from pathlib import Path
import re
import xml.etree.ElementTree as ET
from zipfile import BadZipFile, ZipFile

from agent_core.rag.ingest import ingest_document

from .models import UploadedDocument


def create_uploaded_document(scenario_id: str, uploaded_file) -> UploadedDocument:
    """
    保存上传文件的元数据记录。

    Documents 模块只记录文件与场景关系、原始名称、类型和大小，
    真正的入库动作由用户后续主动触发，避免上传阶段就耦合 RAG 流程。
    """
    extension = _detect_extension(uploaded_file.name)
    return UploadedDocument.objects.create(
        scenario_id=scenario_id,
        original_name=uploaded_file.name,
        file=uploaded_file,
        file_type=extension,
        size=uploaded_file.size,
        status=UploadedDocument.STATUS_UPLOADED,
    )


def extract_text(document: UploadedDocument) -> str:
    """
    根据文档类型选择合适的文本抽取策略。

    V1 的目标是“可演示且稳定”，因此：
    - `.txt` / `.md` 直接按文本读取
    - `.pdf` 优先走 pypdf，失败时回退为二进制容错读取
    - `.docx` 优先解析 Word XML，失败时回退为二进制容错读取
    """
    path = Path(document.file.path)
    extension = f".{document.file_type.lower().lstrip('.')}"
    if extension == ".pdf":
        return _extract_pdf_text(path)
    if extension == ".docx":
        return _extract_docx_text(path)
    return _read_text_file(path)


def index_document(document: UploadedDocument) -> UploadedDocument:
    """
    触发单个文档入库，并把成功/失败状态回写到 UploadedDocument。

    这里故意不抛业务异常给 View：
    View 层只需要知道“最终状态是什么”，而错误信息统一落到模型字段中，
    便于页面重试和演示。
    """
    try:
        text = extract_text(document)
        ingest_result = ingest_document(
            document_id=document.id,
            scenario_id=document.scenario_id,
            source_file=document.original_name,
            text=text,
            collection=document.scenario_id,
        )
        _apply_ingest_result(document, ingest_result.success, ingest_result.error)
    except Exception as exc:
        _apply_ingest_result(document, success=False, error=str(exc))
    document.save(update_fields=["status", "error_message", "updated_at"])
    return document


def _apply_ingest_result(document: UploadedDocument, success: bool, error: str = "") -> None:
    """把入库结果映射为 UploadedDocument 的稳定状态字段。"""
    if success:
        document.status = UploadedDocument.STATUS_INDEXED
        document.error_message = ""
        return
    document.status = UploadedDocument.STATUS_FAILED
    document.error_message = error


def _detect_extension(file_name: str) -> str:
    """统一将扩展名转成小写且去掉前导点，便于模型字段存储。"""
    return Path(file_name).suffix.lower().lstrip(".")


def _read_text_file(path: Path) -> str:
    """优先按 UTF-8 读取；失败时回退到系统默认编码。"""
    try:
        return path.read_text(encoding="utf-8")
    except UnicodeDecodeError:
        return path.read_text()


def _extract_pdf_text(path: Path) -> str:
    """优先使用 pypdf 抽取 PDF 文本，失败时回退到容错方案。"""
    try:
        import pypdf

        reader = pypdf.PdfReader(str(path))
        return "\n".join(page.extract_text() or "" for page in reader.pages)
    except Exception:
        return _read_binary_text_fallback(path)


def _extract_docx_text(path: Path) -> str:
    """提取 Word XML 中的可见文字内容，不追求保留样式。"""
    try:
        with ZipFile(path) as archive:
            document_xml = archive.read("word/document.xml")
        root = ET.fromstring(document_xml)
        namespace = {"w": "http://schemas.openxmlformats.org/wordprocessingml/2006/main"}
        texts = [node.text for node in root.findall(".//w:t", namespace) if node.text]
        return "\n".join(texts)
    except (BadZipFile, KeyError, ET.ParseError):
        return _read_binary_text_fallback(path)


def _read_binary_text_fallback(path: Path) -> str:
    """
    当结构化抽取失败时，退回到“尽可能保留纯文本”的保底方案。

    该方案不保证版式，但足以支撑 V1 入库和演示。
    """
    data = path.read_bytes()
    text = data.decode("utf-8", errors="ignore")
    text = re.sub(r"[\x00-\x08\x0b\x0c\x0e-\x1f]+", " ", text)
    return text.strip()