Search Results for "coordinate"
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Showing 57 open source projects for "coordinate"
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reg-factory
Google Mail registration
...The project includes modules for email registration, platform sign-up flows, token handling, cookie export, and account workflow management. It uses local scripts and external tool integrations to coordinate browser profiles, network settings, Android-based Gmail workflows, and runtime logs. The included panel helps users launch scripts, fill parameters, monitor tool status, and review process output from one place. Because the project touches sensitive account-creation workflows, it should only be used in authorized, compliant, and non-abusive testing environments. -
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Pottery
Redis for humans
Redis is awesome, but Redis commands are not always intuitive. Pottery is a Pythonic way to access Redis. If you know how to use Python dicts, then you already know how to use Pottery. Pottery is useful for accessing Redis more easily, and also for implementing microservice resilience patterns, and it has been battle-tested in production at scale. -
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METATRON
AI-powered penetration testing assistant using local LLM on linux
METATRON is a multi-agent AI orchestration framework designed to coordinate complex workflows across multiple intelligent agents. It provides a structured system for task delegation, communication, and collaboration between agents. The framework emphasizes scalability, allowing multiple agents to work together on large or complex problems. It includes mechanisms for managing context, memory, and execution flow across tasks. -
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AG-UI
The Agent-User Interaction Protocol
...Instead of treating an AI agent as a black-box chat endpoint, AG-UI defines structured events for messages, tool calls, state changes, lifecycle updates, and user interactions. This makes it easier for developers to build agent-powered apps that stream progress, request human input, update UI state, and coordinate complex workflows. The project is especially useful for teams building copilots, workflow assistants, multi-agent products, or custom AI interfaces. Overall, AG-UI provides a shared communication layer between autonomous systems and the interfaces where people actually use them. -
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MathModelAgent
An Agent Designed for Mathematical Modeling
...The project uses a multi-agent architecture where different specialized agents handle tasks such as problem interpretation, modeling design, programming implementation, and paper writing. Through integration with multiple large language models, the system can coordinate these components to generate structured modeling solutions and formatted research papers suitable for submission. The platform also includes a code execution environment that allows generated programs to be tested, corrected, and refined during the modeling workflow. -
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Astropy
Repository for the Astropy core package
The Astropy Project is a community effort to develop a common core package for Astronomy in Python and foster an ecosystem of interoperable astronomy packages. Astropy is a Python library for use in astronomy. Learn Astropy provides a portal to all of the Astropy educational material through a single dynamically searchable web page. It allows you to filter tutorials by keywords, search for filters, and make search queries in tutorials and documentation simultaneously. The Anaconda Python... -
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Claude Code Bridge
Real-time multi-AI collaboration: Claude, Codex & Gemini
Claude Code Bridge is an open-source command-line tool designed to enable real-time collaboration between multiple AI coding assistants within a unified development environment. The system allows developers to coordinate interactions between models such as Claude, Codex, and Gemini so that they can work together on programming tasks. By maintaining persistent shared context between these models, the tool reduces redundant prompts and minimizes token usage while allowing each AI system to contribute specialized capabilities. The architecture functions as a unified launcher that manages communication between multiple AI providers and coordinates their responses within the same development session. ... -
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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 domains. OWL delivers state-of-the-art performance on benchmarks like GAIA and emphasizes real-time decision-making, web automation, rich search integration, document parsing, and multi-tool workflows, making it suitable for tasks ranging from information retrieval to interactive automation. -
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ClawTeam
ClawTeam: Agent Swarm Intelligence (One Command → Full Automation)
ClawTeam is an advanced multi-agent orchestration framework that enables AI agents to form collaborative swarms capable of solving complex tasks autonomously. Instead of relying on a single agent, the system allows a leader agent to spawn and coordinate multiple specialized sub-agents, each responsible for different aspects of a problem. These agents communicate, share insights, and dynamically adapt their strategies based on real-time feedback, creating a form of collective intelligence. The framework supports a wide range of use cases, including software development, machine learning research, financial analysis, and content production. ... -
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VoxelMorph
Unsupervised Learning for Image Registration
VoxelMorph is an open-source deep learning framework designed for medical image registration, a process that aligns multiple medical scans into a common spatial coordinate system. Traditional image registration techniques typically rely on optimization procedures that must be executed separately for each pair of images, which can be computationally expensive and slow. VoxelMorph approaches the problem using neural networks that learn to predict deformation fields that transform one image so that it aligns with another. ... -
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OM1
Modular AI runtime for robots
OM1 is an open-source AI platform designed to build autonomous agents capable of interacting with digital environments and completing complex tasks. The project focuses on creating a modular architecture where language models can coordinate with external tools, APIs, and knowledge sources to accomplish multi-step objectives. Instead of operating as simple conversational systems, OM1 agents can plan actions, retrieve information, and execute tasks across different services. The framework integrates reasoning modules, planning strategies, and tool interfaces that allow agents to operate in dynamic environments. ... -
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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 logic into reusable pieces that can be tested, versioned, and reused across projects. ... -
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Growth Lab
An end-to-end growth tool that understands the product
...It uses Codex or Claude Code as the runtime and treats natural-language conversations as the control surface. Collectors gather product, market, content, and channel evidence, while executor skills help create, publish, review, and coordinate growth work. Each growth model follows an observe-act-review loop and keeps persistent memory of evidence, actions, results, and recommended next steps. The project currently includes workflows for SEO page growth and Xiaohongshu content research, creation, compliance checks, and review. Product data and operational memory stay in the user's own workspace rather than a proprietary hosted format. -
