[pack]
id = "data-science-toolkit"
name = "Data Science Toolkit"
version = "1.0.0"
description = "Complete ML/AI development stack: data processing pipelines, model training, visualization, and deployment"
category = "ml"
author = "ggen-team"
repository = "https://github.com/seanchatmangpt/ggen"
license = "MIT"
production_ready = true

packages = [
    "data-pipeline-cli",
    "ai-microservice",
]

[[pack.templates]]
name = "ml-pipeline"
path = "templates/ml-pipeline"
description = "End-to-end ML pipeline template"
variables = ["model_type", "dataset", "metrics"]

[[pack.templates]]
name = "jupyter-notebook"
path = "templates/jupyter-notebook"
description = "Jupyter notebook template for experiments"
variables = ["experiment_name", "data_source"]

[pack.metadata]
test_coverage = "90%"
code_examples = 12
documentation_files = 8

tags = ["ml", "ai", "data-science", "machine-learning", "data-pipeline"]
keywords = ["machine-learning", "data-science", "ml-pipeline", "jupyter", "visualization"]

[pack.sparql_queries]
list_models = """
PREFIX ggen: <http://ggen.io/ontology#>
SELECT ?model ?name ?type ?accuracy
WHERE {
    ?model a ggen:MLModel ;
           ggen:modelName ?name ;
           ggen:modelType ?type ;
           ggen:accuracy ?accuracy .
}
"""
