diff --git a/package.json b/package.json
index 2a4ba85..5335ecd 100644
--- a/package.json
+++ b/package.json
@@ -1,6 +1,6 @@
 {
   "name": "@kevisual/ai",
-  "version": "0.0.18",
+  "version": "0.0.19",
   "description": "AI Center Services",
   "main": "index.js",
   "basename": "/root/ai-center-services",
diff --git a/src/test/aliyun/test.ts b/src/test/aliyun/test.ts
deleted file mode 100644
index e984cc0..0000000
--- a/src/test/aliyun/test.ts
+++ /dev/null
@@ -1,59 +0,0 @@
-import { BailianProvider } from '../../provider/index.ts'
-import dotenv from 'dotenv';
-
-dotenv.config();
-import { App } from '@kevisual/router'
-import util from 'node:util';
-const ai = new BailianProvider({
-  apiKey: process.env.BAILIAN_API_KEY || '',
-  model: 'qwen-turbo-latest',
-  baseURL: 'https://dashscope.aliyuncs.com/compatible-mode/v1'
-})
-
-
-// const res = await ai.chat([
-
-//   {
-//     role: 'user',
-//     content: `1+1等于多少？`
-//   },
-
-// ],
-// )
-// // console.log('AI Response:', res);
-// const content = res.choices[0].message?.content || ''
-
-// console.log(util.inspect(res, { depth: null }))
-
-// console.log('responseText', ai.responseText)
-
-
-// const res = await ai.chatStream([
-
-//   {
-//     role: 'user',
-//     content: `1+1等于多少？`
-//   },
-
-// ],
-// )
-// // console.log('AI Response:', res);
-// export const readStream = async (chatStream) => {
-//   let buffer = '';
-//   for await (const chunk of chatStream) {
-//     // chunk 已经是解码后的字符串，直接拼接即可
-//     buffer += chunk;
-//   }
-//   console.log('AI Response:', buffer);
-// };
-
-// await readStream(res);
-
-const embe = await ai.generateEmbeddingCore([
-  '你好，世界！',
-  'Hello, world!',
-], {
-  model: 'text-embedding-v4'
-});
-
-console.log('Embedding Response:', util.inspect(embe, { depth: null }));
\ No newline at end of file
diff --git a/src/test/chunks/01-get.ts b/src/test/chunks/01-get.ts
deleted file mode 100644
index 65e0128..0000000
--- a/src/test/chunks/01-get.ts
+++ /dev/null
@@ -1,65 +0,0 @@
-import { getChunks } from '../../provider/utils/chunk.ts';
-
-const str = 'Hello world this is a test 你好沙盒 very big';
-
-
-const str2 = `不能直接使用 tiktoken（OpenAI的分词器）来计算 Qwen 模型的 Token 数量，因为两者的分词规则（Tokenization）和词表（Vocabulary）完全不同。
-
-为什么不能混用？
-词表不同
-
-tiktoken 是 OpenAI 为 GPT 系列设计的（如 gpt-3.5-turbo, gpt-4），其词表针对英语和代码优化。
-
-Qwen 使用独立训练的 BPE 词表，对中文、多语言的支持更友好，分词粒度可能不同。
-
-分词结果差异大
-同一段文本，tiktoken 和 Qwen 的分词结果可能完全不同。例如：
-
-OpenAI (tiktoken): "你好" → ['你', '好']（2 Tokens）
-
-Qwen: "你好" → ['你好']（1 Token，如果词表中包含该组合）
-
-性能问题
-即使强制使用 tiktoken 计算 Qwen 的 Token，结果也不准确，可能导致：
-
-输入超出模型上下文限制（因统计偏差）。
-
-API 计费或本地推理时出现意外错误。
-
-正确方法：用 Qwen 的分词器
-通过 Hugging Face transformers 加载 Qwen 的原生分词器：
-
-python
-复制
-from transformers import AutoTokenizer
-
-# 加载 Qwen 的分词器（以 Qwen-7B 为例）
-tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen-7B", trust_remote_code=True)
-
-text = "你好，Qwen模型！"
-tokens = tokenizer.tokenize(text)  # 查看分词结果
-token_count = len(tokenizer.encode(text, add_special_tokens=False))
-
-print("分词结果:", tokens)
-print("Token数量:", token_count)
-常见问题
-为什么需要 trust_remote_code=True？
-Qwen 的分词器是自定义实现的（非 Hugging Face 原生），此参数允许从模型仓库加载运行代码。
-
-其他语言的 Token 计算？
-Qwen 对非英语（如中文、日文）的分词效率较高，但仍需用其原生分词器统计。
-
-与 tiktoken 的速度对比？
-tiktoken 是纯 Python 实现，速度较快；Qwen 的分词器基于 Hugging Face，可能稍慢但对齐模型需求。
-
-总结
-禁止混用：tiktoken ≠ Qwen 分词器。
-
-始终使用模型配套工具：Qwen 需通过 transformers 加载其官方分词器。
-
-中文场景特别注意：Qwen 对中文的分词更高效，直接使用可避免偏差。
-
-如果需要验证分词规则，可通过 tokenizer.vocab 查看词表内容（但注意词表通常较大）。`
-
-const chunks = getChunks(str2);
-console.log(chunks);
diff --git a/src/test/common.ts b/src/test/common.ts
deleted file mode 100644
index 09d8db5..0000000
--- a/src/test/common.ts
+++ /dev/null
@@ -1,18 +0,0 @@
-import { Jimen } from "../jimeng/index.ts"
-import dotenv from 'dotenv';
-dotenv.config();
