diff --git a/astrbot/core/db/vec_db/faiss_impl/document_storage.py b/astrbot/core/db/vec_db/faiss_impl/document_storage.py
index 7a94b9d91..17c0cb3ae 100644
--- a/astrbot/core/db/vec_db/faiss_impl/document_storage.py
+++ b/astrbot/core/db/vec_db/faiss_impl/document_storage.py
@@ -14,6 +14,8 @@ class DocumentStorage:
         """Initialize the SQLite database and create the documents table if it doesn't exist."""
         if not os.path.exists(self.db_path):
             await self.connect()
+            if not self.connection:
+                raise RuntimeError("Failed to connect to the database.")
             async with self.connection.cursor() as cursor:
                 with open(self.sqlite_init_path, "r", encoding="utf-8") as f:
                     sql_script = f.read()
@@ -30,8 +32,8 @@ class DocumentStorage:
         self,
         metadata_filters: dict,
         ids: list | None = None,
-        offset: int = 0,
-        limit: int = 100,
+        offset: int | None = 0,
+        limit: int | None = 100,
     ) -> list[dict]:
         """Retrieve documents by metadata filters and ids.
 
@@ -41,6 +43,7 @@ class DocumentStorage:
         Returns:
             list: The list of document IDs(primary key, not doc_id) that match the filters.
         """
+        assert self.connection is not None, "Database connection is not initialized."
         # metadata filter -> SQL WHERE clause
         where_clauses = []
         values = []
@@ -55,8 +58,13 @@ class DocumentStorage:
 
         result = []
         async with self.connection.cursor() as cursor:
-            sql = f"SELECT * FROM documents WHERE {where_sql} ORDER BY id LIMIT ? OFFSET ?"
-            values.extend([limit, offset])
+            sql = f"SELECT * FROM documents WHERE {where_sql}"
+            if limit is not None:
+                sql += " LIMIT ?"
+                values.append(limit)
+            if offset is not None:
+                sql += " OFFSET ?"
+                values.append(offset)
 
             await cursor.execute(sql, values)
             for row in await cursor.fetchall():
@@ -72,6 +80,7 @@ class DocumentStorage:
         Returns:
             dict: The document data.
         """
+        assert self.connection is not None, "Database connection is not initialized."
         async with self.connection.cursor() as cursor:
             await cursor.execute("SELECT * FROM documents WHERE doc_id = ?", (doc_id,))
             row = await cursor.fetchone()
@@ -87,18 +96,61 @@ class DocumentStorage:
             doc_id (str): The doc_id.
             new_text (str): The new text to update the document with.
         """
+        assert self.connection is not None, "Database connection is not initialized."
         async with self.connection.cursor() as cursor:
             await cursor.execute(
                 "UPDATE documents SET text = ? WHERE doc_id = ?", (new_text, doc_id)
             )
             await self.connection.commit()
 
+    async def delete_documents(self, metadata_filters: dict):
+        """Delete documents by their metadata filters.
+
+        Args:
+            metadata_filters (dict): The metadata filters to apply.
+        """
+        assert self.connection is not None, "Database connection is not initialized."
+        async with self.connection.cursor() as cursor:
+            where_clauses = []
+            values = []
+            for key, val in metadata_filters.items():
+                where_clauses.append(f"json_extract(metadata, '$.{key}') = ?")
+                values.append(val)
+            where_sql = " AND ".join(where_clauses) or "1=1"
+            await cursor.execute(f"DELETE FROM documents WHERE {where_sql}", values)
+            await self.connection.commit()
+
+    async def count_documents(self, metadata_filters: dict | None = None) -> int:
+        """Count documents in the database.
+
+        Args:
+            metadata_filters (dict | None): Metadata filters to apply.
+
+        Returns:
+            int: The count of documents.
+        """
+        assert self.connection is not None, "Database connection is not initialized."
+        async with self.connection.cursor() as cursor:
+            sql = "SELECT COUNT(*) FROM documents"
+            values = []
+            if metadata_filters:
+                where_clauses = []
+                for key, val in metadata_filters.items():
+                    where_clauses.append(f"json_extract(metadata, '$.{key}') = ?")
+                    values.append(val)
+                where_sql = " AND ".join(where_clauses)
+                sql += f" WHERE {where_sql}"
+            await cursor.execute(sql, values)
+            count = await cursor.fetchone()
+            return count[0] if count else 0
+
     async def get_user_ids(self) -> list[str]:
         """Retrieve all user IDs from the documents table.
 
