feat: 更新依赖项，重构 fetch 逻辑，添加工具路由和代理功能

src/common.ts

@@ -2,6 +2,24 @@ import { createOpenAICompatible } from '@ai-sdk/openai-compatible';
 import { createAnthropic } from '@ai-sdk/anthropic';
 import { generateText } from 'ai';
 import 'dotenv/config';
+import util from 'node:util';
+// 保存原始 fetch 引用
+const originalFetch = fetch;
+
+export const defaultFetch = {
+  fetch: async (input: string | URL | Request, init?: BunFetchRequestInit) => {
+    console.log('请求 URL:', input);
+    console.log('请求选项:', init);
+
+    const response = await originalFetch(input, init);  // 调用原始 fetch
+
+    console.log('响应状态:', response.status);
+    const responseBody = await response.clone().text();  // 使用 clone 避免消耗原始 response
+    console.log('响应体:', responseBody);
+
+    return response;
+  }
+}
 
 export function resolveEnvVars(value: string): string {
   return value.replace(/{env:([^}]+)}/g, (_, varName) => {
@@ -19,6 +37,8 @@ export const models = {
   'MiniMax-M2.1': 'MiniMax-M2.1',
   'qwen3-coder-plus': 'qwen3-coder-plus',
   'hunyuan-a13b': 'hunyuan-a13b',
+  'qwen-plus': 'qwen-plus',
+  'auto': 'AUTO_Models',
 }
 export const bailian = createOpenAICompatible({
   baseURL: 'https://coding.dashscope.aliyuncs.com/v1',
@@ -36,6 +56,7 @@ export const minimax = createAnthropic({
   baseURL: 'https://api.minimaxi.com/anthropic/v1',
   name: 'custom-minimax',
   apiKey: process.env.MINIMAX_API_KEY!,
+  fetch: defaultFetch.fetch as any
 });
 
 export const doubao = createOpenAICompatible({
@@ -44,8 +65,20 @@ export const doubao = createOpenAICompatible({
   apiKey: process.env.DOUBAO_API_KEY!,
 });
 
+
 export const cnb = createOpenAICompatible({
-  baseURL: resolveEnvVars('https://api.cnb.cool/{env:CNB_REPO_SLUG}/-/ai/'),
+  baseURL: 'https://api.cnb.cool/kevisual/kevisual/-/ai/',
+  // baseURL: resolveEnvVars('https://api.cnb.cool/{env:CNB_REPO_SLUG}/-/ai/'),
   name: 'custom-cnb',
   apiKey: process.env.CNB_API_KEY!,
+  fetch: defaultFetch.fetch as any
 });
+export const proxyCnb = createOpenAICompatible({
+  baseURL: 'http://localhost:4005/api',
+  name: 'proxy-cnb',
+  apiKey: process.env.CNB_API_KEY!,
+});
+
+export const showMore = (obj: any) => {
+  return util.inspect(obj, { depth: null, colors: true });
+}

