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agency swarm

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Basic Information

Agency Swarm is a framework to automate and orchestrate multi-agent AI systems by enabling users to build collaborative "agencies" composed of specialized agent roles. It was created to let developers and teams model automation with real-world entities such as CEOs, developers and virtual assistants, and to simplify agent creation, communication and state management. The project is built on top of the OpenAI Assistants API and provides tooling to define agents, customize prompts, add type-safe tools, convert OpenAPI schemas into tools, and persist assistant state in a settings.json file. It includes CLI commands, agent templates and examples for running agents locally or as a backend service, and is designed for production use. The repository focuses on giving full control over prompts, tool definitions and communication flows so agencies can be tailored to specific workflows and deployed reliably.

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3734
App URL
https://github.com/VRSEN/agency-swarm
Github Repository
https://github.com/VRSEN/agency-swarm/blob/main/README.md

App Details

Features
The README highlights several concrete features: customizable agent roles with descriptions, instructions and file/schema folders; full control over prompts to avoid pre-defined restrictions; type-safe tools built with Pydantic-style validation and automatic error handling; a messaging tool that routes communication between agents according to their roles; state management of assistants stored in a settings.json file; conversion of OpenAPI schemas into tools via a ToolFactory; CLI utilities including genesis, import-agent and create-agent-template; demo modes with a web Gradio interface, terminal demo and backend completion API; and a folder template structure that organizes files, schemas, tools and instructions for each agent. The project is presented as production-ready and extensible.
Use Cases
Agency Swarm helps developers and teams create, iterate and deploy collaborative multi-agent systems by providing structure and reusable tooling. It reduces boilerplate through agent templates and a clear folder layout, makes tool creation safer with automatic type validation, and simplifies integration of external APIs by converting OpenAPI schemas into callable tools. Directional communication flows enforce predictable interactions between agents, while CLI commands accelerate agency generation, importing and local customization. Built-in demos help validate behavior in web or terminal interfaces and a backend completion API enables embedding agencies into services. Persistent state management for assistants and production-oriented design make it easier to manage long-running deployments. Planned enhancements such as asynchronous task handling and inter-agency communication aim to extend scalability and autonomy.

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