Restore 0.1.5 version from stash

wolai-backend/app/services/simple_ai_service.py

@@ -0,0 +1,91 @@
+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()