Search Results for "define"
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Showing 24 open source projects for "define"
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Open CoDesign
Open-source Claude Design alternative
...The architecture emphasizes privacy, with all data stored locally and no mandatory accounts or telemetry. It also includes built-in design skill modules and allows users to define custom styles and preferences. Overall, it bridges AI generation and design engineering into a unified, programmable workflow. -
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AgentForge
Extensible AGI Framework
AgentForge is a framework for creating and deploying AI agents that can perform autonomous decision-making and task execution. It enables developers to define agent behaviors, train models, and integrate AI-powered automation into various applications. -
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Claude Code Plugins
Intelligent automation and multi-agent orchestration for Claude Code
Claude Code Plugins is a lightweight framework designed to define, manage, and execute AI agents in a modular and extensible way, typically focusing on orchestrating tasks using large language models and tool integrations. The project provides abstractions for building agents that can interpret instructions, execute commands, and interact with external systems in a structured workflow. It emphasizes simplicity and composability, allowing developers to define agent behaviors through reusable components rather than monolithic logic. ... -
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Nerve
The Simple Agent Development Kit
Define agents using a clean YAML format: system prompt, task, tools, and variables — all in one file. -
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Karpathy Skills
A single CLAUDE.md file to improve Claude Code behavior
...The project focuses on reducing wrong assumptions, hidden confusion, overengineered solutions, and unnecessary edits outside the requested scope. Its principles encourage the agent to think before coding, prefer simple implementations, make surgical changes, and define verifiable success criteria. It can be installed as a Claude Code plugin or copied directly into a project as reusable instructions. Its main value is not automation, but behavioral alignment that helps coding agents produce cleaner, smaller, and more deliberate changes. -
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LangGraph
Build resilient language agents as graphs
LangGraph is a library for building stateful, multi-actor applications with LLMs, used to create agent and multi-agent workflows. Compared to other LLM frameworks, it offers these core benefits: cycles, controllability, and persistence. LangGraph allows you to define flows that involve cycles, essential for most agentic architectures, differentiating it from DAG-based solutions. As a very low-level framework, it provides fine-grained control over both the flow and state of your application, crucial for creating reliable agents. Additionally, LangGraph includes built-in persistence, enabling advanced human-in-the-loop and memory features. -
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CrewAI
Framework for orchestrating role-playing, autonomous AI agents
Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks. The power of AI collaboration has too much to offer. CrewAI is designed to enable AI agents to assume roles, share goals, and operate in a cohesive unit - much like a well-oiled crew. Whether you're building a smart assistant platform, an automated customer service ensemble, or a multi-agent research team, CrewAI... -
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Cua
Open-source infrastructure for Computer-Use Agents. Sandboxes
Cua is an open-source command-line utility and workflow orchestrator designed to help developers define, compose, and run common tasks with a unified interface, promoting consistency and reuse across projects. It introduces a declarative syntax for specifying build scripts, automation pipelines, environment setups, and project-specific commands so contributors don’t need to memorize disparate scripts or tooling across languages and ecosystems. -
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Agency Agents
A complete AI agency at your fingertips
...It is designed around the idea of “agency,” where each agent has a defined role, responsibility, and interaction pattern within a larger system. The framework enables developers to define workflows where agents communicate, delegate tasks, and share context, creating a distributed problem-solving environment. It supports modular design, allowing agents to be composed into reusable systems that can be adapted across different use cases. The project emphasizes clarity in agent responsibilities, which helps reduce ambiguity and improve reliability in multi-agent workflows. ... -
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GenericAgent
Self-evolving autonomous agent framework
The GenericAgent project is a flexible framework for building autonomous AI agents that can operate across diverse tasks and environments. It is designed around modularity, allowing developers to define agents with interchangeable components such as tools, memory systems, and reasoning strategies. The architecture emphasizes generality, enabling the same agent framework to be adapted for different domains including coding, research, and task automation. It integrates with modern language models to provide planning, execution, and iterative reasoning capabilities, making it suitable for complex workflows. ... -
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Defang
Defang CLI and sample projects
...The Defang Command Line Interface (CLI) facilitates interactions with the platform, offering installation options via shell scripts, Homebrew, Winget, Nix, or direct download. Developers can define services using compose.yaml files, which Defang utilizes to deploy applications to the cloud. -
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typeui.sh
Design system skills for agentic tools
...It focuses on improving developer productivity by reducing runtime errors and ensuring consistency across UI components. The framework integrates closely with TypeScript, allowing developers to define interfaces and components with strict type validation. It supports component-based architecture, making it easier to build scalable and maintainable applications. TypeUI also emphasizes reusability, enabling developers to create standardized components that can be shared across projects. Its design encourages clean and predictable code, which is especially valuable in large-scale applications. ... -
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GoGogot
Lightweight self-hosted AI agent
