diff --git a/astrbot/core/db/plugin/sqlite_impl.py b/astrbot/core/db/plugin/sqlite_impl.py
deleted file mode 100644
index 53cfb828..00000000
--- a/astrbot/core/db/plugin/sqlite_impl.py
+++ /dev/null
@@ -1,113 +0,0 @@
-import json
-import aiosqlite
-import os
-from typing import Any
-from .plugin_storage import PluginStorage
-from astrbot.core.utils.astrbot_path import get_astrbot_data_path
-
-DBPATH = os.path.join(get_astrbot_data_path(), "plugin_data", "sqlite", "plugin_data.db")
-
-
-class SQLitePluginStorage(PluginStorage):
-    """插件数据的 SQLite 存储实现类。
-
-    该类提供异步方式将插件数据存储到 SQLite 数据库中，支持数据的增删改查操作。
-    所有数据以 (plugin, key) 作为复合主键进行索引。
-    """
-
-    _instance = None  # Standalone instance of the class
-    _db_conn = None
-    db_path = None
-
-    def __new__(cls):
-        """
-        创建或获取 SQLitePluginStorage 的单例实例。
-        如果实例已存在，则返回现有实例；否则创建一个新实例。
-        数据在 `data/plugin_data/sqlite/plugin_data.db` 下。
-        """
-        os.makedirs(os.path.dirname(DBPATH), exist_ok=True)
-        if cls._instance is None:
-            cls._instance = super(SQLitePluginStorage, cls).__new__(cls)
-            cls._instance.db_path = DBPATH
-        return cls._instance
-
-    async def _init_db(self):
-        """初始化数据库连接（只执行一次）"""
-        if SQLitePluginStorage._db_conn is None:
-            SQLitePluginStorage._db_conn = await aiosqlite.connect(self.db_path)
-            await self._setup_db()
-
-    async def _setup_db(self):
-        """
-        异步初始化数据库。
-
-        创建插件数据表，如果表不存在则创建，表结构包含 plugin、key 和 value 字段，
-        其中 plugin 和 key 组合作为主键。
-        """
-        await self._db_conn.execute("""
-            CREATE TABLE IF NOT EXISTS plugin_data (
-                plugin TEXT,
-                key TEXT,
-                value TEXT,
-                PRIMARY KEY (plugin, key)
-            )
-        """)
-        await self._db_conn.commit()
-
-    async def set(self, plugin: str, key: str, value: Any):
-        """
-        异步存储数据。
-
-        将指定插件的键值对存入数据库，如果键已存在则更新值。
-        值会被序列化为 JSON 字符串后存储。
-
-        Args:
-            plugin: 插件标识符
-            key: 数据键名
-            value: 要存储的数据值（任意类型，将被 JSON 序列化）
-        """
-        await self._init_db()
-        await self._db_conn.execute(
-            "INSERT INTO plugin_data (plugin, key, value) VALUES (?, ?, ?) "
-            "ON CONFLICT(plugin, key) DO UPDATE SET value = excluded.value",
-            (plugin, key, json.dumps(value)),
-        )
-        await self._db_conn.commit()
-
-    async def get(self, plugin: str, key: str) -> Any:
-        """
-        异步获取数据。
-
-        从数据库中获取指定插件和键名对应的值，
-        返回的值会从 JSON 字符串反序列化为原始数据类型。
-
-        Args:
-            plugin: 插件标识符
-            key: 数据键名
-
-        Returns:
-            Any: 存储的数据值，如果未找到则返回 None
-        """
-        await self._init_db()
-        async with self._db_conn.execute(
-            "SELECT value FROM plugin_data WHERE plugin = ? AND key = ?",
-            (plugin, key),
-        ) as cursor:
-            row = await cursor.fetchone()
-            return json.loads(row[0]) if row else None
-
-    async def delete(self, plugin: str, key: str):
-        """
-        异步删除数据。
-
-        从数据库中删除指定插件和键名对应的数据项。
-
-        Args:
-            plugin: 插件标识符
-            key: 要删除的数据键名
-        """
-        await self._init_db()
-        await self._db_conn.execute(
-            "DELETE FROM plugin_data WHERE plugin = ? AND key = ?", (plugin, key)
-        )
-        await self._db_conn.commit()
diff --git a/astrbot/core/rag/embedding/openai_source.py b/astrbot/core/rag/embedding/openai_source.py
deleted file mode 100644
index dc09d84d..00000000
--- a/astrbot/core/rag/embedding/openai_source.py
+++ /dev/null
@@ -1,20 +0,0 @@
-from typing import List
-from openai import AsyncOpenAI
-
-
-class SimpleOpenAIEmbedding:
-    def __init__(
-        self,
-        model,
-        api_key,
-        api_base=None,
-    ) -> None:
-        self.client = AsyncOpenAI(api_key=api_key, base_url=api_base)
-        self.model = model
-
-    async def get_embedding(self, text) -> List[float]:
-        """
-        获取文本的嵌入
-        """
-        embedding = await self.client.embeddings.create(input=text, model=self.model)
-        return embedding.data[0].embedding
diff --git a/astrbot/core/rag/knowledge_db_mgr.py b/astrbot/core/rag/knowledge_db_mgr.py
deleted file mode 100644
index f1c1f386..00000000
--- a/astrbot/core/rag/knowledge_db_mgr.py
+++ /dev/null
@@ -1,95 +0,0 @@
-import os
-from typing import List, Dict
-from astrbot.core import logger
-from .store import Store
-from astrbot.core.config import AstrBotConfig
-from astrbot.core.utils.astrbot_path import get_astrbot_data_path
-
-
-class KnowledgeDBManager:
-    def __init__(self, astrbot_config: AstrBotConfig) -> None:
-        self.db_path = os.path.join(get_astrbot_data_path(), "knowledge_db")
-        self.config = astrbot_config.get("knowledge_db", {})
-        self.astrbot_config = astrbot_config
-        if not os.path.exists(self.db_path):
-            os.makedirs(self.db_path)
