diff --git a/src/pages/api/chat/vectorGpt.ts b/src/pages/api/chat/vectorGpt.ts
index 704f2f9dc..2b7b38460 100644
--- a/src/pages/api/chat/vectorGpt.ts
+++ b/src/pages/api/chat/vectorGpt.ts
@@ -1,7 +1,7 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { connectToDatabase } from '@/service/mongo';
 import { authChat } from '@/service/utils/chat';
-import { httpsAgent, openaiChatFilter, systemPromptFilter } from '@/service/utils/tools';
+import { httpsAgent, systemPromptFilter } from '@/service/utils/tools';
 import { ChatCompletionRequestMessage, ChatCompletionRequestMessageRoleEnum } from 'openai';
 import { ChatItemType } from '@/types/chat';
 import { jsonRes } from '@/service/response';
@@ -9,11 +9,9 @@ import type { ModelSchema } from '@/types/mongoSchema';
 import { PassThrough } from 'stream';
 import { modelList, ModelVectorSearchModeMap, ModelVectorSearchModeEnum } from '@/constants/model';
 import { pushChatBill } from '@/service/events/pushBill';
-import { connectRedis } from '@/service/redis';
-import { VecModelDataPrefix } from '@/constants/redis';
-import { vectorToBuffer } from '@/utils/tools';
 import { openaiCreateEmbedding, gpt35StreamResponse } from '@/service/utils/openai';
 import dayjs from 'dayjs';
+import { PgClient } from '@/service/pg';
 
 /* 发送提示词 */
 export default async function handler(req: NextApiRequest, res: NextApiResponse) {
@@ -43,7 +41,6 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
     }
 
     await connectToDatabase();
-    const redis = await connectRedis();
     let startTime = Date.now();
 
     const { chat, userApiKey, systemKey, userId } = await authChat(chatId, authorization);
@@ -65,38 +62,22 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
       text: prompt.value
     });
 
+    // 相似度搜素
     const similarity = ModelVectorSearchModeMap[model.search.mode]?.similarity || 0.22;
-    // 搜索系统提示词, 按相似度从 redis 中搜出相关的 q 和 text
-    const redisData: any[] = await redis.sendCommand([
-      'FT.SEARCH',
-      `idx:${VecModelDataPrefix}:hash`,
-      `@modelId:{${String(
-        chat.modelId._id
-      )}} @vector:[VECTOR_RANGE ${similarity} $blob]=>{$YIELD_DISTANCE_AS: score}`,
-      'RETURN',
-      '1',
-      'text',
-      'SORTBY',
-      'score',
-      'PARAMS',
-      '2',
-      'blob',
-      vectorToBuffer(promptVector),
-      'LIMIT',
-      '0',
-      '30',
-      'DIALECT',
-      '2'
-    ]);
+    const vectorSearch = await PgClient.select<{ id: string; q: string; a: string }>('modelData', {
+      fields: ['id', 'q', 'a'],
+      order: [{ field: 'vector', mode: `<=> '[${promptVector}]'` }],
+      where: [
+        ['model_id', model._id],
+        'AND',
+        ['user_id', userId],
+        'AND',
+        `vector <=> '[${promptVector}]' < ${similarity}`
+      ],
+      limit: 30
+    });
 
-    const formatRedisPrompt: string[] = [];
-    // 格式化响应值，获取 qa
-    for (let i = 2; i < 61; i += 2) {
-      const text = redisData[i]?.[1];
-      if (text) {
-        formatRedisPrompt.push(text);
-      }
-    }
+    const formatRedisPrompt: string[] = vectorSearch.rows.map((item) => `${item.q}\n${item.a}`);
 
     /* 高相似度+退出，无法匹配时直接退出 */
     if (
@@ -121,9 +102,9 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
 
       prompts.unshift({
         obj: 'SYSTEM',
-        value: `${model.systemPrompt} 用知识库内容回答，知识库内容为: "当前时间:${dayjs().format(
+        value: `${model.systemPrompt} 知识库是最新的,下面是知识库内容:当前时间为${dayjs().format(
           'YYYY/MM/DD HH:mm:ss'
-        )} ${systemPrompt}"`
+        )}\n${systemPrompt}`
       });
     }
 
diff --git a/src/pages/api/model/data/exportModelData.ts b/src/pages/api/model/data/exportModelData.ts
index 215a72615..99639760b 100644
--- a/src/pages/api/model/data/exportModelData.ts
+++ b/src/pages/api/model/data/exportModelData.ts
@@ -2,8 +2,7 @@ import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase } from '@/service/mongo';
 import { authToken } from '@/service/utils/tools';
-import { connectRedis } from '@/service/redis';
-import { VecModelDataIdx } from '@/constants/redis';
+import { PgClient } from '@/service/pg';
 
 export default async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
   try {
@@ -25,28 +24,23 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse<
     const userId = await authToken(authorization);
 
     await connectToDatabase();
-    const redis = await connectRedis();
 
