"""Data pipeline agent entry point.

Extracts, transforms, and loads records on a daily schedule.
Runs at 02:00 UTC via cron: ``0 2 * * *``.
"""

from __future__ import annotations

from typing import Any


def run() -> dict[str, Any]:
    """Execute the daily ETL pipeline.

    Returns
    -------
    dict
        Keys: ``rows_read`` (int), ``rows_written`` (int),
        ``errors`` (list[str]).

    Example integration with LangChain
    -----------------------------------
    .. code-block:: python

        from langchain.agents import AgentExecutor, create_openai_tools_agent
        from langchain_openai import ChatOpenAI

        llm = ChatOpenAI(model="gpt-4o")
        tools = [read_source_database, write_destination_database, notify_data_team]
        agent = create_openai_tools_agent(llm, tools, prompt)
        executor = AgentExecutor(agent=agent, tools=tools)
        result = executor.invoke({"run_date": "today"})
    """
    # TODO: implement real ETL logic
    print("Running daily ETL pipeline")
    return {"rows_read": 0, "rows_written": 0, "errors": []}


def main() -> None:
    """Run the agent in standalone mode (for local testing)."""
    result = run()
    print(f"Result: {result}")


if __name__ == "__main__":
    main()
