Twilio 上的实时智能体

Twilio 提供了一个 Media Streams API，可将电话通话中的原始音频发送到 WebSocket 服务器。此配置可用于将你的语音智能体连接到 Twilio。你可以在 websocket 模式下使用默认的 Realtime Session transport，将来自 Twilio 的事件连接到你的 Realtime Session。不过，这要求你设置正确的音频格式，并自行调整打断时机，因为电话通话天然会比基于 Web 的对话引入更高延迟。

为改进配置体验，我们创建了一个专用传输层来处理与 Twilio 的连接，包括打断处理和音频转发。

设置

请确保你拥有 Twilio 账号和 Twilio 电话号码。
设置一个可接收 Twilio 事件的 WebSocket 服务器。

如果你在本地开发，需要配置本地隧道（例如 ngrok 或 Cloudflare Tunnel）以便 Twilio 可以访问你的本地服务器。你可以使用 TwilioRealtimeTransportLayer 来连接 Twilio。
通过安装 extensions 包来安装 Twilio 适配器：
Terminal window
```
npm install @openai/agents-extensions
```

导入适配器和模型，并连接到你的 RealtimeSession：

import { TwilioRealtimeTransportLayer } from '@openai/agents-extensions';
import { RealtimeAgent, RealtimeSession } from '@openai/agents/realtime';

const agent = new RealtimeAgent({
  name: 'My Agent',
});

// Create a new transport mechanism that will bridge the connection between Twilio and
// the OpenAI Realtime API.
const twilioTransport = new TwilioRealtimeTransportLayer({
  twilioWebSocket: websocketConnection,
});

const session = new RealtimeSession(agent, {
  // set your own transport
  transport: twilioTransport,
});

将你的 RealtimeSession 连接到 Twilio：

session.connect({ apiKey: 'your-openai-api-key' });

你在 RealtimeSession 中期望的任何事件和行为都会按预期工作，包括工具调用、护栏等。更多关于如何将 RealtimeSession 与语音智能体结合使用的信息，请阅读语音智能体概述。

提示与注意事项

速度是关键。

为了接收 Twilio 的所有必要事件和音频，你应在拿到 WebSocket 连接引用后尽快创建 TwilioRealtimeTransportLayer 实例，并在之后立即调用 session.connect()。
访问 Twilio 原始事件。

如果你想访问 Twilio 发送的原始事件，可以监听 RealtimeSession 实例上的 transport_event 事件。每个来自 Twilio 的事件类型都是 twilio_message，并包含 message 属性，其中带有原始事件数据。
查看调试日志。

有时你可能会遇到需要更多上下文信息的问题。设置 DEBUG=openai-agents* 环境变量后，将显示 Agents SDK 的所有调试日志。或者，你也可以仅启用 Twilio 适配器的调试日志，使用 DEBUG=openai-agents:extensions:twilio*。

完整示例服务器

下面是一个完整的端到端 WebSocket 服务器示例，用于接收来自 Twilio 的请求并将其转发到 RealtimeSession。

import Fastify from 'fastify';
import type { FastifyInstance, FastifyReply, FastifyRequest } from 'fastify';
import dotenv from 'dotenv';
import fastifyFormBody from '@fastify/formbody';
import fastifyWs from '@fastify/websocket';
import {
  RealtimeAgent,
  RealtimeSession,
  backgroundResult,
  tool,
} from '@openai/agents/realtime';
import { TwilioRealtimeTransportLayer } from '@openai/agents-extensions';
import { hostedMcpTool } from '@openai/agents';
import { z } from 'zod';
import process from 'node:process';

// Load environment variables from .env file
dotenv.config();

// Retrieve the OpenAI API key from environment variables. You must have OpenAI Realtime API access.
const { OPENAI_API_KEY } = process.env;
if (!OPENAI_API_KEY) {
  console.error('Missing OpenAI API key. Please set it in the .env file.');
  process.exit(1);
}
const PORT = +(process.env.PORT || 5050);

// Initialize Fastify
const fastify = Fastify();
fastify.register(fastifyFormBody);
fastify.register(fastifyWs);

const weatherTool = tool({
  name: 'weather',
  description: 'Get the weather in a given location.',
  parameters: z.object({
    location: z.string(),
  }),
  execute: async ({ location }: { location: string }) => {
    return backgroundResult(`The weather in ${location} is sunny.`);
  },
});

const secretTool = tool({
  name: 'secret',
  description: 'A secret tool to tell the special number.',
  parameters: z.object({
    question: z
      .string()
      .describe(
        'The question to ask the secret tool; mainly about the special number.',
      ),
  }),
  execute: async ({ question }: { question: string }) => {
    return `The answer to ${question} is 42.`;
  },
  needsApproval: true,
});

const agent = new RealtimeAgent({
  name: 'Greeter',
  instructions:
    'You are a friendly assistant. When you use a tool always first say what you are about to do.',
  tools: [
    hostedMcpTool({
      serverLabel: 'deepwiki',
      serverUrl: 'https://mcp.deepwiki.com/mcp',
    }),
    secretTool,
    weatherTool,
  ],
});

// Root Route
fastify.get('/', async (_request: FastifyRequest, reply: FastifyReply) => {
  reply.send({ message: 'Twilio Media Stream Server is running!' });
});

// Route for Twilio to handle incoming and outgoing calls
// <Say> punctuation to improve text-to-speech translation
fastify.all(
  '/incoming-call',
  async (request: FastifyRequest, reply: FastifyReply) => {
    const twimlResponse = `
<?xml version="1.0" encoding="UTF-8"?>
<Response>
    <Say>O.K. you can start talking!</Say>
    <Connect>
        <Stream url="wss://${request.headers.host}/media-stream" />
    </Connect>
</Response>`.trim();
    reply.type('text/xml').send(twimlResponse);
  },
);

// WebSocket route for media-stream
fastify.register(async (scopedFastify: FastifyInstance) => {
  scopedFastify.get(
    '/media-stream',
    { websocket: true },
    async (connection: any) => {
      const twilioTransportLayer = new TwilioRealtimeTransportLayer({
        twilioWebSocket: connection,
      });

      const session = new RealtimeSession(agent, {
        transport: twilioTransportLayer,
        model: 'gpt-realtime',
        config: {
          audio: {
            output: {
              voice: 'verse',
            },
          },
        },
      });

      session.on('mcp_tools_changed', (tools: { name: string }[]) => {
        const toolNames = tools.map((tool) => tool.name).join(', ');
        console.log(`Available MCP tools: ${toolNames || 'None'}`);
      });

      session.on(
        'tool_approval_requested',
        (_context: unknown, _agent: unknown, approvalRequest: any) => {
          console.log(
            `Approving tool call for ${approvalRequest.approvalItem.rawItem.name}.`,
          );
          session
            .approve(approvalRequest.approvalItem)
            .catch((error: unknown) =>
              console.error('Failed to approve tool call.', error),
            );
        },
      );

      session.on(
        'mcp_tool_call_completed',
        (_context: unknown, _agent: unknown, toolCall: unknown) => {
          console.log('MCP tool call completed.', toolCall);
        },
      );

      await session.connect({
        apiKey: OPENAI_API_KEY,
      });
      console.log('Connected to the OpenAI Realtime API');
    },
  );
});

fastify.listen({ port: PORT }, (err: Error | null) => {
  if (err) {
    console.error(err);
    process.exit(1);
  }
  console.log(`Server is listening on port ${PORT}`);
});

process.on('SIGINT', () => {
  fastify.close();
  process.exit(0);
});