-    // 从 redis 中获取数据
-    const searchRes = await redis.ft.search(
-      VecModelDataIdx,
-      `@modelId:{${modelId}} @userId:{${userId}}`,
-      {
-        RETURN: ['q', 'text'],
-        LIMIT: {
-          from: 0,
-          size: 10000
-        }
-      }
-    );
-
-    const data: [string, string][] = [];
-
-    searchRes.documents.forEach((item: any) => {
-      if (item.value.q && item.value.text) {
-        data.push([item.value.q.replace(/\n/g, '\\n'), item.value.text.replace(/\n/g, '\\n')]);
-      }
+    // 统计数据
+    const count = await PgClient.count('modelData', {
+      where: [['model_id', modelId], 'AND', ['user_id', userId]]
     });
+    // 从 pg 中获取所有数据
+    const pgData = await PgClient.select<{ q: string; a: string }>('modelData', {
+      where: [['model_id', modelId], 'AND', ['user_id', userId]],
+      fields: ['q', 'a'],
+      order: [{ field: 'id', mode: 'DESC' }],
+      limit: count
+    });
+
+    const data: [string, string][] = pgData.rows.map((item) => [
+      item.q.replace(/\n/g, '\\n'),
+      item.a.replace(/\n/g, '\\n')
+    ]);
 
     jsonRes(res, {
       data
diff --git a/src/pages/api/model/data/getModelData.ts b/src/pages/api/model/data/getModelData.ts
index 38b400fa7..64a29916c 100644
--- a/src/pages/api/model/data/getModelData.ts
+++ b/src/pages/api/model/data/getModelData.ts
@@ -37,7 +37,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse<
     await connectToDatabase();
 
     const searchRes = await PgClient.select<PgModelDataItemType>('modelData', {
-      field: ['id', 'q', 'a', 'status'],
+      fields: ['id', 'q', 'a', 'status'],
       where: [['user_id', userId], 'AND', ['model_id', modelId]],
       order: [{ field: 'id', mode: 'DESC' }],
       limit: pageSize,
diff --git a/src/pages/api/model/data/pushModelDataCsv.ts b/src/pages/api/model/data/pushModelDataCsv.ts
index 425c3ba99..99920cd77 100644
--- a/src/pages/api/model/data/pushModelDataCsv.ts
+++ b/src/pages/api/model/data/pushModelDataCsv.ts
@@ -3,11 +3,8 @@ import { jsonRes } from '@/service/response';
 import { connectToDatabase, Model } from '@/service/mongo';
 import { authToken } from '@/service/utils/tools';
 import { generateVector } from '@/service/events/generateVector';
-import { connectRedis } from '@/service/redis';
-import { VecModelDataPrefix, ModelDataStatusEnum } from '@/constants/redis';
-import { VecModelDataIdx } from '@/constants/redis';
-import { customAlphabet } from 'nanoid';
-const nanoid = customAlphabet('abcdefghijklmnopqrstuvwxyz1234567890', 12);
+import { ModelDataStatusEnum } from '@/constants/model';
+import { PgClient } from '@/service/pg';
 
 export default async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
   try {
@@ -29,7 +26,6 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse<
     const userId = await authToken(authorization);
 
     await connectToDatabase();
-    const redis = await connectRedis();
 
     // 验证是否是该用户的 model
     const model = await Model.findOne({
@@ -47,10 +43,18 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse<
         try {
           q = q.replace(/\\n/g, '\n');
           a = a.replace(/\\n/g, '\n');
-          const redisSearch = await redis.ft.search(VecModelDataIdx, `@q:${q} @text:${a}`, {
-            RETURN: ['q', 'text']
+          const count = await PgClient.count('modelData', {
+            where: [
+              ['user_id', userId],
+              'AND',
+              ['model_id', modelId],
+              'AND',
+              ['q', q],
+              'AND',
+              ['a', a]
+            ]
           });
-          if (redisSearch.total > 0) {
+          if (count > 0) {
             return Promise.reject('已经存在');
           }
         } catch (error) {
@@ -62,35 +66,26 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse<
         });
       })
     );
-
+    // 过滤重复的内容
     const filterData = searchRes
       .filter((item) => item.status === 'fulfilled')
       .map<{ q: string; a: string }>((item: any) => item.value);
 