         Returns:
             list: A list of user IDs.
         """
+        assert self.connection is not None, "Database connection is not initialized."
         async with self.connection.cursor() as cursor:
             await cursor.execute("SELECT DISTINCT user_id FROM documents")
             rows = await cursor.fetchall()
diff --git a/astrbot/core/db/vec_db/faiss_impl/embedding_storage.py b/astrbot/core/db/vec_db/faiss_impl/embedding_storage.py
index 18ee3189c..f29084148 100644
--- a/astrbot/core/db/vec_db/faiss_impl/embedding_storage.py
+++ b/astrbot/core/db/vec_db/faiss_impl/embedding_storage.py
@@ -9,7 +9,7 @@ import numpy as np
 
 
 class EmbeddingStorage:
-    def __init__(self, dimension: int, path: str = None):
+    def __init__(self, dimension: int, path: str | None = None):
         self.dimension = dimension
         self.path = path
         self.index = None
@@ -18,7 +18,6 @@ class EmbeddingStorage:
         else:
             base_index = faiss.IndexFlatL2(dimension)
             self.index = faiss.IndexIDMap(base_index)
-        self.storage = {}
 
     async def insert(self, vector: np.ndarray, id: int):
         """插入向量
@@ -29,12 +28,12 @@ class EmbeddingStorage:
         Raises:
             ValueError: 如果向量的维度与存储的维度不匹配
         """
+        assert self.index is not None, "FAISS index is not initialized."
         if vector.shape[0] != self.dimension:
             raise ValueError(
                 f"向量维度不匹配, 期望: {self.dimension}, 实际: {vector.shape[0]}"
             )
         self.index.add_with_ids(vector.reshape(1, -1), np.array([id]))
-        self.storage[id] = vector
         await self.save_index()
 
     async def search(self, vector: np.ndarray, k: int) -> tuple:
@@ -46,10 +45,22 @@ class EmbeddingStorage:
         Returns:
             tuple: (距离, 索引)
         """
+        assert self.index is not None, "FAISS index is not initialized."
         faiss.normalize_L2(vector)
         distances, indices = self.index.search(vector, k)
         return distances, indices
 
+    async def delete(self, ids: list[int]):
+        """删除向量
+
+        Args:
+            ids (list[int]): 要删除的向量ID列表
+        """
+        assert self.index is not None, "FAISS index is not initialized."
+        id_array = np.array(ids, dtype=np.int64)
+        self.index.remove_ids(id_array)
+        await self.save_index()
+
     async def save_index(self):
         """保存索引
 
diff --git a/astrbot/core/db/vec_db/faiss_impl/vec_db.py b/astrbot/core/db/vec_db/faiss_impl/vec_db.py
index 7c2ae1c01..dfbfa3f31 100644
--- a/astrbot/core/db/vec_db/faiss_impl/vec_db.py
+++ b/astrbot/core/db/vec_db/faiss_impl/vec_db.py
@@ -39,6 +39,9 @@ class FaissVecDB(BaseVecDB):
         """
         插入一条文本和其对应向量，自动生成 ID 并保持一致性。
         """
+        assert self.document_storage.connection is not None, (
+            "Database connection is not initialized."
+        )
         metadata = metadata or {}
         str_id = id or str(uuid.uuid4())  # 使用 UUID 作为原始 ID
 
@@ -119,23 +122,49 @@ class FaissVecDB(BaseVecDB):
 
         return top_k_results
 
-    async def delete(self, doc_id: int):
+    async def delete(self, doc_id: str):
         """
-        删除一条文档
+        删除一条文档块（chunk）
         """
+        assert self.document_storage.connection is not None, (
+            "Database connection is not initialized."
+        )
+        # 获得对应的 int id
+        result = await self.document_storage.get_document_by_doc_id(doc_id)
+        int_id = result["id"] if result else None
+        if int_id is None:
+            return
         await self.document_storage.connection.execute(
             "DELETE FROM documents WHERE doc_id = ?", (doc_id,)
         )
+        await self.embedding_storage.delete([int_id])
         await self.document_storage.connection.commit()
 
     async def close(self):
         await self.document_storage.close()
 