-
-const jimeng = new Jimen({
-  token: process.env.JIMENG_TOKEN,
-})
-
-console.log("Generating image...");
-
-await jimeng.generateImage({
-  prompt: "创建一幅未来城市的数字艺术作品，充满科技感和创新元素，色彩鲜艳，细节丰富",
-  resolution: "2k"
-}).then((res) => {
-  console.log("Image generation response:", res);
-}).catch((err) => {
-  console.error("Error generating image:", err);
-});
\ No newline at end of file
diff --git a/src/test/encrypt/index.ts b/src/test/encrypt/index.ts
deleted file mode 100644
index 99b3f84..0000000
--- a/src/test/encrypt/index.ts
+++ /dev/null
@@ -1,9 +0,0 @@
-import { encryptAES, decryptAES } from '../..//provider/utils/parse-config.ts';
-
-const plainx = process.env.API_KEY;
-const decryptKey = process.env.DECRYPT_KEY;
-const encrypt = encryptAES(plainx, decryptKey);
-console.log('encrypt', encrypt);
-
-const decrypt = decryptAES(encrypt, decryptKey);
-console.log(decrypt);
diff --git a/src/test/func-call/curl.sh b/src/test/func-call/curl.sh
deleted file mode 100644
index f9f00ae..0000000
--- a/src/test/func-call/curl.sh
+++ /dev/null
@@ -1,35 +0,0 @@
-curl --request POST \
-  --url https://api.siliconflow.cn/v1/chat/completions \
-  --header 'Authorization: Bearer sk-qbiigkzoaamuqxtwlgkugodncebkfbosemadfubjrseobpvx' \
-  --header 'Content-Type: application/json' \
-  --data '{
-  "model": "Qwen/Qwen3-14B",
-  "messages": [
-    {
-      "role": "user",
-      "content": "计算a+b的值"
-    }
-  ],
-  "stream": false,
-  "max_tokens": 512,
-  "stop": null,
-  "temperature": 0.7,
-  "top_p": 0.7,
-  "top_k": 50,
-  "frequency_penalty": 0.5,
-  "n": 1,
-  "response_format": {
-    "type": "text"
-  },
-  "tools": [
-    {
-      "type": "function",
-      "function": {
-        "description": "计算a，b，c算法的值，a=1，b=2，c=3",
-        "name": "compouted",
-        "parameters": {},
-        "strict": false
-      }
-    }
-  ]
-}'
\ No newline at end of file
diff --git a/src/test/func-call/demo.ts b/src/test/func-call/demo.ts
deleted file mode 100644
index 6b91d7f..0000000
--- a/src/test/func-call/demo.ts
+++ /dev/null
@@ -1,116 +0,0 @@
-import { SiliconFlow } from '../../provider/chat-adapter/siliconflow.ts';
-import { Ollama } from '../../provider/chat-adapter/ollama.ts';
-import dotenv from 'dotenv';
-
-dotenv.config();
-const siliconflow = new SiliconFlow({
-  apiKey: process.env.SILICONFLOW_API_KEY,
-  model: 'Qwen/Qwen3-14B',
-});
-const ollama = new Ollama({
-  model: 'qwen3:32b',
-  apiKey: process.env.OLLAMA_API_KEY,
-  baseURL: process.env.OLLAMA_BASE_URL,
-});
-const main = async () => {
-  const usage = await siliconflow.getUsageInfo();
-  console.log(usage);
-};
-// 1. 定义工具函数
-const availableFunctions: Record<string, (args: any) => Promise<any>> = {
-  get_time: async (args: { location: string }) => {
-    // 模拟API调用
-    console.log('time', args);
-    return {
-      time: '2022-03-22 12:00:00',
-    };
-  },
-  get_location: async (args: { symbol: string }) => {
-    // 模拟API调用
-    console.log('location', args);
-    return {
-      city: 'Beijing',
-    };
-  },
-};
-
-// main();
-const funcCall = async (model = siliconflow) => {
-  const tools = [
-    {
-      type: 'function',
-      function: {
-        name: 'get_time',
-        description: '获取当前时间',
-        parameters: {
-          type: 'object',
-          properties: {
-            place: {
-              type: 'string',
-              description: '位置',
-            },
-          },
-          required: ['place'],
-        },
-      },
-    },
-    {
-      type: 'function',
-      function: {
-        name: 'get_location',
-        description: '获取当前位置',
-        // parameters: {},
-        parameters: {},
-        strict: false,
-      },
-    },
-  ];
-  const messages: any[] = [{ role: 'user', content: '获取当前位置的当前时间' }];
