Search Results for "jade multi agent"

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.

...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 define structured multi-agent systems in a modular way. The repo includes examples showing how to build agents that call local functions, chain between agents, validate input/output, stream responses, and interact in real time (e.g. voice agents via WebRTC). It also has tracing and debugging support so you can introspect how agents executed their workflows. ...

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, metrics, and tracing to help teams maintain high visibility into production workloads. ...

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.

Sensu is an open source monitoring tool for ephemeral infrastructure and distributed applications. It is an agent-based monitoring system with built-in auto-discovery, making it very well-suited for cloud environments. Sensu uses service checks to monitor service health and collect telemetry data. It also has a number of well-defined APIs for configuration, external data input, and to provide access to Sensu's data. Sensu is extremely extensible and is commonly referred to as "the monitoring...

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. ...

SILENTTRINITY is a modern post-exploitation framework built around asynchronous, collaborative, and multi-server workflows for authorized security operations. It is powered by Python 3 and .NET’s Dynamic Language Runtime, using the author’s Bring Your Own Interpreter concept to dynamically evaluate tasks through embedded .NET scripting languages. The framework was designed to bring back some of the flexibility associated with PowerShell-style operations without directly relying on...

The purpose of the project is to develop a portable programming framework that facilitates distributed and multi-threaded programming for C++, Java, and Python. MADARA was originally developed as an agent-based middleware specifically for real-time, distributed artificial intelligence, but is now more general purpose for distributed timing, control, knowledge and reasoning, and quality-of-service. MADARA is composed of several tools and middleware, and the main entry point into the system is the Knowledge and Reasoning Language (KaRL) Engine, which provides a real-time scripting language for nanosecond execution times hooked into a flexible transport layer for distributed reasoning. ...

CArtAgO is a framework for programming and executing virtual environments in multi-agent programs.

jade4spring enables integration of the Java Agent Development Framework (JADE) in your Spring application-context.

simpA is an agent-oriented framework on top of Java providing a high-level approach to concurrent, multi-core, distributed programming.

Blackboard implements a lightweight, portable tuple space suitable for multi-agent system and distributed component design. Supports implicit invocation via content-filtered asynchronous events, blocking call semantics, and shared memory messaging.

This is a framework to develop Contexts and Agents and a Container to run them. The Container lets each Agent interact with the Context and other Agents. The agents are deployed in jar files and each one runs in an exclusive sandbox.