Demo: Zava Media AI Assistant
Multi-Agent Architecture
for Image & Video Processing - Overview

Costa Rica

brown9804

Last updated: 2026-01-16

---

List of References (Click to expand)

• Foundry Models sold directly by Azure - models available
• Timelines for Foundry Models - retirement dates
• Azure OpenAI in Microsoft Foundry model deprecations and retirements - deprecation Date
• Use model router for Microsoft Foundry - model-router LLMs
• Model summary table and region availability - table summary
• Baseline architecture for an Azure Kubernetes Service (AKS) cluster
• Run your functions from a package file in Azure
• What is Microsoft Translator Pro?
• Model leaderboards in Microsoft Foundry portal (preview)
• AI Leaderboards - general ref
• How to Stream Agent Responses
• How to enable Live Streaming over Direct Line for a Copilot Studio - deployed agent?
• Azure OpenAI Responses API
• Foundry Control Plane: Managing AI agents at scale | BRK202

Important

Disclaimer: This repository contains a demo of Zava Media AI Assistant, a hybrid system using 2 Azure AI Agents (via Azure AI Agents Service) for conversational orchestration and cropping, with code-based orchestration for other media tasks (video, image generation, document processing). It features a fully automated "Zero-Touch" deployment pipeline orchestrated by Terraform, which provisions infrastructure, creates specialized AI agents in MSFT Foundry, and deploys the complete application stack. Feel free to modify this as needed, it's just a reference. Please refer TechWorkshop L300: AI Apps and Agents, and if needed contact Microsoft directly: Microsoft Sales and Support for more guidance.

E.g

Important

The deployment process typically takes 15-20 minutes

1. Adjust terraform.tfvars values
2. Initialize terraform with terraform init. Click here to understand more about the deployment process
3. Run terraform apply - this automatically handles all deployment including agent creation and configuration

Key Features

Warning

• Multi-Region Deployment: Sweden Central hosts 4 models + 2 agents, East US hosts 1 model.
• All models use GlobalStandard SKU for optimal performance and availability.

For example East US & Sweden Central:

East US	Sweden Central

• Hybrid Agent Architecture: 2 Azure AI Agents for chat-based orchestration + code-based orchestration for media processing
• Multi-Region Deployment:
  • Sweden Central: 4 models + 2 agents
    • Models: model-router, GPT-4o, Sora, FLUX.1-Kontext-pro
    • Agents: zava-media-orchestrator, vision-analyst
  • East US: 1 model (no agents)
    • Models: FLUX.2-pro
• 2 Azure AI Agents (chat-based via Responses API):
  • zava-media-orchestrator: Central request router using model-router chat model. Routes to 18+ other models
  • vision-analyst: Object detection and coordinate analysis using GPT-4o chat model with vision (provides JSON coordinates via HTTPS). ~ Analyzes images to detect objects and return bounding box coordinates as JSON. Application code handles actual image manipulation (cropping, resizing, etc.) using the provided coordinates.
• Code-Based Orchestration for generation tasks:
  • Video Generation: Direct calls to Sora (Sweden Central). ~ Video generation model (not used by agents, called directly via code)
  • Image Generation: Direct calls to FLUX.1-Kontext-pro (Sweden Central) and FLUX.2-pro (East US) ~ Image generation model (not used by agents, called directly via code).
• Real-Time Image Processing: Upload or paste images directly into the chat for immediate agent action
• Real MSFT Foundry Agents: Integrates with MSFT Foundry to create and host persistent agents across multiple projects
• Zero-Touch Deployment: A single terraform apply command handles the entire lifecycle
• Advanced Task Coordination: Inter-agent task delegation (e.g., "Crop this, then change background, then add text")
• Dynamic Configuration: All settings managed via terraform.tfvars - no code changes needed, just add your values here

Architecture Overview

Important

Agents use CHAT models only (not image generation models). GPT-4o is a chat model with vision, it can see/analyze images in conversation but doesn't generate images.