src/routes/ai.ts

@@ -0,0 +1,83 @@
+import { generateText, tool, type ModelMessage, type ToolApprovalResponse } from 'ai';
+import { z } from 'zod';
+import { cnb, proxyCnb, models, showMore } from '../common.ts';
+
+import { app } from './app.ts';
+import type { App } from '@kevisual/router';
+
+const createTool = async (app: App, message: { path: string, key: string }) => {
+  const route = app.findRoute({ path: message.path, key: message.key });
+  if (!route) {
+    console.error(`未找到路径 ${message.path} 和 key ${message.key} 的路由`);
+    return null;
+  }
+  const _tool = tool({
+    description: route.description || '无描述',
+    inputSchema: z.object({
+      ...route.metadata?.args
+    }), // 这里可以根据实际需要定义输入参数的 schema
+    execute: async (args: any) => {
+      console.log(`执行工具 ${message.path} ${message.key}，输入参数:`, args);
+      // 这里可以根据实际需要调用对应的路由处理函数
+      const res = await app.run({ path: message.path, key: message.key, payload: args });
+      // 假设路由处理函数返回一个字符串结果
+      console.log(`工具 ${message.path} ${message.key} 执行结果:`, res);
+      // return '任务列表:' + JSON.stringify(res);
+      return res;
+    }
+  });
+  return _tool;
+}
+
+const createTools = async (app: App) => {
+  const tools: Record<string, any> = {};
+  for (const route of app.routes) {
+    const id = route.id!;
+    const _tool = await createTool(app, { path: route.path!, key: route.key! });
+    if (_tool && id) {
+      tools[id] = _tool;
+    }
+  }
+  return tools;
+}
+
+const tools = await createTools(app);
+
+let messages: ModelMessage[] = [
+  {
+    role: 'user',
+    content: '任务步骤:第一步获取今天的任务列表,第二步完成id为1的任务。'
+  }
+]
+let result = await generateText({
+  model: proxyCnb(models['auto']),
+  tools,
+  messages
+  // prompt: '今天的任务是什么? 如果有id为1的任务,请完成他。'
+  // prompt: '完成今天的任务1。'
+});
+console.log('生成结果:', result.text);
+console.log('=== 生成内容详情 ===');
+console.log(showMore(result));
+
+messages.push(...result.response.messages);
+
+const result2 = await generateText({
+  model: cnb(models['auto']),
+  tools,
+  messages
+});
+console.log('生成结果2:', result2.text);
+console.log('=== 生成内容详情 ===');
+console.log(showMore(result2));
+
+messages.push(...result2.response.messages);
+
+const result3 = await generateText({
+  model: cnb(models['auto']),
+  tools,
+  messages
+});
+console.log('生成结果3:', result3.text);
+console.log('=== 生成内容详情 ===');
+console.log(showMore(result3));

src/routes/ai2.ts

@@ -0,0 +1,20 @@
+import { app } from './app.ts';
+import { cnb, proxyCnb, models, showMore } from '../common.ts';
+import { runAgent } from './lib.ts';
+
+const result = await runAgent({
+  app,
+  query:"WHERE path='task' AND key='today'",
+  languageModel: proxyCnb(models['auto']),
+  messages: [
+    {
+      role: 'user',
+      content: '任务步骤:第一步获取今天的任务列表,第二步完成id为1的任务。'
+    }
+  ]
+})
+
+console.log('最终结果:', result.text);
+
+console.log('=== 生成内容详情 ===');
+console.log(showMore(result.steps));

src/routes/app.ts

@@ -0,0 +1,67 @@
+import { App } from '@kevisual/router'
+import z from 'zod';
+
+export const app = new App();
+
+const tasks = [
+  {
+    id: 1,
+    title: 'Task 1',
+    description: 'This is the first task.',
+    completed: false,
+  },
+  {
+    id: 2,
+    title: 'Task 2',
+    description: 'This is the second task.',
+    completed: true,
+  },
+]
+app.route({
+  path: 'task',
+  key: 'today',
+  description: '获取今日待办任务列表',
+}).define(async (ctx) => {
+
+  const list = tasks.map(task => ({
+    id: task.id,
+    title: task.title,
+    description: task.description,
+    completed: task.completed,
+  }))
+  ctx.body = { list }
+}).addTo(app)
+
+app.route({
+  path: 'task',
+  key: 'done',
+  description: '完成任务',
+  metadata: {
+    args: {
+      id: z.number().describe('任务ID'),
+    }
+  }
+}).define(async (ctx) => {
+  const { id } = ctx.args as { id: number };
+  const task = tasks.find(t => t.id === id);
+  if (task) {
+    task.completed = true;
+    ctx.body = { message: `任务 ${id} 已完成` };
+  } else {
+    ctx.body = { message: `未找到任务 ${id}` };
+  }
+}).addTo(app)
+
+app.route({
+  path: 'task',
+  key: 'list',
+  description: '获取所有任务列表',
+}).define(async (ctx) => {
+  const list = tasks.map(task => ({
+    id: task.id,
+    title: task.title,
+    description: task.description,
+    completed: task.completed,
+  }))
+  ctx.body = { list }
+}).addTo(app)