-  const res = await model.chat(messages, {
-    tools: tools as any,
-  });
-  console.log(res.choices[0]);
-  const assistantMessage = res.choices[0].message;
-  const finish_reason = res.choices[0].finish_reason;
-  messages.push(assistantMessage);
-  let toolCalls = assistantMessage.tool_calls;
-  console.log("toolCalls", JSON.stringify(toolCalls));
-  let maxRetries = 3;
-  while (toolCalls && toolCalls.length > 0) {
-    // 处理每个函数调用
-    for (const toolCall of toolCalls) {
-      const functionName = toolCall.function.name;
-      const functionArgs = JSON.parse(toolCall.function.arguments);
-      // 调用本地函数
-      const functionResponse = await availableFunctions[functionName](functionArgs);
-      // 将结果添加到消息历史
-      messages.push({
-        role: 'tool',
-        name: functionName,
-        content: JSON.stringify(functionResponse),
-        tool_call_id: toolCall.id,
-      });
-    }
-
-    // 第二次调用 - 将函数结果发送给模型获取最终回复
-    const secondResponse = await model.chat(messages, {
-      tools: tools as any,
-    });
-
-    const finalMessage = secondResponse.choices[0].message;
-    messages.push(finalMessage);
-    const _toolCalls = finalMessage.tool_calls;
-    console.log("toolCalls", JSON.stringify(toolCalls) ,finalMessage.role);
-    toolCalls = _toolCalls ? _toolCalls : [];
-    maxRetries--;
-    if (maxRetries <= 0) {
-      break;
-    }
-    
-    console.log('tool calls', toolCalls);
-  }
-
-  console.log(messages);
-};
-
-funcCall(ollama as any);
diff --git a/src/test/model-scope/index.ts b/src/test/model-scope/index.ts
deleted file mode 100644
index 7f28630..0000000
--- a/src/test/model-scope/index.ts
+++ /dev/null
@@ -1,26 +0,0 @@
-import { ModelScope } from '../../provider/chat-adapter/model-scope.ts';
-import { logger } from '../../modules/logger.ts';
-import util from 'util';
-import { config } from 'dotenv';
-config();
-
-const chat = new ModelScope({
-  apiKey: process.env.MODEL_SCOPE_API_KEY,
-  model: 'Qwen/Qwen2.5-Coder-32B-Instruct',
-});
-
-// chat.chat([{ role: 'user', content: 'Hello, world! 1 + 1 equals ?' }]);
-const chatMessage = [{ role: 'user', content: 'Hello, world! 1 + 1 equals ?' }];
-
-const main = async () => {
-  const res = await chat.test();
-  logger.info('test', res);
-};
-
-main();
-const mainChat = async () => {
-  const res = await chat.chat(chatMessage as any);
-  logger.info('chat', res);
-};
-
-// mainChat();
diff --git a/src/test/ollama-knowledge.ts b/src/test/ollama-knowledge.ts
deleted file mode 100644
index de514ed..0000000
--- a/src/test/ollama-knowledge.ts
+++ /dev/null
@@ -1,37 +0,0 @@
-import { Knowledge } from '../../../../src/provider/knowledge/knowledge.ts';
-import fs from 'fs';
-import dotenv from 'dotenv';
-
-dotenv.config();
-const knowledge = new Knowledge({
-  embeddingModel: 'bge-m3:latest',
-  baseURL: 'https://ollama.xiongxiao.me/v1',
-  model: 'qwq:latest',
-  apiKey: process.env.OLLAMA_API_KEY,
-});
-
-const main = async () => {
-  const res = await knowledge.generateEmbeddingCore('Hello world this is a test 你好沙盒 very big');
-  fs.writeFileSync('docs/embedding.json', JSON.stringify(res, null, 2));
-  console.log(res);
-};
-
-main();
-
-const main2 = async () => {
-  const text1 = 'Hello, world! this is a test';
-  const text2 = 'Hello, world! this is a test 2';
-  const text3 = 'Hello, world! this is a test 3';
-  const text4 = 'Hello, world! this is a test 4';
-  const text5 = 'Hello, world! this is a test 5';
-  const text6 = 'Hello, world! this is a test 6';
-  const text7 = 'Hello, world! this is a test 7';
-  const text8 = 'Hello, world! this is a test 8';
-  const text9 = 'Hello, world! this is a test 9';
-  const text10 = 'Hello, world! this is a test 10';