How It Works:

1. Orchestrator Agent (model-router - chat model) receives user requests and routes appropriately
2. Vision Analyst Agent (GPT-4o - chat model with vision) can SEE images in chat and provide object detection coordinates via JSON
3. Code Orchestration calls generation models directly:
   • Video generation (Sora - not an agent, direct API call)
   • Image generation (FLUX.1-Kontext-pro - not an agent, direct API call)
4. Key Distinction:
   • Agents = Chat Models (model-router, GPT-4o) for conversation and analysis
   • Code = Generation Models (Sora, FLUX) for creating videos/images
   • GPT-4o is a CHAT model that can see images, NOT an image generation model

Warning

Azure Quota and Model Availability The models deployed (model-router, GPT-4o, FLUX.2-pro, FLUX.1-Kontext-pro, Sora) require GPU capacity and are subject to Azure quotas. If you encounter deployment errors related to "Insufficient Quota", request a quota increase: Azure Support

Architecture

graph TD
    User[User] <--> UI[Media Studio UI]
    UI <--> App[FastAPI Application]
    
    App <--> Orchestrator[zava-media-orchestrator<br/>Model Router Chat Model<br/>Sweden Central]
    App <--> Vision[vision-analyst<br/>GPT-4o Chat + Vision<br/>Object Detection & Coordinates<br/>Sweden Central]
    
    App <--> CodeOrch[Code-Based Orchestration]
    
    CodeOrch --> Sora[Sora<br/>Video Generation<br/>Sweden Central]
    CodeOrch --> FLUX1[FLUX.1-Kontext-pro<br/>Image Generation<br/>Sweden Central]
    CodeOrch --> FLUX2[FLUX.2-pro<br/>Image Generation<br/>East US]
    
    subgraph "Azure AI Agents - Chat Models Only"
        Orchestrator
        Vision
    end
    
    subgraph "Sweden Central - Generation Models"
        Sora
        FLUX1
    end
    
    subgraph "East US - Generation Models"
        FLUX2
    end

Loading

Architecture Distribution:

• 2 Azure AI Agents (Sweden Central): zava-media-orchestrator (model-router), vision-analyst (GPT-4o)
• Generation Models: Sora, FLUX.1-Kontext-pro (Sweden Central), FLUX.2-pro (East US)
• Key: As now, Agents use chat models per Azure AI Agents SDK design

What Happens Under the Hood?

When you run terraform apply, the following automated sequence occurs:

1. Infrastructure Provisioning:

   • Creates Resource Group, 2 Azure AI Foundry projects (Sweden Central + East US), Key Vault, Storage Account, and Container Registry (ACR)
   • Multi-Region Model Deployment:
     • Sweden Central (4 models):
       • Model Router (Orchestrator - automatic model selection from 18+ options)
       • GPT-4o (Vision and cropping tasks)
       • Sora (Native video generation)
       • FLUX.1-Kontext-pro (Document processing and contextual understanding)
     • East US (1 model):
       • FLUX.2-pro (Background generation, thumbnail creation, artistic image manipulation)
   • All models use GlobalStandard SKU for optimal performance
   • All resources use Managed Identity for secure authentication (no API keys stored)

2. Automated Agent Creation:

   • Fully automated by Terraform: No manual intervention required
   • Installs the azure-ai-projects SDK and connects to MSFT Foundry projects in both regions
   • Creates specialized media processing agents:
     • Sweden Central: zava-media-orchestrator, vision-analyst
     • East US: No agents (Models accessed directly via code)
   • Automatically stores agent IDs in Azure Key Vault for secure access with region prefixes
   • Web app retrieves agent configuration from Key Vault automatically
   • Zero manual configuration - Terraform handles all multi-region agent deployment and setup

3. Application Deployment:

   • Builds the Docker container in the cloud (ACR Build)
   • Configures the Azure Web App with the generated Agent IDs and Managed Identity
   • Deploys the container and restarts the app

Verification

After deployment completes, verify the system:

1. Check the Web App:

   • The Terraform output will provide the application_url

   • Visit https://<your-app-name>.azurewebsites.net

   • You should see the Zava Media AI interface

     How.the.Web.App.looks.like.mp4

2. Verify Agent Architecture:

   • Go to the MSFT Foundry Portal
   • Check Sweden Central Project -> Build -> Agents:
     • Should see: zava-media-orchestrator and vision-analyst
   • Check East US Project:
     • Note: No agents are created in East US. The FLUX.2-pro model is accessed directly via code.
   • Agent IDs are automatically stored in Azure Key Vault with region prefixes and retrieved by the web app

3. Test Processing: For example:

   • Chat: Ask for information "What is GitHub Copilot?"

     

   • Image Upload: Upload an image and ask "Crop the main subject"

   • Background: "Change the background to a beach scene" (routed to East US for fast generation)

   • Thumbnail: "Create a thumbnail with the text 'AMAZING'" (routed to East US)

   • Multi-Step: "Crop the car, put it on a race track background, and add the text 'SPEED' in red"

   • Video: "Generate a 5-second video of a sunset over mountains" (Sweden Central - Sora)

   • Document: "Extract all text from this PDF" or "Summarize this document" (Sweden Central - FLUX.1-Kontext-pro)

Refresh Date: 2026-01-16