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.. "_examples/generative_design_ex/00-create_project_upload_data.py"
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.. only:: html

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        :ref:`Go to the end <sphx_glr_download__examples_generative_design_ex_00-create_project_upload_data.py>`
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.. rst-class:: sphx-glr-example-title

.. _sphx_glr__examples_generative_design_ex_00-create_project_upload_data.py:

.. _ref_create_project_upload_data:

Creating a GeomAI Project and Uploading Training Data
===========================================================

This example demonstrates how to connect to the instance, create a new project, and upload geometry files as training data.

Before you begin
-------------------------------------------

Make sure you have:

- Valid SimAI credentials and organization access.
- A folder containing geometry files (.vtp or .stl format).
- The ``ansys-simai-core`` library installed.

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Import necessary libraries
-------------------------------------------

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.. code-block:: Python


    import os

    import ansys.simai.core as asc
    from ansys.simai.core.errors import NotFoundError


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Configure your settings
-------------------------------------------
Update these variables with your specific settings:

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.. code-block:: Python


    ORGANIZATION = "my_organization"  # Replace with your organization name
    DATASET_PATH = "path/to/your/data/folder"  # Folder with .vtp or .stl files
    PROJECT_NAME = "new-bracket-project"  # Your project name


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Create the client
-------------------------------------------
Create a client to use the PySimAI library. This client will be the
entrypoint for all Generative Design objects.

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.. code-block:: Python


    simai_client = asc.SimAIClient(organization=ORGANIZATION)
    geomai_client = simai_client.geomai



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List all available training data:

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.. code-block:: Python


    print("\nAvailable training data:")
    available_tds = geomai_client.training_data.list()


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Create or retrieve a project
-------------------------------------------
Try to get an existing project by name, or create it if it does not exist:

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.. code-block:: Python


    try:
        project = geomai_client.projects.get(name=PROJECT_NAME)
        print(f"Using existing project: {PROJECT_NAME}")
    except NotFoundError:
        project = geomai_client.projects.create(PROJECT_NAME)
        print(f"Created new project: {PROJECT_NAME}")

    print(f"Current project: {project.name}")


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Upload training data to the project
-------------------------------------------
Loop through all geometry files in your dataset folder and upload them.
The script handles duplicates by checking if the data already exist.

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.. code-block:: Python


    print("\nUploading training data files:")
    successful_uploads = 0
    failed_uploads = 0

    for fname in os.listdir(DATASET_PATH):
        td_name = os.path.splitext(fname)[0]
        fpath = os.path.join(DATASET_PATH, fname)

        # Skip non-geometry files
        if not fname.lower().endswith((".vtp", ".stl")):
            print(f"Skipping non-geometry file: {fname}")
            continue

        # Check if training data already exist
        existing_tds = [td for td in available_tds if td.name == td_name]
        if existing_tds:
            print(f"Training data '{fname}' already exists in the datalake. Skipping upload.")
            td = existing_tds[0]
            try:
                td.add_to_project(project)
                print(f"✓ Added existing '{fname}' to project '{project.name}'")
                successful_uploads += 1
            except Exception as e:
                print(f"✗ Failed to add existing '{fname}' to project: {e}")
                failed_uploads += 1
            continue

        # Upload new training data
        try:
            training_data = geomai_client.training_data.create_from_file(file=fpath, project=project)
            print(f"✓ Uploaded '{fname}' -> ID: {training_data.id}")
            successful_uploads += 1
        except Exception as e:
            print(f"✗ Failed to upload '{fname}': {e}")
            failed_uploads += 1

    print(f"\nUpload summary: {successful_uploads} successful, {failed_uploads} failed")


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Check and wait for data processing
-------------------------------------------
After uploading, the instance needs to process the geometries. This script
displays the progress of the data processing.

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.. code-block:: Python


    project_data = project.data()


    print("\nWaiting for data processing to complete...")
    for data in project_data:
        print(f"Processing '{data.name}'...")
        data.wait()
        if data.is_ready:
            print(f"✓ Data '{data.name}' is ready")
        else:
            print(f"✗ Data '{data.name}' failed: {data.failure_reason}")


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Display project status summary
-------------------------------------------
Show a summary of the project's data processing status:

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.. code-block:: Python


    project_data = project.data()

    print("\nProject Summary")
    print("=" * 50)
    ready_data = [data for data in project_data if data.is_ready]
    not_ready_data = [data for data in project_data if not data.is_ready]

    print(f"Total data in project: {len(project_data)}")
    print(f"Ready data: {len(ready_data)} of {len(project_data)}")
    print(f"Not ready data: {len(not_ready_data)} of {len(project_data)}")

    if not_ready_data:
        print(
            "\nFailed data processing details:\n"
            "Having an 'invalid geometry' means that the geometry is not compatible with Generative Design. "
            "Please check the geometry file for errors or issues (watertightness and manifold).\n"
        )
        for data in not_ready_data:
            print(f"- {data.name}: {data.failure_reason}")


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Next steps
-------------------------------------------
Once all data is ready, you can proceed to build a model.
See the next example: :ref:`ref_build_model`.


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