Get Started#

Set up the AI Teaching Assistant on Windows and ingest your first course materials.

Confirm your machine meets the System Requirements before starting.

Important

Use Windows PowerShell (not Command Prompt/CMD) for all steps in this guide. PowerShell scripts (.ps1 files) will not execute in CMD — they will only open as text files.

Step 1: Prerequisites#

  • Git for Windows — Download here

  • Python 3.11 or 3.12 — Download here (check “Add Python to PATH”)

  • Visual C++ Build Tools — Required for some Python packages

Step 2: Clone The Repository#

Open PowerShell and run:

git clone --filter=blob:none --sparse https://github.com/open-edge-platform/edge-ai-suites.git -b main `
; cd edge-ai-suites `
; git sparse-checkout set education-ai-suite/ai-teaching-assistant `
; cd education-ai-suite/ai-teaching-assistant

Step 3: Run Windows Setup#

PowerShell script handles all setup (Python venv, dependencies, models):

# If prompted about execution policy, run:
# Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser

.\setup_windows.ps1

Note

This setup script also initializes the required submodules automatically.

The script will:

  1. Create and activate a Python virtual environment

  2. Download and install model files (~30-50 GB)

  3. Install all dependencies for the five services

First run may take 10-30 minutes while models are downloaded and cached.

Step 4: Start the Application#

.\start_ata.ps1

Services will start in sequence:

  • audio-analyzer (8010)

  • text-to-speech (8011)

  • rag-service (8020)

  • kiosk-core (8012)

  • ai-teaching-assistant ui (7860)

Wait for all services to show “ready” in the terminal.

Step 5: Verify All Services Are Running#

Open PowerShell and verify health:

# Audio-to-text
curl http://127.0.0.1:8010/health

# Text-to-speech
curl http://127.0.0.1:8011/health

# RAG service
curl http://127.0.0.1:8020/health

# Session orchestrator
curl http://127.0.0.1:8012/health

Each response should be: {"status": "ok"}

Step 6: Access the Web Interface#

Open your browser and navigate to:

http://127.0.0.1:7860

You should see the AI Teaching Assistant interface.

Step 7: Ingest Course Materials#

  1. In the browser, go to the “Knowledge Base” panel

  2. Click “Choose Files” and select your course material (.txt, .md, .docx, or .pdf)

  3. Click “Upload” — wait for “Upload successful” confirmation

Stopping the Application#

.\stop_ata.ps1

To stop individual services, use Ctrl+C in their respective terminal windows.

Uninstall#

The application has no installer — all files live inside the cloned repository. To uninstall, stop the services and delete the Python virtual environments (venv) along with the downloaded models, storage, and cache folders.

Warning

Deleting the storage/ folders permanently removes user data, including the RAG vector database of your ingested course materials (rag-service/storage/vector_db). Back up anything you want to keep first.

  1. Stop all services:

    .\stop_ata.ps1

  2. Run the uninstall script from the ai-teaching-assistant directory:

    .\uninstall_ata.ps1

    The script lists the folders it will delete and asks for confirmation before removing the venv, models, storage, and .cache folders for every service.

    Options:

    # Skip the confirmation prompt
.\uninstall_ata.ps1 -Yes

# Also delete the Hugging Face cache in your user profile
.\uninstall_ata.ps1 -Yes -RemoveHfCache

  3. (Optional) To remove the entire application, delete the cloned repository folder.

To reinstall later, re-run .\setup_windows.ps1 — it will recreate the virtual environments and re-download the models. Ingested course materials will need to be uploaded again.

Note

If you deleted the cloned repository folder in step 3, re-run Step 2: Clone The Repository first — setup_windows.ps1 lives inside the repo, so running it alone is not enough.

Next Steps#