src/routes/lib.ts

@@ -0,0 +1,66 @@
+import { App, type RouteInfo } from '@kevisual/router'
+import { generateText, tool, type ModelMessage, type LanguageModel, type GenerateTextResult } from 'ai';
+import z from 'zod';
+import { filter } from '@kevisual/js-filter'
+const createTool = async (app: App, message: { path: string, key: string }) => {
+  const route = app.findRoute({ path: message.path, key: message.key });
+  if (!route) {
+    console.error(`未找到路径 ${message.path} 和 key ${message.key} 的路由`);
+    return null;
+  }
+  const _tool = tool({
+    description: route.description || '无描述',
+    inputSchema: z.object({
+      ...route.metadata?.args
+    }), // 这里可以根据实际需要定义输入参数的 schema
+    execute: async (args: any) => {
+      console.log(`执行工具 ${message.path} ${message.key}，输入参数:`, args);
+      // 这里可以根据实际需要调用对应的路由处理函数
+      const res = await app.run({ path: message.path, key: message.key, payload: args });
+      // 假设路由处理函数返回一个字符串结果
+      console.log(`工具 ${message.path} ${message.key} 执行结果:`, res);
+      // return '任务列表:' + JSON.stringify(res);
+      return res;
+    }
+  });
+  return _tool;
+}
+
+const createTools = async (app: App) => {
+  const tools: Record<string, any> = {};
+  for (const route of app.routes) {
+    const id = route.id!;
+    const _tool = await createTool(app, { path: route.path!, key: route.key! });
+    if (_tool && id) {
+      tools[id] = _tool;
+    }
+  }
+  return tools;
+}
+type Route = Partial<RouteInfo>
+
+export const reCallAgent = async (opts: { messages?: ModelMessage[], tools?: Record<string, any>, languageModel: LanguageModel }): Promise<GenerateTextResult<Record<string, any>, any>> => {
+  const { messages = [], tools = {}, languageModel } = opts;
+  const result = await generateText({
+    model: languageModel,
+    messages,
+    tools,
+  });
+  const step = result.steps[0]!;
+  if (step.finishReason === 'tool-calls') {
+    messages.push(...result.response.messages);
+    return reCallAgent({ messages, tools, languageModel });
+  }
+  return result
+}
+export const runAgent = async (opts: { app: App, messages?: ModelMessage[], routes?: Route[], query?: string, languageModel: LanguageModel }) => {
+  const { app, languageModel } = opts;
+  let messages = opts.messages || [];
+
+  let routes = app.routes;
+  if (opts.query) {
+    routes = filter(routes, opts.query);
+  };
+  const tools = await createTools(app);
+  return await reCallAgent({ messages, tools, languageModel });
+}

src/test-cnb.ts

@@ -17,7 +17,7 @@ function resolveEnvVars(value: string): string {
 const cnb = createOpenAICompatible({
   baseURL: resolveEnvVars('{env:CNB_API_ENDPOINT}/{env:CNB_REPO_SLUG}/-/ai/'),
   name: 'custom-cnb',
-  apiKey: process.env.CNB_API_KEY!,
+  // apiKey: process.env.CNB_API_KEY!,
 });
 
 const { text } = await generateText({

src/test-minimax.ts

@@ -0,0 +1,9 @@
+import { minimax } from "./common"
+import { generateText } from 'ai';
+
+const { text } = await generateText({
+  model: minimax('MiniMax-M2.1'),
+  prompt: 'What is an agent?',
+});
+
+console.log('Response:', text);