-        self.store_insts: Dict[str, Store] = {}
-        for name, cfg in self.config.items():
-            if cfg["strategy"] == "embedding":
-                logger.info(f"加载 Chroma Vector Store：{name}")
-                try:
-                    from .store.chroma_db import ChromaVectorStore
-                except ImportError as ie:
-                    logger.error(f"{ie} 可能未安装 chromadb 库。")
-                    continue
-                self.store_insts[name] = ChromaVectorStore(
-                    name, cfg["embedding_config"]
-                )
-            else:
-                logger.error(f"不支持的策略：{cfg['strategy']}")
-
-    async def list_knowledge_db(self) -> List[str]:
-        return [
-            f
-            for f in os.listdir(self.db_path)
-            if os.path.isfile(os.path.join(self.db_path, f))
-        ]
-
-    async def create_knowledge_db(self, name: str, config: Dict):
-        """
-        config 格式：
-        ```
-        {
-            "strategy": "embedding", # 目前只支持 embedding
-            "chunk_method": {
-                "strategy": "fixed",
-                "chunk_size": 100,
-                "overlap_size": 10
-            },
-            "embedding_config": {
-                "strategy": "openai",
-                "base_url": "",
-                "model": "",
-                "api_key": ""
-            }
-        }
-        ```
-        """
-        if name in self.config:
-            raise ValueError(f"知识库已存在：{name}")
-
-        self.config[name] = config
-        self.astrbot_config["knowledge_db"] = self.config
-        self.astrbot_config.save_config()
-
-    async def insert_record(self, name: str, text: str):
-        if name not in self.store_insts:
-            raise ValueError(f"未找到知识库：{name}")
-
-        ret = []
-        match self.config[name]["chunk_method"]["strategy"]:
-            case "fixed":
-                chunk_size = self.config[name]["chunk_method"]["chunk_size"]
-                chunk_overlap = self.config[name]["chunk_method"]["overlap_size"]
-                ret = self._fixed_chunk(text, chunk_size, chunk_overlap)
-            case _:
-                pass
-
-        for chunk in ret:
-            await self.store_insts[name].save(chunk)
-
-    async def retrive_records(self, name: str, query: str, top_n: int = 3) -> List[str]:
-        if name not in self.store_insts:
-            raise ValueError(f"未找到知识库：{name}")
-
-        inst = self.store_insts[name]
-        return await inst.query(query, top_n)
-
-    def _fixed_chunk(self, text: str, chunk_size: int, chunk_overlap: int) -> List[str]:
-        chunks = []
-        start = 0
-        while start < len(text):
-            end = start + chunk_size
-            chunks.append(text[start:end])
-            start += chunk_size - chunk_overlap
-        return chunks
diff --git a/astrbot/core/rag/store/__init__.py b/astrbot/core/rag/store/__init__.py
deleted file mode 100644
index 0e74c5a0..00000000
--- a/astrbot/core/rag/store/__init__.py
+++ /dev/null
@@ -1,9 +0,0 @@
-from typing import List
-
-
-class Store:
-    async def save(self, text: str):
-        pass
-
-    async def query(self, query: str, top_n: int = 3) -> List[str]:
-        pass
diff --git a/astrbot/core/rag/store/chroma_db.py b/astrbot/core/rag/store/chroma_db.py
deleted file mode 100644
index d4cfae94..00000000
--- a/astrbot/core/rag/store/chroma_db.py
+++ /dev/null
@@ -1,44 +0,0 @@
-import chromadb
-import uuid
-from typing import List, Dict
-from astrbot.api import logger
-from ..embedding.openai_source import SimpleOpenAIEmbedding
-from . import Store
-from astrbot.core.utils.astrbot_path import get_astrbot_data_path
-
-
-class ChromaVectorStore(Store):
-    def __init__(self, name: str, embedding_cfg: Dict) -> None:
-        import os
-        self.chroma_client = chromadb.PersistentClient(
-            path=os.path.join(get_astrbot_data_path(), "long_term_memory_chroma.db")
-        )
-        self.collection = self.chroma_client.get_or_create_collection(name=name)
-        self.embedding = None
-        if embedding_cfg["strategy"] == "openai":
-            self.embedding = SimpleOpenAIEmbedding(
-                model=embedding_cfg["model"],
-                api_key=embedding_cfg["api_key"],
-                api_base=embedding_cfg.get("base_url", None),
-            )
-
-    async def save(self, text: str, metadata: Dict = None):
-        logger.debug(f"Saving text: {text}")
-        embedding = await self.embedding.get_embedding(text)
-
-        self.collection.upsert(
-            documents=text,
-            metadatas=metadata,
-            ids=str(uuid.uuid4()),
-            embeddings=embedding,
-        )
-
-    async def query(
-        self, query: str, top_n=3, metadata_filter: Dict = None
-    ) -> List[str]:
-        embedding = await self.embedding.get_embedding(query)
-
-        results = self.collection.query(
-            query_embeddings=embedding, n_results=top_n, where=metadata_filter
-        )
-        return results["documents"][0]