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feat(provider/anthropic): support fine-grained tool streaming with eagerInputStreaming (#13078)
<!-- Welcome to contributing to AI SDK! We're excited to see your changes. We suggest you read the following contributing guide we've created before submitting: https://github.com/vercel/ai/blob/main/CONTRIBUTING.md --> ## Background <!-- Why was this change necessary? --> Fine-grained tool streaming is supported with an `eagerInputStreaming` flag ([anthropic doc](https://platform.claude.com/docs/en/agents-and-tools/tool-use/fine-grained-tool-streaming)), the feature is recently taken off beta ## Summary <!-- What did you change? --> - Added eagerInputStreaming provider option support for Anthropic function tools - Only custom (function) tools support this. This is not specified on Anthropic's docs, but Anthropic's API rejects eager_input_streaming on provider-defined tools with an "extra inputs are not permitted" validation error. If you'd like to test it, here is a sample request I sent: ``` curl https://api.anthropic.com/v1/messages \ -H "content-type: application/json" \ -H "x-api-key: $ANTHROPIC_API_KEY" \ -H "anthropic-version: 2023-06-01" \ -d '{ "model": "claude-sonnet-4-5-20250514", "max_tokens": 1024, "tools": [ { "type": "code_execution_20260120", "name": "code_execution", "eager_input_streaming": true } ], "messages": [ { "role": "user", "content": "Write and run a python script that prints hello world" } ], "stream": true }' ``` ## Manual Verification <!-- For features & bugfixes. Please explain how you *manually* verified that the change works end-to-end as expected (excluding automated tests). Remove the section if it's not needed (e.g. for docs). --> - added example script ## Checklist <!-- Do not edit this list. Leave items unchecked that don't apply. If you need to track subtasks, create a new "## Tasks" section Please check if the PR fulfills the following requirements: --> - [x] Tests have been added / updated (for bug fixes / features) - [x] Documentation has been added / updated (for bug fixes / features) - [x] A _patch_ changeset for relevant packages has been added (for bug fixes / features - run `pnpm changeset` in the project root) - [x] I have reviewed this pull request (self-review) ## Future Work <!-- Feel free to mention things not covered by this PR that can be done in future PRs. Remove the section if it's not needed. --> - backport to v5
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‎.changeset/pink-jeans-taste.md‎

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---
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'@ai-sdk/anthropic': patch
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---
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feat(anthropic): support eagerInputStreaming option for fine-grained tool streaming