-    async def count_documents(self) -> int:
+    async def count_documents(self, metadata_filter: dict | None = None) -> int:
         """
         计算文档数量
+
+        Args:
+            metadata_filter (dict | None): 元数据过滤器
         """
-        async with self.document_storage.connection.cursor() as cursor:
-            await cursor.execute("SELECT COUNT(*) FROM documents")
-            count = await cursor.fetchone()
-            return count[0] if count else 0
+        assert self.document_storage.connection is not None, (
+            "Database connection is not initialized."
+        )
+        count = await self.document_storage.count_documents(
+            metadata_filters=metadata_filter or {}
+        )
+        return count
+
+    async def delete_documents(self, metadata_filters: dict):
+        """
+        根据元数据过滤器删除文档
+        """
+        docs = await self.document_storage.get_documents(
+            metadata_filters=metadata_filters, offset=None, limit=None
+        )
+        doc_ids: list[int] = [doc["id"] for doc in docs]
+        await self.embedding_storage.delete(doc_ids)
+        await self.document_storage.delete_documents(metadata_filters=metadata_filters)
diff --git a/astrbot/core/knowledge_base/kb_db_sqlite.py b/astrbot/core/knowledge_base/kb_db_sqlite.py
index c49cdf231..77b980a9d 100644
--- a/astrbot/core/knowledge_base/kb_db_sqlite.py
+++ b/astrbot/core/knowledge_base/kb_db_sqlite.py
@@ -2,7 +2,7 @@ from contextlib import asynccontextmanager
 from pathlib import Path
 
 from sqlmodel import SQLModel, col, desc
-from sqlalchemy import text, func, select, update
+from sqlalchemy import text, func, select, update, delete
 from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker, create_async_engine
 
 from astrbot.core import logger
@@ -250,6 +250,19 @@ class KBSQLiteDatabase:
                 "knowledge_base": row[1],
             }
 
+    async def delete_document_by_id(self, doc_id: str, vec_db: FaissVecDB):
+        """删除单个文档及其相关数据"""
+        # 在知识库表中删除
+        async with self.get_db() as session:
+            async with session.begin():
+                # 删除文档记录
+                delete_stmt = delete(KBDocument).where(col(KBDocument.doc_id) == doc_id)
+                await session.execute(delete_stmt)
+                await session.commit()
+
+        # 在 vec db 中删除相关向量
+        await vec_db.delete_documents(metadata_filters={"doc_id": doc_id})
+
     # ===== 多媒体查询 =====
 
     async def list_media_by_doc(self, doc_id: str) -> list[KBMedia]:
diff --git a/astrbot/core/knowledge_base/kb_helper.py b/astrbot/core/knowledge_base/kb_helper.py
index 2a9229318..9203c7ed1 100644
--- a/astrbot/core/knowledge_base/kb_helper.py
+++ b/astrbot/core/knowledge_base/kb_helper.py
@@ -206,6 +206,26 @@ class KBHelper:
         doc = await self.kb_db.get_document_by_id(doc_id)
         return doc
 
+    async def delete_document(self, doc_id: str):
+        """删除单个文档及其相关数据"""
+        await self.kb_db.delete_document_by_id(
+            doc_id=doc_id,
+            vec_db=self.vec_db,  # type: ignore
+        )
+        await self.kb_db.update_kb_stats(
+            kb_id=self.kb.kb_id,
+            vec_db=self.vec_db,  # type: ignore
+        )
+
+    async def delete_chunk(self, chunk_id: str):
+        """删除单个文本块及其相关数据"""
+        vec_db: FaissVecDB = self.vec_db  # type: ignore
+        await vec_db.delete(chunk_id)
+        await self.kb_db.update_kb_stats(
+            kb_id=self.kb.kb_id,
+            vec_db=self.vec_db,  # type: ignore
+        )
+
     async def get_chunks_by_doc_id(
         self, doc_id: str, offset: int = 0, limit: int = 100
     ) -> list[dict]:
@@ -229,6 +249,12 @@ class KBHelper:
             )
         return result
 