-    // 插入 redis
-    const insertRedisRes = await Promise.allSettled(
-      filterData.map((item) => {
-        return redis.sendCommand([
-          'HMSET',
-          `${VecModelDataPrefix}:${nanoid()}`,
-          'userId',
-          userId,
-          'modelId',
-          String(modelId),
-          'q',
-          item.q,
-          'text',
-          item.a,
-          'status',
-          ModelDataStatusEnum.waiting
-        ]);
-      })
-    );
+    // 插入 pg
+    const insertRes = await PgClient.insert('modelData', {
+      values: filterData.map((item) => [
+        { key: 'user_id', value: userId },
+        { key: 'model_id', value: modelId },
+        { key: 'q', value: item.q },
+        { key: 'a', value: item.a },
+        { key: 'status', value: ModelDataStatusEnum.waiting }
+      ])
+    });
 
     generateVector();
 
     jsonRes(res, {
-      data: insertRedisRes.filter((item) => item.status === 'fulfilled').length
+      data: insertRes.rowCount
     });
   } catch (err) {
     jsonRes(res, {
diff --git a/src/pages/api/model/data/putModelData.ts b/src/pages/api/model/data/putModelData.ts
index c146cd175..9e07e650e 100644
--- a/src/pages/api/model/data/putModelData.ts
+++ b/src/pages/api/model/data/putModelData.ts
@@ -1,13 +1,13 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { authToken } from '@/service/utils/tools';
-import { connectRedis } from '@/service/redis';
 import { ModelDataStatusEnum } from '@/constants/redis';
 import { generateVector } from '@/service/events/generateVector';
+import { PgClient } from '@/service/pg';
 
 export default async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
   try {
-    const { dataId, text, q } = req.body as { dataId: string; text: string; q?: string };
+    const { dataId, a, q } = req.body as { dataId: string; a: string; q?: string };
     const { authorization } = req.headers;
 
     if (!authorization) {
@@ -21,26 +21,21 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse<
     // 凭证校验
     const userId = await authToken(authorization);
 
-    const redis = await connectRedis();
+    // 更新 pg 内容
+    await PgClient.update('modelData', {
+      where: [['id', dataId], 'AND', ['user_id', userId]],
+      values: [
+        { key: 'a', value: a },
+        ...(q
+          ? [
+              { key: 'q', value: q },
+              { key: 'status', value: ModelDataStatusEnum.waiting }
+            ]
+          : [])
+      ]
+    });
 
-    // 校验是否为该用户的数据
-    const dataItemUserId = await redis.hGet(dataId, 'userId');
-    if (dataItemUserId !== userId) {
-      throw new Error('无权操作');
-    }
-
-    // 更新
-    await redis.sendCommand([
-      'HMSET',
-      dataId,
-      ...(q ? ['q', q, 'status', ModelDataStatusEnum.waiting] : []),
-      'text',
-      text
-    ]);
-
-    if (q) {
-      generateVector();
-    }
+    q && generateVector();
 
     jsonRes(res);
   } catch (err) {
diff --git a/src/pages/api/model/del.ts b/src/pages/api/model/del.ts
index be2780619..e82cade53 100644
--- a/src/pages/api/model/del.ts
+++ b/src/pages/api/model/del.ts
@@ -6,13 +6,12 @@ import { getUserApiOpenai } from '@/service/utils/openai';
 import { TrainingStatusEnum } from '@/constants/model';
 import { TrainingItemType } from '@/types/training';
 import { httpsAgent } from '@/service/utils/tools';
-import { connectRedis } from '@/service/redis';
-import { VecModelDataIdx } from '@/constants/redis';
+import { PgClient } from '@/service/pg';
 
 /* 获取我的模型 */
 export default async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
   try {
-    const { modelId } = req.query;
+    const { modelId } = req.query as { modelId: string };
     const { authorization } = req.headers;
 
     if (!authorization) {
@@ -37,21 +36,11 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse<
     }
 
     await connectToDatabase();
-    const redis = await connectRedis();
 