...The system is likely designed to enable rapid execution of commands and processes, acting as a bridge between manual scripting and more advanced agent frameworks. It emphasizes simplicity and speed, allowing developers to define and run tasks without heavy configuration or overhead. The architecture suggests a modular approach where tasks can be composed and reused across different contexts. It may also incorporate elements of automation pipelines, enabling sequential or conditional execution of operations. The project is particularly suited for developers who want to experiment with automation concepts without adopting complex infrastructure. ... -
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AIPex
AI browser automation assistant, no migration and privacy first
...It supports modular plugin architecture so teams can extend or customize how assistants behave based on project conventions, code standards, or tooling preferences. AIPex also includes orchestration pipelines that let teams define multi-step AI-driven transformations — for example, generating code then running validation, producing documentation, and opening change requests — all within a unified pattern. -
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AutoAgent AI
Autonomous harness engineering
AutoAgent is an experimental AI framework focused on autonomous agent engineering, where a meta-agent iteratively improves another agent’s architecture without direct human intervention. Instead of manually tuning prompts or workflows, developers define high-level goals in a configuration file, and the system continuously modifies its own tools, orchestration, and logic based on benchmark performance. It operates through a loop of testing, analyzing failures, and refining the agent’s configuration to maximize a scoring metric. The framework uses a single-file agent harness combined with structured tasks and evaluation suites to guide optimization. ... -
16
Bytebot
Bytebot is an AI desktop agent that automates computer tasks
...Bytebot can be embedded into editors, terminals, or CI/CD pipelines to provide contextual recommendations, highlight quality issues, and propose fixes based on understanding of code and project context. The framework is often extensible, allowing teams to define custom commands, workflows, or plug-ins that connect to internal APIs, coding standards, or proprietary repositories. -
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VoltAgent
Open Source TypeScript AI Agent Framework
An AI Agent Framework provides the foundational structure and tools needed to build applications powered by autonomous agents. These agents, often driven by Large Language Models (LLMs), can perceive their environment, make decisions, and take actions to achieve specific goals. Building such agents from scratch involves managing complex interactions with LLMs, handling state, connecting to external tools and data, and orchestrating workflows. VoltAgent is an open source TypeScript framework... -
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HybridClaw
The enterprise operating layer for open agents
...It is designed to work alongside modern agent ecosystems such as OpenClaw, Claude Code, and similar agentic coding tools, providing a flexible infrastructure for managing agent behaviors, workflows, and capabilities. The project emphasizes modularity, allowing developers to define and compose “skills” or capabilities that agents can invoke dynamically, enabling more adaptive and context-aware automation. HybridClaw aims to bridge the gap between isolated AI tools and fully orchestrated agent systems by enabling communication, coordination, and shared context across multiple agents or processes. It is particularly relevant in scenarios where developers want to build complex autonomous systems that interact with codebases. -
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Inkeep
Create AI Agents in a No-Code Visual Builder or TypeScript SDK
...It lets developers and non-technical users create, manage, and orchestrate multi-agent systems using both a no-code visual builder and a full TypeScript SDK, giving two ways to define agent behaviors that stay in sync with each other. Agents built with this framework can act as real-time conversational assistants — for example, handling help desk inquiries, providing internal support to teams, or driving in-app experiences — and they can be extended to automate multi-step tasks that interact with external systems like CRMs, knowledge bases, or ticketing systems. ... -
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Auto-Commenter
A Claude skill that automatically posts personalized comments
...It is framed as a “skill” that can be configured to operate in specific communities, aiming to reduce the repetitive work of staying active while still keeping comments personalized. Because it is designed for ongoing use, it typically includes setup steps for credentials, configuration, and guardrails that define where and how it should comment. -
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InfiAgent
Build your own Cowork, AI Scientist and other SoTA Agents
...The framework uses a serial multi-agent hierarchy where specialized agents coordinate in tree-structured paths for clear task delegation and minimal tool conflicts, while batch file operations and persistent workspaces ensure reproducibility and traceability. It aims to solve real-world challenges in long-horizon reasoning and execution, offering configuration-driven customization so that users can define domain-specific agents like research assistants. -
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Habitat-Lab
A modular high-level library to train embodied AI agents
...Allowing users to train agents in a wide variety of single and multi-agent tasks (e.g. navigation, rearrangement, instruction following, question answering, human following), as well as define novel tasks. Configuring and instantiating a diverse set of embodied agents, including commercial robots and humanoids, specifying their sensors and capabilities. Providing algorithms for single and multi-agent training (via imitation or reinforcement learning, or no learning at all as in SensePlanAct pipelines), as well as tools to benchmark their performance on the defined tasks using standard metrics. -
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Diplomacy Cicero
Code for Cicero, an AI agent that plays the game of Diplomacy
...The codebase is implemented primarily in Python with performance-critical components in C++ (via pybind11 bindings) and is configured to run in a high‐GPU cluster environment. Configuration is managed via protobuf files to define tasks such as self-play, benchmark agent comparisons, and RL training. The project is now archived and read-only, reflecting that it is no longer actively developed but remains publicly available for research use. -
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ReactAgent
The open-source React.js Autonomous LLM Agent
React-Agent is a framework for integrating AI-driven agents into React applications. It provides an intuitive way to build interactive UI components powered by AI models, enabling dynamic and intelligent user interfaces.
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