+    async def get_chunk_count_by_doc_id(self, doc_id: str) -> int:
+        """获取文档的块数量"""
+        vec_db: FaissVecDB = self.vec_db  # type: ignore
+        count = await vec_db.count_documents(metadata_filter={"doc_id": doc_id})
+        return count
+
     async def _save_media(
         self,
         doc_id: str,
diff --git a/astrbot/core/knowledge_base/kb_mgr.py b/astrbot/core/knowledge_base/kb_mgr.py
index 362a60aa2..47a48af64 100644
--- a/astrbot/core/knowledge_base/kb_mgr.py
+++ b/astrbot/core/knowledge_base/kb_mgr.py
@@ -190,8 +190,7 @@ class KnowledgeBaseManager:
             kb.emoji = emoji
         if embedding_provider_id is not None:
             kb.embedding_provider_id = embedding_provider_id
-        if rerank_provider_id is not None:
-            kb.rerank_provider_id = rerank_provider_id
+        kb.rerank_provider_id = rerank_provider_id  # 允许设置为 None
         if chunk_size is not None:
             kb.chunk_size = chunk_size
         if chunk_overlap is not None:
diff --git a/astrbot/core/knowledge_base/retrieval/manager.py b/astrbot/core/knowledge_base/retrieval/manager.py
index 63d59e973..7e90cf2f6 100644
--- a/astrbot/core/knowledge_base/retrieval/manager.py
+++ b/astrbot/core/knowledge_base/retrieval/manager.py
@@ -94,6 +94,7 @@ class RetrievalManager:
                     "top_k_sparse": kb.top_k_sparse or 50,
                     "top_m_final": kb.top_m_final or 5,
                     "vec_db": kb_helper.vec_db,
+                    "rerank_provider_id": kb.rerank_provider_id,
                 }
                 new_kb_ids.append(kb_id)
             else:
@@ -147,7 +148,13 @@ class RetrievalManager:
         first_rerank = None
         for kb_id in kb_ids:
             vec_db: FaissVecDB = kb_options[kb_id]["vec_db"]
-            if vec_db and vec_db.rerank_provider:
+            rerank_pi = kb_options[kb_id]["rerank_provider_id"]
+            if (
+                vec_db
+                and vec_db.rerank_provider
+                and rerank_pi
+                and rerank_pi == vec_db.rerank_provider.meta().id
+            ):
                 first_rerank = vec_db.rerank_provider
                 break
         if first_rerank and retrieval_results:
diff --git a/astrbot/dashboard/routes/knowledge_base.py b/astrbot/dashboard/routes/knowledge_base.py
index 27e8e0662..f4f54d80b 100644
--- a/astrbot/dashboard/routes/knowledge_base.py
+++ b/astrbot/dashboard/routes/knowledge_base.py
@@ -30,8 +30,6 @@ class KnowledgeBaseRoute(Route):
 
         # 注册路由
         self.routes = {
-            # 系统管理
-            # "/kb/status": ("GET", self.get_kb_status),
             # 知识库管理
             "/kb/list": ("GET", self.list_kbs),
             "/kb/create": ("POST", self.create_kb),
@@ -43,11 +41,10 @@ class KnowledgeBaseRoute(Route):
             "/kb/document/list": ("GET", self.list_documents),
             "/kb/document/upload": ("POST", self.upload_document),
             "/kb/document/get": ("GET", self.get_document),
-            # "/kb/document/delete": ("POST", self.delete_document),
+            "/kb/document/delete": ("POST", self.delete_document),
             # # 块管理
             "/kb/chunk/list": ("GET", self.list_chunks),
-            # "/kb/chunk/get": ("GET", self.get_chunk),
-            # "/kb/chunk/delete": ("POST", self.delete_chunk),
+            "/kb/chunk/delete": ("POST", self.delete_chunk),
             # # 多媒体管理
             # "/kb/media/list": ("GET", self.list_media),
             # "/kb/media/delete": ("POST", self.delete_media),
@@ -579,6 +576,70 @@ class KnowledgeBaseRoute(Route):
             logger.error(traceback.format_exc())
             return Response().error(f"获取文档详情失败: {str(e)}").__dict__
 
+    async def delete_document(self):
+        """删除文档
+
+        Body:
+        - kb_id: 知识库 ID (必填)
+        - doc_id: 文档 ID (必填)
+        """
+        try:
+            kb_manager = self._get_kb_manager()
+            data = await request.json
+
+            kb_id = data.get("kb_id")
+            if not kb_id:
+                return Response().error("缺少参数 kb_id").__dict__
+            doc_id = data.get("doc_id")
+            if not doc_id:
+                return Response().error("缺少参数 doc_id").__dict__
+
+            kb_helper = await kb_manager.get_kb(kb_id)
+            if not kb_helper:
+                return Response().error("知识库不存在").__dict__
+
+            await kb_helper.delete_document(doc_id)
+            return Response().ok(message="删除文档成功").__dict__
+
+        except ValueError as e:
+            return Response().error(str(e)).__dict__
+        except Exception as e:
+            logger.error(f"删除文档失败: {e}")
+            logger.error(traceback.format_exc())
+            return Response().error(f"删除文档失败: {str(e)}").__dict__
+
+    async def delete_chunk(self):
+        """删除文本块
+
+        Body:
+        - kb_id: 知识库 ID (必填)
+        - chunk_id: 块 ID (必填)
+        """
+        try:
+            kb_manager = self._get_kb_manager()
+            data = await request.json
+
+            kb_id = data.get("kb_id")
+            if not kb_id:
+                return Response().error("缺少参数 kb_id").__dict__
+            chunk_id = data.get("chunk_id")
+            if not chunk_id:
+                return Response().error("缺少参数 chunk_id").__dict__
+
+            kb_helper = await kb_manager.get_kb(kb_id)
+            if not kb_helper:
+                return Response().error("知识库不存在").__dict__
+
+            await kb_helper.delete_chunk(chunk_id)
+            return Response().ok(message="删除文本块成功").__dict__
+
+        except ValueError as e:
+            return Response().error(str(e)).__dict__
+        except Exception as e:
+            logger.error(f"删除文本块失败: {e}")
+            logger.error(traceback.format_exc())
+            return Response().error(f"删除文本块失败: {str(e)}").__dict__
+
     async def list_chunks(self):
         """获取块列表
 
