from __future__ import annotations

import argparse
from dataclasses import dataclass, field
from pathlib import Path


def web_search(query: str) -> str:
    """Deterministic demo search tool; replace with a real search API if needed."""
    return (
        f"Search results for {query}: LangGraph helps build stateful agents; "
        "Deep Agents combine planning, tools, memory, and file writing."
    )


@dataclass
class ScratchDeepAgent:
    virtual_files: dict[str, str] = field(default_factory=dict)

    def plan(self, task: str) -> list[str]:
        return [
            f"Сформировать поисковый запрос по теме: {task}",
            "Собрать краткую справку через web_search",
            "Сохранить результат в виртуальный файл",
            "Выгрузить виртуальные файлы на диск",
        ]

    def run(self, task: str) -> str:
        steps = self.plan(task)
        evidence = web_search(task)
        report = "# Search report\n\n" + "\n".join(f"- {step}" for step in steps)
        report += f"\n\n## Evidence\n\n{evidence}\n"
        self.virtual_files["report.md"] = report
        self.virtual_files["notes.txt"] = evidence
        return report

    def flush_files(self, output_dir: str = "agent_output") -> list[Path]:
        root = Path(output_dir)
        root.mkdir(parents=True, exist_ok=True)
        written: list[Path] = []
        for name, content in self.virtual_files.items():
            path = root / name
            path.write_text(content, encoding="utf-8")
            written.append(path)
        return written


def main() -> None:
    parser = argparse.ArgumentParser()
    parser.add_argument("task", nargs="*", default=["LangGraph agents"])
    args = parser.parse_args()
    agent = ScratchDeepAgent()
    print(agent.run(" ".join(args.task)))
    for path in agent.flush_files():
        print(f"written: {path}")


if __name__ == "__main__":
    main()