import argparse
import logging
import time
from pathlib import Path

from neo4j.exceptions import DriverError, Neo4jError

from techdocs_graphrag.ingestion import load_documents
from techdocs_graphrag.services import Services, build_services

RETRY_DELAY_SECONDS = 2


def parse_arguments() -> argparse.Namespace:
    parser = argparse.ArgumentParser(description="Indexe un corpus Markdown dans Neo4j.")
    parser.add_argument("data_dir", type=Path, nargs="?", default=Path("data"))
    parser.add_argument("--reset", action="store_true", help="Vide la base avant indexation.")
    parser.add_argument("--if-empty", action="store_true", help="N'indexe que si la base est vide.")
    parser.add_argument("--wait", type=int, default=0, metavar="SECONDS", help="Attend Neo4j.")
    return parser.parse_args()


def wait_for_database(services: Services, timeout_seconds: int) -> None:
    deadline = time.monotonic() + timeout_seconds
    while True:
        try:
            services.store.verify_connectivity()
            return
        except (DriverError, Neo4jError):
            if time.monotonic() >= deadline:
                raise
            time.sleep(RETRY_DELAY_SECONDS)


def main() -> None:
    logging.basicConfig(level=logging.INFO, format="%(levelname)s %(name)s: %(message)s")
    arguments = parse_arguments()
    services = build_services()
    try:
        wait_for_database(services, arguments.wait)
        if arguments.if_empty and services.store.stats()["chunks"]:
            print("Base déjà indexée.")
            return
        if arguments.reset:
            services.store.reset()
        report = services.indexer.run(
            load_documents(arguments.data_dir),
            on_progress=lambda done, total: print(f"\r{done}/{total} chunks", end="", flush=True),
        )
        print(f"\n{report}")
    finally:
        services.close()


if __name__ == "__main__":
    main()