@@ -612,6 +673,7 @@ class KnowledgeBaseRoute(Route):
                         "items": chunk_list,
                         "page": page,
                         "page_size": page_size,
+                        "total": await kb_helper.get_chunk_count_by_doc_id(doc_id),
                     }
                 )
                 .__dict__
diff --git a/dashboard/src/i18n/locales/zh-CN/features/knowledge-base/document.json b/dashboard/src/i18n/locales/zh-CN/features/knowledge-base/document.json
index 22781666a..c90c29cc2 100644
--- a/dashboard/src/i18n/locales/zh-CN/features/knowledge-base/document.json
+++ b/dashboard/src/i18n/locales/zh-CN/features/knowledge-base/document.json
@@ -22,7 +22,10 @@
     "preview": "预览",
     "search": "搜索分块",
     "searchPlaceholder": "输入关键词搜索分块内容...",
-    "showing": "显示"
+    "showing": "显示",
+    "deleteConfirm": "确定要删除该文本块吗?",
+    "deleteSuccess": "文本块删除成功",
+    "deleteFailed": "文本块删除失败"
   },
   "edit": {
     "title": "编辑分块",
diff --git a/dashboard/src/views/knowledge-base/DocumentDetail.vue b/dashboard/src/views/knowledge-base/DocumentDetail.vue
index 5e1c22b20..e99d1a75d 100644
--- a/dashboard/src/views/knowledge-base/DocumentDetail.vue
+++ b/dashboard/src/views/knowledge-base/DocumentDetail.vue
@@ -133,6 +133,14 @@
                 color="info"
                 @click="viewChunk(item)"
               />
+              <!-- 删除 -->
+              <v-btn
+                icon="mdi-delete"
+                variant="text"
+                size="small"
+                color="error"
+                @click="deleteChunk(item)"
+              />
             </template>
 
             <template #no-data>
@@ -318,7 +326,7 @@ const loadChunks = async () => {
     })
     if (response.data.status === 'ok') {
       chunks.value = response.data.data.items || []
-      totalChunks.value = response.data.data.items.length
+      totalChunks.value = response.data.data.total || 0
     }
   } catch (error) {
     console.error('Failed to load chunks:', error)
@@ -346,6 +354,27 @@ const viewChunk = (chunk: any) => {
   showViewDialog.value = true
 }
 
+// 删除分块
+const deleteChunk = async (chunk: any) => {
+  if (!confirm(t('chunks.deleteConfirm'))) return
+  try {
+    const response = await axios.post('/api/kb/chunk/delete', {
+      chunk_id: chunk.chunk_id,
+      doc_id: docId.value,
+      kb_id: kbId.value
+    })
+    if (response.data.status === 'ok') {
+      showSnackbar(t('chunks.deleteSuccess'))
+      loadChunks()
+    } else {
+      showSnackbar(t('chunks.deleteFailed'), 'error')
+    }
+  } catch (error) {
+    console.error('Failed to delete chunk:', error)
+    showSnackbar(t('chunks.deleteFailed'), 'error')
+  }
+}
+
 // 工具函数
 const getFileIcon = (fileType: string) => {
   const type = fileType?.toLowerCase() || ''
diff --git a/dashboard/src/views/knowledge-base/components/DocumentsTab.vue b/dashboard/src/views/knowledge-base/components/DocumentsTab.vue
index 7dda40363..814443415 100644
--- a/dashboard/src/views/knowledge-base/components/DocumentsTab.vue
+++ b/dashboard/src/views/knowledge-base/components/DocumentsTab.vue
@@ -357,7 +357,8 @@ const deleteDocument = async () => {
   deleting.value = true
   try {
     const response = await axios.post('/api/kb/document/delete', {
-      doc_id: deleteTarget.value.doc_id
+      doc_id: deleteTarget.value.doc_id,
+      kb_id: props.kbId
     })
 
     if (response.data.status === 'ok') {