mastra integration

examples/mastra.ts

@@ -0,0 +1,61 @@
+import { Agent } from '@mastra/core/agent';
+import { AgentRunServer, type AgentRequest } from '../src/server';
+import {
+  MastraConverter,
+  type AgentEventItem,
+  model,
+  toolset,
+} from '../src/integration/mastra';
+
+import { logger } from '../src/utils/log';
+
+const mastraAgent = new Agent({
+  id: 'run_agent',
+  name: 'AgentRun',
+  instructions: `
+你是一个智能助手，你会帮助用户完成各种任务。你的输出后，必须是返向输出的。
+
+如，用户输入 “你好”，应该输出 “？么的您助帮以可么什有，好您”
+  `.trim(),
+  model: () => model({ name: 'ohyee-test' }),
+  tools: () => toolset({ name: 'start-mcp-time-ggda' }),
+});
+
+async function* invokeAgent(
+  request: AgentRequest,
+): AsyncGenerator<AgentEventItem> {
+  const converter = new MastraConverter();
+  const mastraStream = await mastraAgent.stream(
+    request.messages.map(
+      (msg) =>
+        ({
+          role: msg.role,
+          content: msg.content || '',
+        }) as any,
+    ),
+  );
+  for await (const chunk of mastraStream.fullStream) {
+    const events = converter.convert(chunk);
+
+    for (const event of events) {
+      yield event;
+    }
+  }
+}
+
+const server = new AgentRunServer({
+  invokeAgent,
+  config: { corsOrigins: ['*'] },
+});
+
+logger.info(`
+curl http://127.0.0.1:9000/openai/v1/chat/completions -X POST \\
+  -H "Content-Type: application/json" \\
+  -d \'{"messages": [{"role": "user", "content": "Hello!"}], "stream": true}\'
+
+curl http://127.0.0.1:9000/ag-ui/agent -X POST \\
+  -H "Content-Type: application/json" \\
+  -d \'{"messages": [{"role": "user", "content": "Hello!"}]}\'
+  `);
+
+server.start({ port: 9000 });

examples/model.ts

@@ -13,10 +13,10 @@
  *   npm run example:model
  */
 
-import { ModelClient, ResourceAlreadyExistError, ResourceNotExistError, Status, BackendType, ModelType, ModelService, ModelProxy } from '../src/index';
-import type { ModelServiceCreateInput, ModelServiceUpdateInput, ModelProxyCreateInput, ModelProxyUpdateInput, ProviderSettings, ProxyConfig } from '../src/index';
-import { logger } from '../src/utils/log';
+import type { ModelProxyCreateInput, ModelServiceCreateInput, ProviderSettings, ProxyConfig } from '../src/index';
+import { ModelClient, ModelProxy, ModelService, ModelType, ResourceAlreadyExistError, ResourceNotExistError, Status } from '../src/index';
 import { Config } from '../src/utils/config';
+import { logger } from '../src/utils/log';
 
 // Logger helper
 function log(message: string, ...args: unknown[]) {
@@ -68,7 +68,7 @@ async function createOrGetModelService(): Promise<ModelService> {
 
   // 等待就绪 / Wait for ready
   await ms.waitUntilReadyOrFailed({
-    beforeCheck: (service: ModelService) =>
+    callback: (service) =>
       log(`  当前状态 / Current status: ${service.status}`),
   });
 
@@ -112,7 +112,11 @@ async function updateModelService(ms: ModelService): Promise<void> {
 async function listModelServices(): Promise<void> {
   log('枚举资源列表 / Listing resources');
 
-  const services = await ModelService.list({ modelType: ModelType.LLM });
+  const services = await ModelService.list({
+    input: {
+      modelType: ModelType.LLM
+    }
+  });
   log(
     `共有 ${services.length} 个资源，分别为 / Total ${services.length} resources:`,
     services.map((s) => s.modelServiceName)
@@ -131,8 +135,10 @@ async function invokeModelService(ms: ModelService): Promise<void> {
   });
 
   // 流式输出 / Stream output
-  for await (const chunk of result.textStream) {
-    process.stdout.write(chunk);
+  if ('textStream' in result && result.textStream) {
+    for await (const chunk of result.textStream) {
+      process.stdout.write(chunk);
+    }
   }
   logger.info(''); // 换行
 }
@@ -198,7 +204,7 @@ async function createOrGetModelProxy(): Promise<ModelProxy> {
 
   // 等待就绪 / Wait for ready
   await mp.waitUntilReadyOrFailed({
-    beforeCheck: (proxy: ModelProxy) =>
+    callback: (proxy) =>
       log(`  当前状态 / Current status: ${proxy.status}`),
   });
 
@@ -257,14 +263,16 @@ async function listModelProxies(): Promise<void> {
 async function invokeModelProxy(mp: ModelProxy): Promise<void> {
   log('调用模型代理进行推理 / Invoking model proxy for inference');
 
-  const result = await mp.completions({
+  const result = await mp.completion({
     messages: [{ role: 'user', content: '你好,请介绍一下你自己' }],
     stream: true,
   });
 
   // 流式输出 / Stream output
-  for await (const chunk of result.textStream) {
-    process.stdout.write(chunk);
+  if ('textStream' in result && result.textStream) {
+    for await (const chunk of result.textStream) {
+      process.stdout.write(chunk);
+    }
   }
   logger.info(''); // 换行
 }