-    // 获取 redis 中模型关联的所有数据
-    const searchRes = await redis.ft.search(
-      VecModelDataIdx,
-      `@modelId:{${modelId}} @userId:{${userId}}`,
-      {
-        LIMIT: {
-          from: 0,
-          size: 10000
-        }
-      }
-    );
-    // 删除 redis 内容
-    await Promise.all(searchRes.documents.map((item) => redis.del(item.id)));
+    // 删除 pg 中所有该模型的数据
+    await PgClient.delete('modelData', {
+      where: [['user_id', userId], 'AND', ['model_id', modelId]]
+    });
 
     // 删除对应的聊天
     await Chat.deleteMany({
diff --git a/src/pages/api/openapi/chat/lafGpt.ts b/src/pages/api/openapi/chat/lafGpt.ts
index 2019fca06..76fafe353 100644
--- a/src/pages/api/openapi/chat/lafGpt.ts
+++ b/src/pages/api/openapi/chat/lafGpt.ts
@@ -7,12 +7,15 @@ import { ChatCompletionRequestMessage, ChatCompletionRequestMessageRoleEnum } fr
 import { ChatItemType } from '@/types/chat';
 import { jsonRes } from '@/service/response';
 import { PassThrough } from 'stream';
-import { ChatModelNameEnum, modelList, ChatModelNameMap } from '@/constants/model';
+import {
+  ChatModelNameEnum,
+  modelList,
+  ChatModelNameMap,
+  ModelVectorSearchModeMap
+} from '@/constants/model';
 import { pushChatBill } from '@/service/events/pushBill';
-import { connectRedis } from '@/service/redis';
-import { VecModelDataPrefix } from '@/constants/redis';
-import { vectorToBuffer } from '@/utils/tools';
 import { openaiCreateEmbedding, gpt35StreamResponse } from '@/service/utils/openai';
+import { PgClient } from '@/service/pg';
 
 /* 发送提示词 */
 export default async function handler(req: NextApiRequest, res: NextApiResponse) {
@@ -46,7 +49,6 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
     }
 
     await connectToDatabase();
-    const redis = await connectRedis();
     let startTime = Date.now();
 
     /* 凭证校验 */
@@ -144,39 +146,29 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
     // 读取对话内容
     const prompts = [prompt];
 
-    // 搜索系统提示词, 按相似度从 redis 中搜出相关的 q 和 text
-    const redisData: any[] = await redis.sendCommand([
-      'FT.SEARCH',
-      `idx:${VecModelDataPrefix}:hash`,
-      `@modelId:{${String(model._id)}}=>[KNN 20 @vector $blob AS score]`,
-      'RETURN',
-      '1',
-      'text',
-      'SORTBY',
-      'score',
-      'PARAMS',
-      '2',
-      'blob',
-      vectorToBuffer(promptVector),
-      'DIALECT',
-      '2'
-    ]);
+    // 相似度搜索
+    const similarity = ModelVectorSearchModeMap[model.search.mode]?.similarity || 0.22;
+    const vectorSearch = await PgClient.select<{ id: string; q: string; a: string }>('modelData', {
+      fields: ['id', 'q', 'a'],
+      order: [{ field: 'vector', mode: `<=> '[${promptVector}]'` }],
+      where: [
+        ['model_id', model._id],
+        'AND',
+        ['user_id', userId],
+        'AND',
+        `vector <=> '[${promptVector}]' < ${similarity}`
+      ],
+      limit: 30
+    });
 
-    // 格式化响应值，获取 qa
-    const formatRedisPrompt: string[] = [];
-    for (let i = 2; i < 42; i += 2) {
-      const text = redisData[i]?.[1];
-      if (text) {
-        formatRedisPrompt.push(text);
-      }
-    }
+    const formatRedisPrompt: string[] = vectorSearch.rows.map((item) => `${item.q}\n${item.a}`);
 
     // textArr 筛选，最多 3000 tokens
     const systemPrompt = systemPromptFilter(formatRedisPrompt, 3000);
 
     prompts.unshift({
       obj: 'SYSTEM',
-      value: `${model.systemPrompt} 知识库内容是最新的，知识库内容为: "${systemPrompt}"`
+      value: `${model.systemPrompt} 知识库是最新的,下面是知识库内容:${systemPrompt}`
     });
 
