Tunisia AI Tour 2026 - Google Vertex AI Agent Workshops Series

(covering all Universities from the North to the south of Tunisia )

Building Agentic AI Workflows with xAI - From Code to Action

This repository contains the full hands-on material used in the Google Vertex AI Agent Workshop Series, delivered during the Tunisia AI Universities Tour 2026 .

It demonstrates how to build agentic AI systems step by step, starting from a local AI agent and progressing toward cloud-scale agentic workflows on Google Vertex AI, with a strong focus on explainability (xAI) and responsible AI.

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What is Tunisia AI Tour’26?

Tunisia AI Tour’26 is a nationwide educational journey bringing hands-on Agentic AI workshops to universities across Tunisia.

From data to deployment, participants do not just learn AI, they build real intelligent agents using industry tools such as Google Vertex AI.

Beyond technology, the tour is rooted in impact, with 50 percent of workshop proceeds donated to people in need through the Tunisian Red Crescent.

Education, access, and responsibility moving together across the country. 🇹🇳✨

Reach Goal : +3000 student !

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Repository Structure

Google vertex-AI agent-workshop/
│
├── local-ai-agent/                 # Demo 1: Local agent (Ollama + Python)
│   ├── agent.py
│   ├── llm.py
│   ├── main.py
│
├── agent-demo (VScode) demo 2/      # Demo 2: Agentic AI with prediction + actions
│
├── Vertex AI Agent Builder/         # Vertex AI managed agent approach
│
├── Presentation/                   # Slides used during the workshop
├── Ressources/                     # Reading material and references
│
├── GOOGLE VERTEX AI DEMO TAKEWAY.pdf
├── ressources links.pdf
└── README.md

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What You Will Learn

By following this repository, you will learn how to:

• Understand Agentic AI vs Generative AI
• Build a multi-step autonomous AI agent
• Separate LLM reasoning from agent control
• Implement planning, memory, autonomy, and stopping logic
• Add explainability (xAI) to agent decisions
• Scale agents to Vertex AI pipelines and Agent Builder

This repository is designed for:

• Students
• Developers
• Data scientists
• AI engineers
• Educators running hands-on workshops

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Architecture Overview

The workshop follows a progressive architecture, starting locally and scaling to Google Vertex AI.

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Mermaid Diagram - Agentic AI Architecture (GitHub Rendered)

flowchart TD
    U[User Goal or Prompt]

    A[AI Agent Control Layer
    Planning
    Memory
    Autonomy
    Stopping Logic]

    LLM[LLM Reasoning Engine
    Ollama or Vertex LLM]

    T[Tools and Actions
    APIs
    Models
    Databases
    External Systems]

    XAI[Explainable AI Layer
    SHAP
    Reason Logs
    Auditability]

    O[Final Output or Action]

    U --> A
    A --> LLM
    A --> T
    LLM --> A
    T --> A
    A --> XAI
    XAI --> O

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Why This Architecture Matters

• The LLM is not the agent
• The agent owns planning, memory, and decisions
• Explainability is built in by design
• The same structure works locally and in production
• This mirrors real enterprise AI systems

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DEMO 1: Local Agentic AI (From Scratch)

This demo runs 100 percent locally using Ollama and Python. No API keys. No cloud required.

[Steps for installation, code, and execution remain exactly as in the previous version]

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DEMO 2: Agentic AI + Prediction + xAI

Scenario

An AI assistant that:

1. Collects data from APIs
2. Runs predictions using a trained model
3. Explains decisions using xAI techniques
4. Acts autonomously
5. Logs every step for traceability

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Vertex AI Only Architecture

This section shows how the same agent architecture maps directly to Google Cloud Vertex AI.

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Mermaid Diagram - Vertex AI Production Architecture

flowchart TD
    U[User or Application]

    AG[Vertex AI Agent Builder
    Agent Logic
    Orchestration]

    M[Vertex AI Models
    Gemini
    Custom Models]

    P[Vertex AI Pipelines
    Workflow Automation]

    FS[Feature Store
    Data Sources]

    XAI[Vertex Explainable AI
    SHAP
    Attribution
    Monitoring]

    ACT[Actions
    APIs
    Cloud Functions
    External Systems]

    LOG[Logging
    Monitoring
    Governance]

    U --> AG
    AG --> M
    AG --> P
    AG --> ACT
    M --> XAI
    P --> LOG
    ACT --> LOG
    XAI --> LOG

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Vertex AI Components Explained

• Agent Builder Manages agent logic, autonomy, and orchestration

• Vertex AI Models LLMs and predictive models used for reasoning and inference

• Vertex Pipelines End to end workflow automation and execution

• Explainable AI Transparency, trust, and regulatory readiness

• Governance and Monitoring Logging, auditing, and production safety

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Local to Cloud Mapping

| Local Workshop Component | Vertex AI Equivalent | | ------------------------ | --------------------- | | Python Agent | Agent Builder | | Ollama LLM | Vertex LLMs | | Local Memory | Feature Store | | Python Logic | Pipelines | | Logs | Cloud Logging | | SHAP | Vertex Explainable AI |

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Teaching Notes

• Chatbots respond
• Agents decide
• xAI explains
• Production systems audit everything

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Resources

• https://docs.cloud.google.com/agent-builder/overview
• https://cloud.google.com/vertex-ai/docs
• https://codelabs.developers.google.com/building-ai-agents-vertexai
• https://cloud.google.com/discover/what-are-ai-agents
• https://bbycroft.net/llm
• https://n8n.io

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Author and Workshop Lead

Mr. Eng. Manai Mohamed Mortadha

• Senior AI Engineer , Netflix USA
• AI Expert Consultant , Tegus USA
• PhD Candidate in Explainable AI (xAI) , Saint MAry's University Canada
• International AI Speaker ( Linkedin Top AI Voice )
• CEO and Head of AI R&D at Man.AI Global
• AI Expert Reviewer & Author , Packt Publishing UK

Links :

• Social Media : https://taplink.cc/manaimortadha
• LinkedIn Profile : https://www.linkedin.com/in/mannai-mortadha/
• GitHub Portfolio : https://github.com/MortadhaMannai
• Leetcode Profile : https://leetcode.com/u/mannaimortadha898/
• Meduim Blog : https://www.google.com/url?q=https://manaimortadha.medium.com/
• Sessionize Profile: https://www.google.com/url?q=https://sessionize.com/Mortadha_Mannai
• Email : mannaimortadha898@gmail.com

Tunisia AI Universities Tour 2026 Building Agentic AI Workflows with xAI on Google Vertex AI - From Code to Action