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AWorld
Build, evaluate and train General Multi-Agent Assistance with ease
...Scalable training across environments and distributed setups. Support for multi-agent collaboration/orchestration (MAS). The system is intended to help agents evolve via experience. It provides features to help and coordinate across multiple agents. It can also scale their training across environments. -
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Claude-Flow
The leading agent orchestration platform for Claude
Claude-Flow v2 Alpha is an advanced AI orchestration and automation framework designed for enterprise-grade, large-scale AI-driven development. It enables developers to coordinate multiple specialized AI agents in real time through a hive-mind architecture, combining swarm intelligence, neural reasoning, and a powerful set of 87 Modular Control Protocol (MCP) tools. The platform supports both quick swarm tasks and persistent multi-agent sessions known as hives, facilitating distributed AI collaboration with persistent contextual memory. ... -
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Nexent
Zero-code platform for building AI agents from natural language input
...Built on the MCP ecosystem, Nexent integrates a wide range of tools, models, and data sources into a unified environment for agent creation and execution. Nexent supports multi-agent collaboration, enabling multiple intelligent agents to interact and coordinate tasks within complex workflows. It also includes capabilities for data processing, knowledge tracing, and multimodal interaction, allowing agents to work with different input and output formats. Nexent provides built-in agents for common scenarios such as productivity, travel, and daily assistance. -
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II Agent
A new open-source framework to build and deploy intelligent agents
...The architecture focuses on transforming traditional software tools into autonomous assistants capable of completing tasks independently based on user instructions. II-Agent supports integration with modern AI services and can coordinate interactions between different models and capabilities within the same workflow. -
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Qwen-2.5-VL
Qwen2.5-VL is the multimodal large language model series
Qwen2.5 is a series of large language models developed by the Qwen team at Alibaba Cloud, designed to enhance natural language understanding and generation across multiple languages. The models are available in various sizes, including 0.5B, 1.5B, 3B, 7B, 14B, 32B, and 72B parameters, catering to diverse computational requirements. Trained on a comprehensive dataset of up to 18 trillion tokens, Qwen2.5 models exhibit significant improvements in instruction following, long-text generation... -
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DATAGEN
AI-driven multi-agent research assistant automating hypothesis
...The system coordinates multiple specialized AI agents that collaborate to perform tasks such as hypothesis generation, data collection, analysis, visualization, and report creation. Instead of requiring users to manually orchestrate each stage of a research process, the platform allows these agents to coordinate automatically and handle the workflow end-to-end. The project integrates several modern AI frameworks including LangChain, LangGraph, and large language models to manage reasoning and data processing tasks. Through this architecture, the system can combine structured data analysis with natural language reasoning to generate insights and research outputs. ... -
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LatentMAS
Latent Collaboration in Multi-Agent Systems
LatentMAS is an advanced framework for multi-agent reinforcement learning (MARL) that uses latent variable modeling to bridge perception and decision-making in environments where agents must coordinate under uncertainty. It provides mechanisms for agents to learn high-level latent representations of states, which simplifies complex sensory inputs into compact, actionable embeddings that facilitate both individual policy learning and inter-agent coordination. Using this latent space, the framework enables Multi-Agent Systems (MAS) to scale more effectively in environments with high dimensionality — such as robotics, simulated physics tasks, and strategic games — by reducing redundant learning burdens and focusing agent exploration. ... -
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OpenAI Agents SDK
A lightweight, powerful framework for multi-agent workflows
The OpenAI Agents Python SDK is a powerful yet lightweight framework for developing multi-agent workflows. This framework enables developers to create and manage agents that can coordinate tasks autonomously, using a set of instructions, tools, guardrails, and handoffs. The SDK allows users to configure workflows in which agents can pass control to other agents as necessary, ensuring dynamic task management. It also includes a built-in tracing system for tracking, debugging, and optimizing agent activities. -
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Solace Agent Mesh
An event-driven framework designed to build multi-agent AI systems
...It introduces a standardized agent-to-agent communication protocol that allows different agents, regardless of their implementation or location, to exchange tasks, share data, and coordinate workflows efficiently. Solace Agent Mesh also includes orchestration mechanisms that dynamically break down user requests into smaller tasks and assign them to the most appropriate agents in real time. -
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BeeAI Framework
Build production-ready AI agents in both Python and Typescript
...It includes a unified backend layer that connects seamlessly to multiple large language model providers, allowing flexible deployment across different AI infrastructures without vendor lock-in. BeeAI also provides orchestration tools for designing dynamic workflows, enabling multiple agents to coordinate tasks through structured execution flows, retries, and parallel processing. -
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Astron Agent
Enterprise platform for building and orchestrating AI agent workflows
...It provides a development environment that combines workflow orchestration, model management, and integration with various AI tools and services. Astron Agent enables organizations to design complex agent-driven processes that coordinate models, automation tools, and enterprise systems. It also integrates robotic process automation capabilities so agents can execute tasks across digital systems instead of only generating responses. Astron Agent supports scalable and high-availability deployments, allowing teams to run reliable AI agent infrastructure in distributed environments. ... -
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WebGLM
An Efficient Web-enhanced Question Answering System
...Instead of relying solely on knowledge stored in the model’s training data, the system retrieves relevant web content and integrates it into the reasoning process. WebGLM introduces several components that coordinate this process, including a retrieval module that selects relevant web documents, a generator that produces answers, and a scoring system that evaluates the quality of generated responses. The architecture aims to improve the reliability and usefulness of AI systems that answer questions about current or external knowledge sources.
