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Event Planning Multi-Agent System

Event Planning Multi-Agent System is a Python reference implementation that uses Microsoft Agent Framework to coordinate five specialized agents in an event-planning workflow. A central coordinator routes tasks and combines structured outputs from venue, budget, catering and logistics roles. The project also demonstrates human approval, external tool integration and Azure deployment patterns.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Event Planning Multi-Agent System — OpenViST project profile in Multi-Agent Systems.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use the project as an implementation reference when an event-planning process benefits from separate specialist agents, explicit routing and approval checkpoints. Its architecture can inform other domains, but adapting it requires domain-specific roles, prompts, tools and data.

Who it is for

  • Developers studying multi-agent orchestration
  • Teams building event-planning workflows with Python and Azure services
  • Learners exploring structured agent routing, human-in-the-loop workflows, A2A and MCP concepts

Documented uses

  • Coordinate specialist agents around an event request
  • Research venue and catering options
  • Calculate budget breakdowns with a Python code interpreter
  • Check weather and create calendar events
  • Pause for user feedback and preserve workflow state
Before you choose

Requirements & limits

The repository is publicly available under the MIT License. The documented Azure deployment requires an Azure subscription and Azure CLI tooling; local use requires Python 3.11+ and uv.

  • The workflow is event-planning-specific rather than a general-purpose agent framework.
  • Azure deployment provisions Microsoft Foundry and Azure OpenAI resources through Azure Developer CLI.
  • The sample depends on several external capabilities, including web search, weather data, calendar tools and code interpretation.
  • Human-in-the-loop state management is built into the documented workflow.
  • The repository provides both an interactive console and a DevUI entry point.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Deploy the event-planning workflow to Azure

Provision the documented Azure resources, install dependencies and prepare the project for local use.

Before you start

  • Python 3.11 or later
  • uv
  • Azure CLI
  • Azure Developer CLI
  • An Azure subscription

Steps

  1. Clone the repository and change into its directory.

  2. Authenticate with Azure using az login and azd auth login.

  3. Run azd up to provision resources, generate the .env file and install dependencies with uv sync.

Expected outcome

The project is provisioned with Microsoft Foundry, Azure OpenAI models and generated connection details for the workflow.

Guide limitations

  • This guide documents setup and provisioning; it does not independently verify a successful deployment.
  • The repository lists an optional container deployment resource but does not make it part of these steps.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
3 October 2026
Original website title
microsoft/spec-to-agents · Official homepage title · retained in its source language
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