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Offered By: IBMSkillsNetwork

AutoGen Wardrobe Wizard: A MultiAgent Fashion System

Learn how to combine Meta's Llama vision model, OpenAI’s DALL·E, and Microsoft’s AutoGen, a framework for orchestrating collaborative AI agents, to build an AI-powered virtual fashion stylist. This project uses modular agents such as a Color Analyst, Style Planner, Silhouette Analyst, and Outfit Board Creator to generate personalised outfit recommendations based on your uploaded photos. By the end, you’ll have a complete multi-agent system that blends computer vision, intelligent coordination, and creative design for real-world fashion use.

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Guided Project

Artificial Intelligence

At a Glance

Learn how to combine Meta's Llama vision model, OpenAI’s DALL·E, and Microsoft’s AutoGen, a framework for orchestrating collaborative AI agents, to build an AI-powered virtual fashion stylist. This project uses modular agents such as a Color Analyst, Style Planner, Silhouette Analyst, and Outfit Board Creator to generate personalised outfit recommendations based on your uploaded photos. By the end, you’ll have a complete multi-agent system that blends computer vision, intelligent coordination, and creative design for real-world fashion use.

Choosing the perfect outfit can often feel overwhelming—but not anymore. AutoGen Wardrobe Wizard is a multi-agent AI system designed to help you effortlessly plan stylish looks tailored to your wardrobe, personal style, and the occasion.

The process begins with Meta's Llama vision model, which analyses your uploaded photo and extracts clothing items to build a digital wardrobe—laying the groundwork for personalised recommendations.
Powered by Microsoft’s AutoGen framework, the system brings together a team of specialised AI agents that function like your own virtual styling team:
  • Color Analyst picks colors that complement your skin tone
  • Style Planner recommends outfit types based on your preferences and the occasion
  • Silhouette Analyst suggests flattering cuts and designs
  • Outfit Board Creator assembles everything into a cohesive final look
To complete the experience, OpenAI’s DALL·E generates a photorealistic outfit board, presenting your styled ensemble in a magazine-inspired flat lay.

By the end of this project, you'll have created a smart fashion assistant that combines visual recognition, collaborative AI, and creative design. It's a fun, real-world example of how multi-agent systems can solve everyday problems—with intelligence and style.

A Look at the Project Ahead

After completing this guided project, you will be able to do:
  • Understand AutoGen’s multi-agent architecture – Learn how to define and coordinate specialized agents to simulate real-world fashion consulting workflows.
  • Build intelligent fashion agents – Create agents with defined roles such as color analysis, style planning, and style advising.
  • Orchestrate collaborative outfit generation – Combine individual agent insights to produce a cohesive final outfit recommendation.
  • Learn to build and run agent workflows with AutoGen – Use Python and AutoGen to define agents, manage communication, and control task execution.
  • Generate visual outputs with DALL·E – Transform final outfit descriptions into AI-generated fashion boards using prompt-based image generation.
  • Deliver personalized styling experiences – Generate tailored fashion suggestions based on user profile inputs like skin tone, occasion, and preferences.

What You'll Need

Technical Requirements: A basic understanding of Python programming. Familiarity with AI agents or large language models (LLMs) is helpful but not mandatory.
Browser Setup: A modern web browser to access the AutoGen tools, follow the guided project environment, and run your code seamlessly.

Estimated Effort

50 Minutes

Level

Intermediate

Skills You Will Learn

AI Agent, Artificial Intelligence, Autogen, Computer Vision, Generative AI, Python

Language

English

Course Code

GPXX0QCJEN

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