     // 控制在 tokens 数量，防止超出
diff --git a/src/pages/api/openapi/chat/vectorGpt.ts b/src/pages/api/openapi/chat/vectorGpt.ts
index 84749e3f5..6e740fb91 100644
--- a/src/pages/api/openapi/chat/vectorGpt.ts
+++ b/src/pages/api/openapi/chat/vectorGpt.ts
@@ -1,22 +1,15 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { connectToDatabase, Model } from '@/service/mongo';
-import {
-  httpsAgent,
-  openaiChatFilter,
-  systemPromptFilter,
-  authOpenApiKey
-} from '@/service/utils/tools';
+import { httpsAgent, systemPromptFilter, authOpenApiKey } from '@/service/utils/tools';
 import { ChatCompletionRequestMessage, ChatCompletionRequestMessageRoleEnum } from 'openai';
 import { ChatItemType } from '@/types/chat';
 import { jsonRes } from '@/service/response';
 import { PassThrough } from 'stream';
 import { modelList, ModelVectorSearchModeMap, ModelVectorSearchModeEnum } from '@/constants/model';
 import { pushChatBill } from '@/service/events/pushBill';
-import { connectRedis } from '@/service/redis';
-import { VecModelDataPrefix } from '@/constants/redis';
-import { vectorToBuffer } from '@/utils/tools';
 import { openaiCreateEmbedding, gpt35StreamResponse } from '@/service/utils/openai';
 import dayjs from 'dayjs';
+import { PgClient } from '@/service/pg';
 
 /* 发送提示词 */
 export default async function handler(req: NextApiRequest, res: NextApiResponse) {
@@ -56,7 +49,6 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
     }
 
     await connectToDatabase();
-    const redis = await connectRedis();
     let startTime = Date.now();
 
     /* 凭证校验 */
@@ -84,38 +76,22 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
       text: prompts[prompts.length - 1].value // 取最后一个
     });
 
-    // 搜索系统提示词, 按相似度从 redis 中搜出相关的 q 和 text
+    // 相似度搜素
     const similarity = ModelVectorSearchModeMap[model.search.mode]?.similarity || 0.22;
-    // 搜索系统提示词, 按相似度从 redis 中搜出相关的 q 和 text
-    const redisData: any[] = await redis.sendCommand([
-      'FT.SEARCH',
-      `idx:${VecModelDataPrefix}:hash`,
-      `@modelId:{${modelId}} @vector:[VECTOR_RANGE ${similarity} $blob]=>{$YIELD_DISTANCE_AS: score}`,
-      'RETURN',
-      '1',
-      'text',
-      'SORTBY',
-      'score',
-      'PARAMS',
-      '2',
-      'blob',
-      vectorToBuffer(promptVector),
-      'LIMIT',
-      '0',
-      '30',
-      'DIALECT',
-      '2'
-    ]);
+    const vectorSearch = await PgClient.select<{ id: string; q: string; a: string }>('modelData', {
+      fields: ['id', 'q', 'a'],
+      order: [{ field: 'vector', mode: `<=> '[${promptVector}]'` }],
+      where: [
+        ['model_id', model._id],
+        'AND',
+        ['user_id', userId],
+        'AND',
+        `vector <=> '[${promptVector}]' < ${similarity}`
+      ],
+      limit: 30
+    });
 
-    const formatRedisPrompt: string[] = [];
-
-    // 格式化响应值，获取 qa
-    for (let i = 2; i < 61; i += 2) {
-      const text = redisData[i]?.[1];
-      if (text) {
-        formatRedisPrompt.push(text);
-      }
-    }
+    const formatRedisPrompt: string[] = vectorSearch.rows.map((item) => `${item.q}\n${item.a}`);
 
     // system 合并
     if (prompts[0].obj === 'SYSTEM') {
@@ -145,9 +121,9 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
 
       prompts.unshift({
         obj: 'SYSTEM',
-        value: `${model.systemPrompt} 用知识库内容回答，知识库内容为: "当前时间:${dayjs().format(
+        value: `${model.systemPrompt} 知识库是最新的,下面是知识库内容:当前时间为${dayjs().format(
           'YYYY/MM/DD HH:mm:ss'
-        )} ${systemPrompt}"`
+        )}\n${systemPrompt}`
       });
     }
 
