Doug's Vercel AI SDK Usage Notes/Examples

import {
  anthropic,
  createAnthropic,
} from "@ai-sdk/anthropic";

const anthropicClient = createAnthropic();
await generateText({
    model: anthropicClient("claude-haiku-4-5"),
    prompt:
      "Calculate the mean and standard deviation of [1, 2, 3, 4, 5, 6, 7, 8, 9, 10].",
    tools: {
      code_execution: anthropic.tools.codeExecution_20250825(),
    },
});

We need to use the Vercel AI SDK piece to send messages, but we have to use the antrhopic foundry SDK to download the generated files using the beta files API.

import { writeFileSync } from "node:fs";
import {
  type AnthropicProviderOptions,
  anthropic,
  createAnthropic,
} from "@ai-sdk/anthropic";
import { AnthropicFoundry } from "@anthropic-ai/foundry-sdk";
import { generateText } from "ai";

const main = async () => {
  const anthropicClient = new AnthropicFoundry();
  const anthropic = createAnthropic();

  const result = await generateText({
    model: anthropic("claude-haiku-4-5"),
    prompt:
      "Write a haiku about the sea and include it in a word doc that also explains the history of haikus.",
    tools: {
      code_execution: anthropic.tools.codeExecution_20250825(),
    },
    maxRetries: 0,
    // timeout: 10 * 60 * 1000, // 10 minutes
    providerOptions: {
      anthropic: {
        container: {
          skills: [
            {
              type: "anthropic",
              skillId: "pdf",
            },
          ],
        },
      } satisfies AnthropicProviderOptions,
    },
  });

  console.log("Result:", result.text);

  const fileIds = [];
  for (const toolResult of result.toolResults) {
    if (
      toolResult.type === "tool-result" &&
      toolResult.toolName === "code_execution"
    ) {
      for (const content of toolResult.output.content) {
        if (content.type === "bash_code_execution_output") {
          fileIds.push(content.file_id);
        }
      }
    }
  }

  /// Download the generated files
  for (const fileId of fileIds) {
    const fileMetadata = await anthropicClient.beta.files.retrieveMetadata(
      fileId,
      {
        betas: ["files-api-2025-04-14"],
      },
    );
    const fileContent = await anthropicClient.beta.files.download(fileId, {
      betas: ["files-api-2025-04-14"],
    });

    // Step 4: Save to disk
    writeFileSync(
      fileMetadata.filename,
      Buffer.from(await fileContent.arrayBuffer()),
    );
    console.log(`Downloaded: ${fileMetadata.filename}`);
  }
};

const result = await generateText({
    model: anthropicAiSdkClient("claude-haiku-4-5"),
    prompt,
    providerOptions: {
      anthropic: {
        mcpServers: [
          {
            type: "url",
            name: "pubmedMcp",
            url: "https://pubmed.mcp.claude.com/mcp",
          },
        ],
      } satisfies AnthropicProviderOptions,
    },
  });

const result = await generateText({
    model: anthropicAiSdkClient("claude-haiku-4-5"),
    prompt,
    providerOptions: {
      anthropic: {
        mcpServers: [
          {
            type: "url",
            name: "clinicalTrialsMcp",
            url: "https://mcp.deepsense.ai/clinical_trials/mcp",
          },
        ],
      } satisfies AnthropicProviderOptions,
    },
  });