feat(rag): Phase 33 RAG API 端點 — /knowledge/rag/index + query + stats

ADR-067 Phase 33: pgvector RAG 三個 HTTP 端點
- POST /knowledge/rag/index — 索引文件到 rag_chunks
- GET /knowledge/rag/query — embed→knn→生成答案
- GET /knowledge/rag/stats — chunks 統計 (透過 Service 層)
- 修正: rag_stats 移至 KnowledgeRAGService.get_stats() (leWOOOgo 積木化)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

apps/api/src/api/v1/knowledge.py

@@ -152,3 +152,48 @@ async def archive_entry(entry_id: str) -> None:
     success = await service.archive_entry(entry_id)
     if not success:
         raise HTTPException(status_code=404, detail="Knowledge entry not found")
+
+
+# =============================================================================
+# Phase 33 (ADR-067 2026-04-10): RAG pgvector 端點
+# =============================================================================
+
+@router.post("/rag/index", status_code=200)
+async def rag_index_document(body: dict) -> dict:
+    """
+    索引文件到 RAG 知識庫 (pgvector rag_chunks 表)
+
+    body: {source, source_id, title, text, metadata?}
+    """
+    from src.services.knowledge_rag_service import get_knowledge_rag_service
+    svc = get_knowledge_rag_service()
+    ok = await svc.index_document(
+        source=body.get("source", "manual"),
+        source_id=body.get("source_id", ""),
+        title=body.get("title", ""),
+        text=body.get("text", ""),
+        metadata=body.get("metadata", {}),
+    )
+    return {"ok": ok, "title": body.get("title", "")}
+
+
+@router.get("/rag/query")
+async def rag_query(
+    q: str = Query(..., min_length=1, description="RAG 查詢問題"),
+    top_k: int = Query(5, ge=1, le=20),
+) -> dict:
+    """
+    RAG 查詢 — embedding → pgvector knn → 生成繁中回答
+    """
+    from src.services.knowledge_rag_service import get_knowledge_rag_service
+    svc = get_knowledge_rag_service()
+    answer = await svc.query(q, top_k=top_k)
+    return {"question": q, "answer": answer}
+
+
+@router.get("/rag/stats")
+async def rag_stats() -> dict:
+    """RAG 知識庫統計"""
+    from src.services.knowledge_rag_service import get_knowledge_rag_service
+    svc = get_knowledge_rag_service()
+    return await svc.get_stats()

apps/api/src/services/knowledge_rag_service.py

@@ -215,6 +215,17 @@ class KnowledgeRAGService:
             start += chunk_size - overlap
         return [c for c in chunks if c.strip()]
 
+    async def get_stats(self) -> dict:
+        """RAG 知識庫統計"""
+        from src.db.base import get_db_context
+        from sqlalchemy import text
+        async with get_db_context() as db:
+            row = await db.execute(
+                text("SELECT COUNT(*) as total, COUNT(DISTINCT source) as sources FROM rag_chunks")
+            )
+            r = row.one()
+            return {"total_chunks": r.total, "sources": r.sources}
+
     async def close(self) -> None:
         if self._http and not self._http.is_closed:
             await self._http.aclose()