diff --git a/src/service/events/generateVector.ts b/src/service/events/generateVector.ts
index 76f462572..7d88d58bf 100644
--- a/src/service/events/generateVector.ts
+++ b/src/service/events/generateVector.ts
@@ -16,7 +16,7 @@ export async function generateVector(next = false): Promise<any> {
   try {
     // 从找出一个 status = waiting 的数据
     const searchRes = await PgClient.select('modelData', {
-      field: ['id', 'q', 'user_id'],
+      fields: ['id', 'q', 'user_id'],
       where: [['status', 'waiting']],
       limit: 1
     });
diff --git a/src/service/pg.ts b/src/service/pg.ts
index 53c51e937..342a09d3f 100644
--- a/src/service/pg.ts
+++ b/src/service/pg.ts
@@ -34,9 +34,9 @@ export const connectPg = async () => {
 
 type WhereProps = (string | [string, string | number])[];
 type GetProps = {
-  field?: string[];
+  fields?: string[];
   where?: WhereProps;
-  order?: { field: string; mode: 'DESC' | 'ASC' }[];
+  order?: { field: string; mode: 'DESC' | 'ASC' | string }[];
   limit?: number;
   offset?: number;
 };
@@ -62,7 +62,7 @@ class Pg {
             if (typeof item === 'string') {
               return item;
             }
-            const val = typeof item[1] === 'string' ? `'${item[1]}'` : item[1];
+            const val = typeof item[1] === 'number' ? item[1] : `'${String(item[1])}'`;
             return `${item[0]}=${val}`;
           })
           .join(' ')}`
@@ -95,7 +95,9 @@ class Pg {
       .join(',');
   }
   async select<T extends QueryResultRow = any>(table: string, props: GetProps) {
-    const sql = `SELECT ${!props.field || props.field?.length === 0 ? '*' : props.field?.join(',')}
+    const sql = `SELECT ${
+      !props.fields || props.fields?.length === 0 ? '*' : props.fields?.join(',')
+    }
       FROM ${table}
       ${this.getWhereStr(props.where)}
       ${
@@ -123,19 +125,34 @@ class Pg {
     return pg.query(sql);
   }
   async update(table: string, props: UpdateProps) {
+    if (props.values.length === 0) {
+      return {
+        rowCount: 0
+      };
+    }
+
     const sql = `UPDATE ${table} SET ${this.getUpdateValStr(props.values)} ${this.getWhereStr(
       props.where
     )}`;
-
     const pg = await connectPg();
     return pg.query(sql);
   }
   async insert(table: string, props: InsertProps) {
+    if (props.values.length === 0) {
+      return {
+        rowCount: 0
+      };
+    }
+
     const fields = props.values[0].map((item) => item.key).join(',');
     const sql = `INSERT INTO ${table} (${fields}) VALUES ${this.getInsertValStr(props.values)} `;
     const pg = await connectPg();
     return pg.query(sql);
   }
+  async query<T extends QueryResultRow = any>(sql: string) {
+    const pg = await connectPg();
+    return pg.query<T>(sql);
+  }
 }
 
 export const PgClient = new Pg();
diff --git a/src/service/utils/tools.ts b/src/service/utils/tools.ts
index 38da94be9..b2cab6f91 100644
--- a/src/service/utils/tools.ts
+++ b/src/service/utils/tools.ts
@@ -137,5 +137,5 @@ export const systemPromptFilter = (prompts: string[], maxTokens: number) => {
     }
   }
 
-  return splitText.slice(0, splitText.length - 1);
+  return splitText.slice(0, splitText.length - 1).replace(/\n+/g, '\n');
 };
diff --git a/src/utils/tools.ts b/src/utils/tools.ts
index 71632d233..64d935402 100644
--- a/src/utils/tools.ts
+++ b/src/utils/tools.ts
@@ -51,23 +51,3 @@ export const Obj2Query = (obj: Record<string, string | number>) => {
   }
   return queryParams.toString();
 };
-
-/**
- * 向量转成 float32 buffer 格式
- */
-export const vectorToBuffer = (vector: number[]) => {
-  const npVector = new Float32Array(vector);
-
-  const buffer = Buffer.from(npVector.buffer);
-
-  return buffer;
-};
-
-export const formatVector = (vector: number[]) => {
-  let formattedVector = vector.slice(0, 1536); // 截取前1536个元素
-  if (vector.length > 1536) {
-    formattedVector = formattedVector.concat(Array(1536 - formattedVector.length).fill(0)); // 在后面添加0
-  }
-
-  return formattedVector;
-};