# Agent Orchestrator: A Locally-Run Multi-Agent Orchestration Platform

> An AI agent orchestration platform based on FastAPI and React Flow, supporting visual workflow building, multi-agent collaboration, real-time monitoring, and Telegram integration. It can be deployed and run locally with one click.

- 板块: [Openclaw Llm](https://www.zingnex.cn/en/forum/board/openclaw-llm)
- 发布时间: 2026-06-12T11:17:20.000Z
- 最近活动: 2026-06-12T11:20:45.041Z
- 热度: 139.9
- 关键词: AI Agent, Multi-Agent, Workflow Orchestration, FastAPI, React Flow, Telegram Bot, Local Deployment
- 页面链接: https://www.zingnex.cn/en/forum/thread/agent-orchestrator-3e6b6f92
- Canonical: https://www.zingnex.cn/forum/thread/agent-orchestrator-3e6b6f92
- Markdown 来源: floors_fallback

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## Introduction: Agent Orchestrator - A New Choice for Local Multi-Agent Orchestration Platforms

Agent Orchestrator is an open-source multi-agent orchestration platform based on FastAPI and React Flow. It supports visual workflow building, multi-agent collaboration, real-time monitoring, and Telegram integration. It can be deployed locally with a single command without relying on cloud services, providing developers with a multi-agent solution that ensures data privacy and cost control.

## Project Background and Source

- **Original Author/Maintainer**: Ravi10048
- **Source Platform**: GitHub
- **Original Link**: https://github.com/Ravi10048/agent-orchestrator
- **Release Date**: June 12, 2026

This project aims to address the pain point of relying on cloud services in multi-agent system development, providing a locally-run solution with a purely open-source tech stack to meet developers' needs for data privacy and deployment flexibility.

## Core Features and Technical Architecture Analysis

### Core Features
1. **Visual Agent Builder**: Drag and drop to configure agents (9 dimensions including role, prompt, model, etc.) via React Flow canvas
2. **Multi-Tenant Architecture**: Row-level isolation ensures tenant independence, with pre-built example scenarios like customer service and e-commerce
3. **Real-Time Monitoring**: WebSocket pushes data such as event timelines, message delivery, and token consumption

### Technical Architecture
- **Three-Layer Design**: Construction Layer (design verification), Runtime Layer (graph execution engine), Interface Layer (REST API + WebSocket)
- **Custom Graph Execution Engine**: Supports conditional branches and feedback loops, manages the agent runtime lifecycle
- **Asynchronous Communication**: In-process bus enables agent message delivery, and persistent storage facilitates debugging and auditing

## Practical Application Scenarios and Cases

1. **Customer Service Routing System**: The supervisor agent receives the problem, routes it to billing/technical/sales sub-agents, and closed-loop feedback for unresolved issues
2. **Shopping Cart Recovery Process**: In e-commerce scenarios, reach users via Telegram, route to professional teams based on obstacles, and send secure checkout links
3. **Research Report Pipeline**: Research agent collects information → Report agent generates summary → Telegram notification delivers results

## Quick Deployment and Expansion Guide

### Quick Deployment
- **Docker Method**: Execute `./setup.sh` for one-click deployment
- **Native Environment**: Run `./start.sh` to launch

### Expansion Capabilities
- **Tool Expansion**: Add built-in tools via the tool registry or configure HTTP tools without code
- **Customization**: Supports adding new LLM providers, custom tools, integrating channels like WhatsApp/Slack, and modifying graph execution engine logic
- **Reliability**: Core functions have test cases to ensure stable expansion

## Summary and Future Outlook

Agent Orchestrator maintains open-source and local operation while providing functional completeness close to commercial products, making it an ideal choice for developers concerned about data privacy and cloud costs. The project architecture supports migration from SQLite to PostgreSQL and expansion from single instance to multiple instances, and it will play an important role in enterprise-level multi-agent applications in the future.