A practical guide for combining text, images, and structured data using the Elysia (YG3) API.

Multimodal AI used to require complex architectures, multiple APIs, or special-purpose models. Today, thanks to the YG3 API (also known as the Elysia API), you can build unified multimodal applications — mixing text + images + tool calling + structured reasoning — through one simple, OpenAI-compatible interface.

This guide breaks down how multimodal workflows work in YG3, what they enable, and how to practically use them to build real business applications. The full notebook and runnable example live on GitHub — this article gives you the conceptual map and production thinking behind it.

Why MultiModal AI Matters in 2025

Multimodal agents unlock capabilities that single-modality text models cannot achieve:

• Understanding product photos
• Processing screenshots
• Analyzing charts or dashboards
• Reading receipts or invoices
• Reviewing UI mockups
• Interpreting documents
• Combining visual + textual reasoning in tool-calling loops

A real business workflow often includes both text and images.

The YG3 API integrates these modalities natively — no special infrastructure required — so you can build applications that see, reason, and act.

What You’ll Learn in This Guide

This tutorial walks you through:

• How multimodal messages work in YG3
• How to send images to the API
• How the model interprets and reasons about visuals
• How to combine image understanding with tool calling
• How to build unified text + image applications
• Real project examples your business can deploy

You’ll understand the logic behind multimodal prompts and how to design workflows that take advantage of visual context.

How MultiModal Input Works in the YG3 API

YG3 supports multimodal content using the OpenAI chat-completions standard.
A single message can contain multiple content blocks:

• Text
• Images
• Instructions
• Tool call requests
• System-level constraints

The model processes the entire message context holistically — meaning:

The model understands what’s happening visually and textually at the same time, and can take actions accordingly.

This unlocks a wide range of use cases.

Examples of MultiModal Reasoning

Here are the types of things the multimodal model can do:

1. Product Image → Description + Attributes

Upload a product image and ask for:

• Title
• Category
• Features
• Materials
• Pricing suggestions
• Amazon-style bullets

Useful for e-commerce automation or catalog ingestion.

2. Screenshot → Debugging & Explanation

Upload a frontend error screenshot:

• The agent explains the error
• Suggests fixes
• Opens a debugging tool
• Guides the user with code examples

This is incredibly valuable for dev-tools workflows.

3. Chart/Image → Insights + Actions

Upload a chart or dashboard snapshot:

• The model extracts metrics
• Identifies anomalies
• Suggests insights
• Writes a report
• Calls APIs or functions based on what it sees

This is the foundation of multimodal BI assistants.

4. Document Image → Structured Extraction

Upload a:

• Receipt
• Invoice
• Contract page
• Letter
• Menu

…and the model can parse it into structured fields and use tool calls to save the result.

5. UI Mockup → Frontend Code Scaffolding

Upload a design mockup:

• Generate UI code
• Build React components
• Suggest layout structure
• Create asset lists
• Provide interaction logic

Great for design → dev acceleration.

How MultiModal Tool Calling Works

This is the breakthrough.

With YG3, the model can:

1. Look at an image
2. Think → "I need to extract structured data"
3. Act → Call your tool
4. Use the result
5. Produce final output

This is multimodal ReAct — visual reasoning + action execution.

Every workflow becomes smarter when the model can see first, then act.

Building Real MultiModal Applications

Here are production-ready examples you can build today using only the YG3 API.

1. Receipt → Expense Tracker

• User uploads receipt photo
• Model extracts vendor, date, total
• Calls your add_expense() function
• Returns a summary + transaction ID

2. Screenshot → Customer Support Automation

• Customer uploads an issue screenshot
• Model identifies problem
• Calls lookup_order() or schedule_support_call()
• Resolves case automatically

3. Product Photo → Marketplace Listing Generator

Perfect for:

• eBay
• Amazon
• Poshmark
• Shopify sellers

Upload a product image → model produces everything needed for a listing.

4. Chart → Performance Insights

• Upload marketing dashboard screenshot
• Model detects trends, anomalies, or opportunities
• Calls your CRM/analytics tools
• Returns actionable insights

This is where BI becomes intelligent.

5. Whiteboard Photo → Project Breakdown

Upload a messy whiteboard photo → the agent:

• Transcribes everything
• Organizes tasks
• Assigns owners
• Calls your project management API

This is productivity superpowers.

Advantages of Using YG3 for MultiModal Projects

1. OpenAI-Compatible

Use all your existing SDK code.

2. Simple API

One endpoint handles text + images + tools.

3. Strong Visual Reasoning

Industrial-grade image understanding.

4. Tool Calling Support

Full ReAct loops with visual triggers.

5. Fast + Reliable

Optimized inference and low-latency performance.

6. Cost-Effective

Designed for real business usage.