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from datetime import datetime, timedelta




from airflow.sdk import DAG, Asset

from airflow.providers.ai.operators import (

    LLMSchemaCompareOperator,

    LLMDataQualityOperator, 

    AnalyticsOperator

)

from airflow.operators.approval import ApprovalOperator




# Define multi-cloud assets with structured metadata




customer_s3 = Asset(

    name="customer_feed_s3",

    uri="s3://data-lake/customer/",

    conn_id="aws_default",

    schema={"id": "int32", "name": "string", "email": "string"},

    sensitivity="pii",

    format="parquet"

)


customer_postgres = Asset(

    name="customer_master_postgres", 

    uri="postgres://warehouse/public/customers",

    conn_id="postgres_default",

    schema={"customer_id": "integer", "full_name": "varchar", "email_address": "varchar"},

    sensitivity="pii"

)


with DAG(

    "intelligent_data_validation",

    start_date=datetime(2024, 1, 1),

    schedule=timedelta(hours=6),

) as dag:




    # 1. Detect schema drift between S3 feed and PostgreSQL master




    schema_drift = LLMSchemaCompareOperator(

        task_id="detect_schema_drift",

        data_sources=[customer_s3, customer_postgres],

        prompt="Identify schema mismatches that would break data loading",

        output_format="structured_report"
    )   


    # 2. Generate data quality queries for new S3 data


    generate_quality_checks = LLMDataQualityOperator(

        task_id="generate_quality_queries",

        data_sources=[customer_s3],

        prompts=[

            "Generate summary statistics queries",

            "Check for duplicate email addresses",

        ],

        dry_run=True

    )


    # 3. Human approval for generated queries (with edit capability)


    approve_queries = ApprovalOperator(

        task_id="approve_quality_queries",

        body="{{ ti.xcom_pull(task_ids='generate_quality_queries') }}",

        allow_modifications=True,

        timeout=timedelta(hours=2)

    )


    # 4. Execute approved quality checks using DataFusion

    execute_quality_checks = AnalyticsOperator(

        task_id="run_quality_analysis",

        query="{{ ti.xcom_pull(task_ids='approve_quality_queries') }}",

        data_sources=[customer_s3],

        engine="datafusion",

        output_location="s3://results/quality-reports/"

    )

    schema_drift >> generate_quality_checks >> approve_queries >> execute_quality_checks