‎examples/ai-functions/src/stream-text/anthropic/fine-grained-tool-streaming.ts‎

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import { createAnthropic } from '@ai-sdk/anthropic';
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import { streamText } from 'ai';
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import 'dotenv/config';
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import { z } from 'zod';
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const anthropic = createAnthropic();
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// fine grained tool streaming can be enabled with eager_input_streaming
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// it is currently supported on custom tools only
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// https://platform.claude.com/docs/en/agents-and-tools/tool-use/fine-grained-tool-streaming
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const tools = {
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write_to_file: {
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description:
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'Request to write content to a file. ALWAYS provide the COMPLETE file content, without any truncation.',
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inputSchema: z.object({
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path: z
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.string()
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.describe(
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'The path of the file to write to (relative to the current workspace directory)',
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),
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content: z.string().describe('The content to write to the file.'),
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}),
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providerOptions: {
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anthropic: {
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eagerInputStreaming: true,
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},
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},
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},
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} as const;
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async function main() {
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const result = streamText({
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model: anthropic('claude-sonnet-4-6'),
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messages: [
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{
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role: 'user',
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content: 'Write a bubble sort implementation in JavaScript to sort.js',
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},
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],
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tools,
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toolChoice: 'required',
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});
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// ── stream events ─────────────────────────────────────────────────────────
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let sawToolInputStart = false;
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let toolInputDeltaCount = 0;
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let toolInputTotalBytes = 0;
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let sawToolInputEnd = false;
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let reasoningDeltaCount = 0;
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// ts() prints a compact timestamp to stderr so we can see real-time ordering
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const T0 = Date.now();
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const ts = (label: string) =>
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process.stderr.write(
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`+${((Date.now() - T0) / 1000).toFixed(2)}s ${label}\n`,
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);
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ts('stream started');
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for await (const part of result.fullStream) {
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switch (part.type) {
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case 'reasoning-start':
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ts('[reasoning-start]');
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process.stdout.write('\n[reasoning-start]\n');
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break;
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case 'reasoning-delta':
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reasoningDeltaCount++;
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if (reasoningDeltaCount === 1 || reasoningDeltaCount % 500 === 0) {
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ts(`[reasoning-delta #${reasoningDeltaCount}]`);
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}
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// process.stdout.write(part.text); // suppress to reduce noise
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break;
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case 'reasoning-end':
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ts(`[reasoning-end] total-reasoning-deltas=${reasoningDeltaCount}`);
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process.stdout.write('\n[reasoning-end]\n');
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break;
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case 'text-start':
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ts('[text-start]');
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process.stdout.write('\n[text-start]\n');
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break;
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case 'text-delta':
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process.stdout.write(part.text);
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break;
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case 'text-end':
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ts('[text-end]');
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process.stdout.write('\n[text-end]\n');
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break;
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case 'tool-input-start':
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sawToolInputStart = true;
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ts(`[tool-input-start] tool=${part.toolName}`);
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process.stdout.write(
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`\n[tool-input-start] id=${part.id} tool=${part.toolName}\n`,
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);
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break;
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case 'tool-input-delta':
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toolInputDeltaCount++;
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toolInputTotalBytes += part.delta.length;
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if (toolInputDeltaCount === 1 || toolInputDeltaCount % 100 === 0) {
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ts(`[tool-input-delta #${toolInputDeltaCount}]`);
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}
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process.stdout.write(part.delta);
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break;
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case 'tool-input-end':
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sawToolInputEnd = true;
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ts(`[tool-input-end]`);
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process.stdout.write(`\n[tool-input-end] id=${part.id}\n`);
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break;
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case 'tool-call': {
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const preview = JSON.stringify(part.input).slice(0, 80);
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ts(`[tool-call] tool=${part.toolName}`);
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console.log(
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`\n[tool-call] tool=${part.toolName} input(preview)=${preview}…`,
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);
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break;
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}
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case 'start-step':
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ts('[start-step]');
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console.log('\n[start-step]');
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break;
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case 'finish-step':
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ts(`[finish-step] reason=${part.finishReason}`);
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console.log(
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`[finish-step] finishReason=${part.finishReason} usage=${JSON.stringify(part.usage)}`,
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);
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break;
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case 'finish':
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ts(`[finish] reason=${part.finishReason}`);
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console.log(
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`\n[finish] finishReason=${part.finishReason} usage=${JSON.stringify(part.totalUsage)}`,
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);
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break;
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case 'error':
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ts('[error]');
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console.error('\n[error]', part.error);
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break;
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}
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}
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// ── diagnosis ─────────────────────────────────────────────────────────────
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// Eager input streaming streams fewer, larger chunks
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// Threshold is heuristic — tune based on observed output.
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const avgChunkBytes =
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toolInputDeltaCount > 0
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? Math.round(toolInputTotalBytes / toolInputDeltaCount)
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: 0;
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const isEager = toolInputDeltaCount >= 1 && avgChunkBytes >= 12;
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console.log('\n=== Summary ===');
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console.log('tool-input-start received :', sawToolInputStart);
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console.log('tool-input-delta count :', toolInputDeltaCount);
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console.log('tool-input-end received :', sawToolInputEnd);
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console.log('reasoning-delta count :', reasoningDeltaCount);
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console.log(
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`\nEager input streaming: ${isEager ? 'detected' : 'not detected'} (${toolInputDeltaCount} deltas, avg ${avgChunkBytes} bytes/chunk)`,
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);
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}
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main().catch(console.error);

‎packages/anthropic/src/anthropic-messages-api.ts‎

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description: string | undefined;
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input_schema: JSONSchema7;
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cache_control: AnthropicCacheControl | undefined;
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eager_input_streaming?: boolean;
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strict?: boolean;
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/**
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* When true, this tool is deferred and will only be loaded when

‎packages/anthropic/src/anthropic-messages-language-model.test.ts‎

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name: 'calculator',
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description: 'Calculate math',
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inputSchema: { type: 'object', properties: {} },
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providerOptions: {
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anthropic: { eagerInputStreaming: true },
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},
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},
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{
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type: 'provider',
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name: 'calculator',
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description: 'Calculate math',
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input_schema: { type: 'object', properties: {} },
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eager_input_streaming: true,
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});
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expect(requestBody.tools[1]).toEqual({

‎packages/anthropic/src/anthropic-prepare-tools.test.ts‎

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name: 'testFunction',
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description: 'A test function',
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inputSchema: { type: 'object', properties: {} },
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providerOptions: {
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anthropic: { eagerInputStreaming: true },
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},
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},
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],
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toolChoice: undefined,
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name: 'testFunction',
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description: 'A test function',
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input_schema: { type: 'object', properties: {} },
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eager_input_streaming: true,
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},
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]);
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expect(result.toolChoice).toBeUndefined();

‎packages/anthropic/src/anthropic-prepare-tools.ts‎

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allowedCallers?: Array<
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'direct' | 'code_execution_20250825' | 'code_execution_20260120'
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>;
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eagerInputStreaming?: boolean;
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}
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export async function prepareTools({
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const anthropicOptions = tool.providerOptions?.anthropic as
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| AnthropicToolOptions
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| undefined;
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// eager_input_streaming is only supported on custom (function) tools
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const eagerInputStreaming = anthropicOptions?.eagerInputStreaming;
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const deferLoading = anthropicOptions?.deferLoading;
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const allowedCallers = anthropicOptions?.allowedCallers;
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description: tool.description,
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input_schema: tool.inputSchema,
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cache_control: cacheControl,
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...(eagerInputStreaming ? { eager_input_streaming: true } : {}),
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...(supportsStructuredOutput === true && tool.strict != null
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? { strict: tool.strict }
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: {}),

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