Call all of the AI SDK methods

js/src/tests/vercel_exporter.int.test.ts

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+import { openai } from "@ai-sdk/openai";
+import { NodeSDK } from "@opentelemetry/sdk-node";
+import { z } from "zod";
+import { LangSmithAISDKExporter } from "../wrappers/vercel.js";
+
+import {
+  generateText,
+  streamText,
+  generateObject,
+  streamObject,
+  embed,
+  embedMany,
+} from "ai";
+import { tool } from "ai";
+
+const telemetrySettings = {
+  isEnabled: true,
+  functionId: "functionId",
+  metadata: {
+    userId: "123",
+    language: "english",
+  },
+};
+
+test.concurrent("generateText", async () => {
+  const traceExporter = new LangSmithAISDKExporter();
+  const sdk = new NodeSDK({ traceExporter });
+  sdk.start();
+
+  function getOrders(userId: string) {
+    return `User ${userId} has the following orders: 1`;
+  }
+
+  function getTrackingInformation(orderId: string) {
+    return `Here is the tracking information for ${orderId}`;
+  }
+
+  await generateText({
+    model: openai("gpt-4o-mini"),
+    messages: [
+      {
+        role: "user",
+        content: "What are my orders and where are they? My user ID is 123",
+      },
+    ],
+    tools: {
+      listOrders: tool({
+        description: "list all orders",
+        parameters: z.object({ userId: z.string() }),
+        execute: async ({ userId }) => getOrders(userId),
+      }),
+      viewTrackingInformation: tool({
+        description: "view tracking information for a specific order",
+        parameters: z.object({ orderId: z.string() }),
+        execute: async ({ orderId }) => getTrackingInformation(orderId),
+      }),
+    },
+    experimental_telemetry: telemetrySettings,
+    maxSteps: 10,
+  });
+
+  await sdk.shutdown();
+});
+
+test.concurrent("streamText", async () => {
+  const traceExporter = new LangSmithAISDKExporter();
+  const sdk = new NodeSDK({ traceExporter });
+  sdk.start();
+
+  function getOrders(userId: string) {
+    return `User ${userId} has the following orders: 1`;
+  }
+
+  function getTrackingInformation(orderId: string) {
+    return `Here is the tracking information for ${orderId}`;
+  }
+
+  const result = await streamText({
+    model: openai("gpt-4o-mini"),
+    messages: [
+      {
+        role: "user",
+        content: "What are my orders and where are they? My user ID is 123",
+      },
+    ],
+    tools: {
+      listOrders: tool({
+        description: "list all orders",
+        parameters: z.object({ userId: z.string() }),
+        execute: async ({ userId }) => getOrders(userId),
+      }),
+      viewTrackingInformation: tool({
+        description: "view tracking information for a specific order",
+        parameters: z.object({ orderId: z.string() }),
+        execute: async ({ orderId }) => getTrackingInformation(orderId),
+      }),
+    },
+    experimental_telemetry: { isEnabled: true },
+    maxSteps: 10,
+  });
+
+  for await (const _stream of result.fullStream) {
+    // consume
+  }
+
+  await sdk.shutdown();
+});
+
+test.concurrent("generateObject", async () => {
+  const traceExporter = new LangSmithAISDKExporter();
+  const sdk = new NodeSDK({ traceExporter });
+  sdk.start();
+
+  await generateObject({
+    model: openai("gpt-4o-mini", { structuredOutputs: true }),
+    schema: z.object({
+      recipe: z.object({
+        city: z.string(),
+        unit: z.union([z.literal("celsius"), z.literal("fahrenheit")]),
+      }),
+    }),
+    prompt: "What's the weather in Prague?",
+    experimental_telemetry: telemetrySettings,
+  });
+
+  await sdk.shutdown();
+});
+
+test.concurrent("streamObject", async () => {
+  const traceExporter = new LangSmithAISDKExporter();
+  const sdk = new NodeSDK({ traceExporter });
+  sdk.start();
+
+  const result = await streamObject({
+    model: openai("gpt-4o-mini", { structuredOutputs: true }),
+    schema: z.object({
+      recipe: z.object({
+        city: z.string(),
+        unit: z.union([z.literal("celsius"), z.literal("fahrenheit")]),
+      }),
+    }),
+    prompt: "What's the weather in Prague?",
+    experimental_telemetry: telemetrySettings,
+  });
+
+  for await (const _partialObject of result.partialObjectStream) {
+    // pass
+  }
+
+  await sdk.shutdown();
+});
+
+test.concurrent("embed", async () => {
+  const traceExporter = new LangSmithAISDKExporter();
+  const sdk = new NodeSDK({ traceExporter });
+  sdk.start();
+
+  await embed({
+    model: openai.embedding("text-embedding-3-small"),
+    value: "prague castle at sunset",
+    experimental_telemetry: telemetrySettings,
+  });
+
+  await sdk.shutdown();
+});
+
+test.concurrent("embedMany", async () => {
+  const traceExporter = new LangSmithAISDKExporter();
+  const sdk = new NodeSDK({ traceExporter });
+  sdk.start();
+
+  await embedMany({
+    model: openai.embedding("text-embedding-3-small"),
+    values: [
+      "a peaceful meadow with wildflowers",
+      "bustling city street at rush hour",
+      "prague castle at sunset",
+    ],
+    experimental_telemetry: telemetrySettings,
+  });
+
+  await sdk.shutdown();
+});
+
+test.concurrent("generateText with image", async () => {
+  const traceExporter = new LangSmithAISDKExporter();
+  const sdk = new NodeSDK({ traceExporter });
+  sdk.start();
+
+  await generateText({
+    model: openai("gpt-4o-mini"),
+    messages: [
+      {
+        role: "user",
+        content: [
+          {
+            type: "text",
+            text: "What's in this picture?",
+          },
+          {
+            type: "image",
+            image: new URL("https://picsum.photos/200/300"),
+          },
+        ],
+      },
+    ],
+    experimental_telemetry: telemetrySettings,
+  });
+
+  await sdk.shutdown();
+});