Building Intelligent Multi-Agent Systems with BeeAI: A Complete Code Guide

Introduction to BeeAI Framework

This tutorial demonstrates how to utilize the BeeAI framework to develop an intelligent multi-agent system from scratch. We cover essential components such as custom agents, specialized tools, memory management, and event monitoring to illustrate how BeeAI facilitates building cooperative and smart agents capable of complex tasks like market research, code analysis, and strategic planning.

Setting Up the Environment

We begin by installing necessary packages including the beeai-framework itself. The code attempts to import BeeAI modules and, if unavailable, falls back to a custom implementation to maintain functionality.

Mock Models and Custom Tools

To simulate language model behavior when BeeAI is not accessible, a MockChatModel is implemented. Alongside, a CustomTool base class defines the structure for tools agents can use.

MarketResearchTool

This tool provides simulated market insights such as competitor analysis, market size, growth trends, and enterprise adoption statistics, enabling agents to make data-driven decisions.

CodeAnalysisTool

Designed to evaluate code snippets, this tool analyzes structure, complexity, async patterns, error handling, and documentation. It generates suggestions to improve code quality.

Custom Agents

Each agent has a defined role, instructions, a set of tools, and memory to store interactions. Agents decide when to utilize tools and generate responses by combining tool outputs and language model reasoning.

Workflow Monitoring and Management

The WorkflowMonitor class logs events with timestamps, tracking agent actions and workflow progress. The CustomWorkflow class orchestrates multiple agents, assigns tasks, shares context, and compiles a comprehensive summary of results.

Demonstrations

Individual Tool Demo

Tests MarketResearchTool and CodeAnalysisTool independently, displaying their outputs.

Advanced Multi-Agent Workflow Demo

Three agents – MarketAnalyst, TechArchitect, and StrategicPlanner – collaboratively execute a business intelligence workflow involving market analysis, code review, and strategic planning.

Main Execution

The main function runs the demos, ensuring compatibility with environments like Google Colab by applying nest_asyncio. It guides next steps for proper BeeAI installation, configuration, and deployment.

This comprehensive guide showcases how BeeAI or a custom equivalent empowers developers to build scalable, maintainable, and production-ready multi-agent AI systems.