fix(knowledge): asyncpg 不支援 :param::type，改用 CAST(:param AS vector)

asyncpg 使用 $1 位置參數，:emb::vector 語法導致 PostgresSyntaxError。
save_embedding 和 semantic_search 均改用 CAST(:emb AS vector) 語法。

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

apps/api/src/repositories/knowledge_repository.py

@@ -196,12 +196,14 @@ class KnowledgeDBRepository:
         return [(row.id, row.title, row.content) for row in result.fetchall()]
 
     async def save_embedding(self, entry_id: str, embedding: list[float]) -> bool:
-        """儲存向量 embedding (768 維)"""
-        # 直接用 raw SQL 寫入 pgvector 欄位
+        """儲存向量 embedding (768 維)
+
+        注意: asyncpg 不支援 :param::type 語法，必須用 CAST(:param AS vector)
+        """
         from sqlalchemy import text as sa_text
         result = await self.db.execute(
             sa_text(
-                "UPDATE knowledge_entries SET embedding = :emb::vector WHERE id = :id"
+                "UPDATE knowledge_entries SET embedding = CAST(:emb AS vector) WHERE id = :id"
             ),
             {"emb": str(embedding), "id": entry_id},
         )
@@ -221,12 +223,12 @@ class KnowledgeDBRepository:
         """
         from sqlalchemy import text as sa_text
         sql = sa_text("""
-            SELECT id, 1 - (embedding <=> :emb::vector) AS score
+            SELECT id, 1 - (embedding <=> CAST(:emb AS vector)) AS score
             FROM knowledge_entries
             WHERE status != 'ARCHIVED'
               AND embedding IS NOT NULL
-              AND 1 - (embedding <=> :emb::vector) >= :threshold
-            ORDER BY embedding <=> :emb::vector
+              AND 1 - (embedding <=> CAST(:emb AS vector)) >= :threshold
+            ORDER BY embedding <=> CAST(:emb AS vector)
             LIMIT :limit
         """)
         rows = await self.db.execute(