Multi-model AI agent orchestrator with YAML workflows

A Rust-based AI agent orchestrator for running multi-model dev teams (Claude, Gemini, GPT) via YAML workflows and daemon scheduling.

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Multi-Model AI Agent Orchestrator

This tool provides a robust framework for orchestrating complex AI agent workflows. Designed for developers, it allows you to define and execute multi-model AI agent teams using declarative YAML configurations. The system leverages a Rust-based backend for performance and reliability, enabling seamless integration of various large language models (LLMs) like Claude, Gemini, and GPT. Its daemon scheduling capabilities ensure continuous operation and automated execution of your AI agent pipelines.

What it Does

The core functionality revolves around defining AI agent interactions and workflows in a structured YAML format. This allows for the creation of sophisticated multi-agent systems where different LLMs can be assigned specific roles and tasks. The orchestrator manages the execution flow, passing context and results between agents, and handling model API calls. It supports scheduling agent tasks, making it suitable for automated development processes, continuous integration, and background AI operations.

Key Features

Multi-Model Support: Integrates with popular LLMs including Claude, Gemini, and GPT.
YAML Workflow Definition: Declarative configuration for defining agent interactions and task sequences.
Rust-Based Backend: High-performance and reliable execution environment.
Daemon Scheduling: Enables background execution and automated task management.
Agent Orchestration: Manages communication and context flow between multiple AI agents.
Developer-Focused: Built with the needs of AI builders and developers in mind.

Who it's For

This tool is ideal for AI developers, researchers, and teams building complex AI-powered applications. If you are working with multiple LLMs and need a structured way to manage their interactions, automate AI tasks, or build sophisticated agent-based systems, this orchestrator will be invaluable. It's particularly useful for scenarios requiring continuous AI operations, automated code generation, complex data analysis pipelines, or multi-agent simulations.