"""Import parsing speed-ups: slim schema without model evidence (A) + sha256 parse cache (B)."""

from __future__ import annotations

import io
from typing import Any

from docx import Document

from app.import_parser import ImportParseOutput, OpenAIResumeImportParser
from app.resume_import_service import ResumeImportService


class FakeCompletion:
    def __init__(self) -> None:
        self.calls: list[dict[str, Any]] = []

    def complete(self, **kwargs: Any) -> Any:
        self.calls.append(kwargs)
        return kwargs["schema"].model_validate(
            {
                "basics": {"name": "张三"},
                "sections": [
                    {
                        "kind": "education",
                        "heading": "教育经历",
                        "items": [{"fields": {"school": "示例大学", "major": "软件工程"}}],
                    }
                ],
                "skill_groups": [],
            }
        )


def _docx(text: str) -> bytes:
    document = Document()
    document.add_paragraph(text)
    buffer = io.BytesIO()
    document.save(buffer)
    return buffer.getvalue()


def _service(tmp_path, completion: FakeCompletion) -> ResumeImportService:
    return ResumeImportService(
        storage_root=tmp_path / "imports",
        parser=OpenAIResumeImportParser(completion=completion),
    )


def test_service_uses_slim_schema_without_model_evidence(tmp_path) -> None:
    """模型不再逐条输出 evidence 引用（本地匹配已覆盖），输出 token 与时间同降。"""
    from app.import_parser_fast import SlimImportParseOutput

    completion = FakeCompletion()
    prepared = _service(tmp_path, completion).prepare(
        file_name="r.docx", declared_mime=None, content=_docx("张三 示例大学 软件工程")
    )

    assert completion.calls[0]["schema"] is SlimImportParseOutput
    assert "evidence" not in completion.calls[0]["system_prompt"].casefold()
    assert completion.calls[0]["timeout_seconds"] == 45.0
    assert completion.calls[0]["max_attempts"] == 1
    assert prepared["document"]["sections"][0]["items"][0]["school"] == "示例大学"
    assert all(item["evidence"] for item in prepared["field_reviews"])  # 本地匹配仍然提供证据


def test_repeated_upload_of_same_file_skips_llm_parse(tmp_path) -> None:
    """同一文件跨会话重复上传命中 sha256 缓存，不再调 LLM 解析。"""
    completion = FakeCompletion()
    service = _service(tmp_path, completion)
    content = _docx("张三 示例大学 软件工程")

    first = service.prepare(file_name="a.docx", declared_mime=None, content=content)
    second = service.prepare(file_name="b.docx", declared_mime=None, content=content)

    assert len(completion.calls) == 1
    assert second["document"] == first["document"]
    assert second["sha256"] == first["sha256"]



def test_prepare_logs_timing_metadata_without_resume_content(tmp_path, monkeypatch) -> None:
    completion = FakeCompletion()
    events: list[dict[str, Any]] = []
    monkeypatch.setattr(
        "app.resume_import_service.log_ai_event",
        lambda event, **fields: events.append({"event": event, **fields}),
    )
    service = _service(tmp_path, completion)
    content = _docx("private resume text")

    service.prepare(file_name="resume.docx", declared_mime=None, content=content)
    service.prepare(file_name="resume-copy.docx", declared_mime=None, content=content)

    assert [event["event"] for event in events] == [
        "resume_import_prepared",
        "resume_import_prepared",
    ]
    first, second = events
    for event in events:
        assert {"extract_ms", "parse_ms", "validate_ms", "storage_ms", "total_ms"} <= event.keys()
        assert event["file_extension"] == ".docx"
        assert event["size_bytes"] == len(content)
        assert "content" not in event
        assert "payload" not in event
        assert "private resume text" not in str(event)
    assert first["cache_hit"] is False
    assert first["text_characters"] > 0
    assert second["cache_hit"] is True
    assert second["text_characters"] is None