that unifies APIs
Motia is a large-scale, multi-language backend framework designed to unify and simplify core backend concerns — from APIs and background jobs to distributed workflows, streams, and advanced AI agent integration — through a single coherent primitive with built-in observability and state management. It provides a unified development philosophy that seamlessly bridges different backend patterns (queues, event streams, scheduled jobs) while offering integrated tools for telemetry, logging,... -
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Hexabot
Hexabot is an open-source AI chatbot / agent builder
Hexabot is an open-source chatbot and conversational AI platform designed to provide a modular and extensible environment for building intelligent assistants. It combines a visual interface with backend flexibility, allowing developers and non-technical users to design conversational flows, integrate APIs, and manage interactions in a structured way. The platform supports both rule-based and AI-driven interactions, enabling hybrid chatbot systems that can handle deterministic workflows...