-  const res = await knowledge.generateEmbeddingCore([text1, text2, text3, text4, text5, text6, text7, text8, text9, text10]);
-  fs.writeFileSync('docs/embedding2.json', JSON.stringify(res, null, 2));
-  console.log(res);
-};
-
-// main2();
diff --git a/src/test/ollama.ts b/src/test/ollama.ts
deleted file mode 100644
index c71658d..0000000
--- a/src/test/ollama.ts
+++ /dev/null
@@ -1,86 +0,0 @@
-import { Ollama } from '../../../../src/provider/chat-adapter/ollama.ts';
-import util from 'util';
-const chat = new Ollama({
-  baseURL: 'https://ollama.xiongxiao.me/v1',
-  apiKey: 'xiongxiao2233',
-  model: 'qwq:latest',
-});
-
-// chat.chat([{ role: 'user', content: 'Hello, world!' }]);
-
-const main = async () => {
-  const res = await chat.test();
-  console.log(util.inspect(res, { depth: null, colors: true }));
-};
-
-// main();
-
-const getJson = async () => {
-  const res = await chat.chat(
-    [
-      { role: 'system', content: '把发送的数据，返回给我对应的json，只处理完发送的数据。如果发送了多个，给我一个数组' },
-      // { role: 'user', content: '{"name":"John","age":30}' },
-      { role: 'user', content: 'name: 张三' },
-      { role: 'user', content: 'name: 李四, age: 18' },
-    ],
-    {
-      response_format: {
-        type: 'json_schema',
-        json_schema: {
-          name: 'user',
-          description: '用户信息',
-          schema: {
-            type: 'object',
-            // properties: {
-            //   name: { type: 'string' },
-            //   // age: { type: 'number' },
-            // },
-            // // required: ['name', 'age'],
-            // required: ['name'],
-            properties: {
-              name: { type: 'string' },
-              age: { type: 'number' },
-            },
-            required: ['name', 'age'],
-          },
-        },
-      },
-      n: 10,
-    },
-  );
-  console.log(util.inspect(res, { depth: null, colors: true }));
-};
-
-// getJson();
-
-const createChat1 = async () => {
-  const res = await chat.chat(
-    [
-      { role: 'user', content: 'a=1, b=2, c=3' },
-      { role: 'user', content: 'a+b+c=?' },
-      { role: 'assistant', content: '给定的值为 \\( a = 1 \\), \\( b = 2 \\), \\( c = 3 \\)。\n' + '\n' + '因此，\\( a + b + c = 1 + 2 + 3 = 6 \\)。' },
-      { role: 'user', content: 'a+b+c+4=?' },
-    ],
-    {
-      model: 'qwen2.5:7b',
-    },
-  );
-  console.log(util.inspect(res, { depth: null, colors: true }));
-};
-
-//  createChat1();
-
-const getTags = async () => {
-  const res = await chat.listModels();
-  console.log(util.inspect(res, { depth: null, colors: true }));
-};
-
-// getTags();
-
-const getRunModels = async () => {
-  const res = await chat.listRunModels();
-  console.log('current', new Date().toISOString());
-  console.log(util.inspect(res, { depth: null, colors: true }));
-};
-
-// getRunModels();
diff --git a/src/test/provider/index.ts b/src/test/provider/index.ts
deleted file mode 100644
index e099a87..0000000
--- a/src/test/provider/index.ts
+++ /dev/null
@@ -1,7 +0,0 @@
-import { ProviderManager } from '../..//provider/index.ts';
-import { config } from 'dotenv';
-config();
-const providerConfig = { provider: 'ModelScope', model: 'Qwen/Qwen2.5-Coder-32B-Instruct', apiKey: process.env.MODEL_SCOPE_API_KEY };
-const provider = await ProviderManager.createProvider(providerConfig);
-const result = await provider.chat([{ role: 'user', content: '你好' }]);
-console.log(result);
diff --git a/src/utils/json.ts b/src/utils/json.ts
deleted file mode 100644
index 560e572..0000000
--- a/src/utils/json.ts
+++ /dev/null
@@ -1,12 +0,0 @@
-/**
- * 尝试从字符串中提取JSON对象
- */
-export const getJsonFromString = (str: string) => {
-  try {
-    const jsonMatch = str.match(/```json\s*([\s\S]*?)\s*```/);
-    if (jsonMatch && jsonMatch[1]) {
-      return JSON.parse(jsonMatch[1]);
-    }
-  } catch (error) {}
-  return null;
-};