Results for agent-coordinate

A Rust crate for defining and managing agent coordinates including locations and goals with flexible initialization options and dynamic state management.

Equipment for orchestrating multiple agents in origin-centric networks with asymmetrical knowledge distribution.

EnhanceSwarm transforms Claude into a sophisticated development team with specialized agents for Backend, Frontend, QA, and Integration. Features detached orchestration, Bullet Train deep integration, automatic worktree merging, and comprehensive logging. Built for production Rails and Bullet Train applications.

GAIA is the mind that inhabits the Legion body. Coordinates agentic subordinate functions, drives the tick cycle, and provides channel abstraction for multi-interface communication.

Build and coordinate AI agents that work together to accomplish complex tasks.

A local PTY harness that wraps terminal AI agents (Claude, Codex, Pi) and adds a control plane for discovery, messaging, and coordination.

Kulu is a powerful orchestration tool for managing LLM agents and their data, inspired by the functionality of CrewAI models. It simplifies the process of integrating and coordinating multiple language models to solve complex problems efficiently.

RCrewAI is a powerful Ruby framework for creating autonomous AI agent crews that collaborate to solve complex tasks. Build intelligent workflows with reasoning agents, tool usage, memory systems, and human oversight. Key Features: • Multi-Agent Orchestration: Create crews of specialized AI agents that work together • Multi-LLM Support: OpenAI GPT-4, Anthropic Claude, Google Gemini, Azure OpenAI, Ollama • Rich Tool Ecosystem: Web search, file operations, SQL databases, email, code execution, PDF processing • Agent Memory: Short-term and long-term memory for learning from past executions • Human-in-the-Loop: Interactive approval workflows and collaborative decision making • Advanced Task Management: Dependencies, retries, async execution, and context sharing • Hierarchical Teams: Manager agents that coordinate and delegate to specialist agents • Production Ready: Security controls, error handling, comprehensive logging, and monitoring • Ruby-First Design: Built specifically for Ruby developers with idiomatic patterns • CLI Tools: Command-line interface for creating and managing AI crews

VSM is a small Ruby framework for building agentic systems using a Viable System Model–style architecture. It gives you Capsules: self‑contained components composed of five named systems (Operations, Coordination, Intelligence, Governance, Identity) plus an async runtime so many capsules can run concurrently.

A comprehensive Ruby implementation of a Knowledge-Based System featuring: • RETE Algorithm: Optimized forward-chaining inference engine with unlinking optimization for high-performance pattern matching • Declarative DSL: Readable, expressive syntax for rule definition with built-in condition helpers • Blackboard Architecture: Multi-agent coordination with message passing and knowledge source registration • Flexible Persistence: SQLite (durable), Redis (fast), and hybrid storage backends with audit trails • Concurrent Execution: Thread-safe auto-inference mode for real-time processing • AI Integration: Native support for LLM integration (Ollama, OpenAI) for hybrid symbolic/neural reasoning • Production Features: Session management, fact history, query API, statistics tracking Perfect for expert systems, trading algorithms, IoT monitoring, portfolio management, and AI-enhanced decision systems.

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