from __future__ import annotations

import json
from typing import Dict, Optional

from app.services.supabase_rest import supabase_rest


class SimpleAIService:
    """提供在 LightRAG 不可用时的兜底回答。"""

    def summarize_document(
        self,
        *,
        query: str,
        user_id: str,
        document_id: Optional[str],
        workspace_id: Optional[str],
    ) -> Dict[str, object]:
        document = None
        if document_id:
            document = supabase_rest.select_one(
                "documents",
                {
                    "id": document_id,
                    "user_id": user_id,
                },
            )

        title = (document or {}).get("title") or "当前页面"
        raw_text = (document or {}).get("raw_text") or ""
        if not raw_text and document and document.get("content"):
            raw_text = self._blocks_to_text(document["content"])

        snippet = raw_text.strip().replace("\n", " ")
        if len(snippet) > 400:
            snippet = snippet[:400].rstrip() + "…"

        if snippet:
            summary = f"《{title}》当前摘要：{snippet}"
        else:
            summary = f"《{title}》暂未填写正文内容，可直接编辑后再次提问。"

        answer = "\n\n".join(
            [
                summary,
                f"你的问题：{query}",
                "（提示：LightRAG 暂未就绪，已使用本地摘要兜底回答）",
            ]
        )

        references = []
        if document_id:
            ref_path = f"doc://{document_id}"
            if title:
                ref_path = f"{ref_path}?title={title}"
            references.append(
                {
                    "file_path": ref_path,
                    "workspace": workspace_id or "",
                }
            )

        return {"content": answer, "references": references}

    def _blocks_to_text(self, content: object) -> str:
        if isinstance(content, str):
            return content
        if isinstance(content, list):
            parts = []
            for item in content:
                text = self._blocks_to_text(item)
                if text:
                    parts.append(text)
            return " ".join(parts)
        if isinstance(content, dict):
            if "text" in content and isinstance(content["text"], str):
                return content["text"]
            parts = []
            for value in content.values():
                text = self._blocks_to_text(value)
                if text:
                    parts.append(text)
            return " ".join(parts)
        try:
            return json.dumps(content, ensure_ascii=False)
        except TypeError:
            return ""


simple_ai_service = SimpleAIService()