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add doc and refactor to switch
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‎content/providers/01-ai-sdk-providers/05-anthropic.mdx‎

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@@ -208,6 +208,97 @@ console.log(text); // text response
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See [AI SDK UI: Chatbot](/docs/ai-sdk-ui/chatbot#reasoning) for more details
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on how to integrate reasoning into your chatbot.
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### Context Management
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Anthropic's Context Management feature allows you to automatically manage conversation context by clearing tool uses or thinking content when certain conditions are met. This helps optimize token usage and manage long conversations more efficiently.
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You can configure context management using the `contextManagement` provider option:
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```ts highlight="7-20"
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import { anthropic, AnthropicProviderOptions } from '@ai-sdk/anthropic';
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import { generateText } from 'ai';
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const result = await generateText({
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model: anthropic('claude-3-7-sonnet-20250219'),
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prompt: 'Continue our conversation...',
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providerOptions: {
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anthropic: {
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contextManagement: {
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edits: [
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{
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type: 'clear_tool_uses_20250919',
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trigger: { type: 'input_tokens', value: 10000 },
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keep: { type: 'tool_uses', value: 5 },
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clearAtLeast: { type: 'input_tokens', value: 1000 },
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clearToolInputs: true,
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excludeTools: ['important_tool'],
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},
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],
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},
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} satisfies AnthropicProviderOptions,
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},
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});
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// Check what was cleared
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console.log(result.providerMetadata?.anthropic?.contextManagement);
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```
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#### Clear Tool Uses
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The `clear_tool_uses_20250919` edit type removes old tool calls from the conversation history:
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- **trigger** - Condition that triggers the clearing (e.g., `{ type: 'input_tokens', value: 10000 }`)
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- **keep** - How many recent tool uses to preserve (e.g., `{ type: 'tool_uses', value: 5 }`)
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- **clearAtLeast** - Minimum amount to clear (e.g., `{ type: 'input_tokens', value: 1000 }`)
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- **clearToolInputs** - Whether to clear tool input parameters (boolean)
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- **excludeTools** - Array of tool names to never clear
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#### Clear Thinking
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The `clear_thinking_20251015` edit type removes thinking/reasoning content:
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```ts
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const result = await generateText({
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model: anthropic('claude-opus-4-20250514'),
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prompt: 'Continue reasoning...',
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providerOptions: {
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anthropic: {
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thinking: { type: 'enabled', budgetTokens: 12000 },
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contextManagement: {
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edits: [
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{
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type: 'clear_thinking_20251015',
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keep: { type: 'thinking_blocks', value: 2 },
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},
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],
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},
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} satisfies AnthropicProviderOptions,
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},
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});
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```
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#### Applied Edits Metadata
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After generation, you can check which edits were applied in the provider metadata:
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```ts
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const metadata = result.providerMetadata?.anthropic?.contextManagement;
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if (metadata?.appliedEdits) {
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metadata.appliedEdits.forEach(edit => {
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if (edit.type === 'clear_tool_uses_20250919') {
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console.log(`Cleared ${edit.clearedToolUses} tool uses`);
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console.log(`Freed ${edit.clearedInputTokens} tokens`);
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} else if (edit.type === 'clear_thinking_20251015') {
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console.log(`Cleared ${edit.clearedThinkingBlocks} thinking blocks`);
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console.log(`Freed ${edit.clearedInputTokens} tokens`);
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}
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});
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}
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```
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For more details, see [Anthropic's Context Management documentation](https://docs.anthropic.com/en/docs/build-with-claude/context-management).
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### Cache Control
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In the messages and message parts, you can use the `providerOptions` property to set cache control breakpoints.

‎examples/ai-core/src/generate-text/anthropic-context-management.ts‎

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@@ -4,126 +4,128 @@ import 'dotenv/config';
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import { z } from 'zod';
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async function main() {
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const result = await generateText({
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model: anthropic('claude-3-7-sonnet-20250219'),
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messages: [
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{
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role: 'user',
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content: 'What is the weather in San Francisco?'
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},
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{
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role: 'assistant',
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content: [
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{
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type: 'tool-call',
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toolCallId: 'tool_1',
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toolName: 'weather',
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input: { location: 'San Francisco' },
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}
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]
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},
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{
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role: 'tool',
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content: [
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{
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type: 'tool-result',
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toolCallId: 'tool_1',
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toolName: 'weather',
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output: {
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type: 'json',
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value: { temperature: 72, condition: 'sunny' }
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}
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}
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]
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},
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{
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role: 'user',
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content: 'What about New York?'
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const result = await generateText({
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model: anthropic('claude-3-7-sonnet-20250219'),
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messages: [
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{
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role: 'user',
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content: 'What is the weather in San Francisco?',
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},
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{
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role: 'assistant',
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content: [
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{
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type: 'tool-call',
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toolCallId: 'tool_1',
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toolName: 'weather',
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input: { location: 'San Francisco' },
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},
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],
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},
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{
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role: 'tool',
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content: [
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{
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type: 'tool-result',
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toolCallId: 'tool_1',
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toolName: 'weather',
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output: {
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type: 'json',
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value: { temperature: 72, condition: 'sunny' },
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},
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{
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role: 'assistant',
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content: [
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{
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type: 'tool-call',
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toolCallId: 'tool_2',
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toolName: 'weather',
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input: { location: 'New York' }
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}
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]
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},
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],
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},
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{
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role: 'user',
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content: 'What about New York?',
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},
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{
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role: 'assistant',
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content: [
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{
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type: 'tool-call',
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toolCallId: 'tool_2',
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toolName: 'weather',
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input: { location: 'New York' },
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},
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],
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},
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{
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role: 'tool',
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content: [
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{
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type: 'tool-result',
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toolCallId: 'tool_2',
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toolName: 'weather',
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output: {
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type: 'json',
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value: { temperature: 65, condition: 'cloudy' },
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},
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},
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],
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},
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{
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role: 'user',
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content: 'compare the two cities.',
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},
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],
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tools: {
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weather: tool({
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description: 'Get the weather of a location',
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inputSchema: z.object({
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location: z.string().describe('The location to get the weather for'),
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}),
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execute: async ({ location }) => ({
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location,
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temperature: 72 + Math.floor(Math.random() * 21) - 10,
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condition: 'sunny',
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}),
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}),
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},
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providerOptions: {
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anthropic: {
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contextManagement: {
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edits: [
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{
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role: 'tool',
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content: [
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{
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type: 'tool-result',
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toolCallId: 'tool_2',
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toolName: 'weather',
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output: {
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type: 'json',
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value: { temperature: 65, condition: 'cloudy' }
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}
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}
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]
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type: 'clear_tool_uses_20250919',
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trigger: {
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type: 'input_tokens',
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value: 1000,
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},
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keep: {
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type: 'tool_uses',
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value: 1,
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},
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clearAtLeast: {
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type: 'input_tokens',
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value: 500,
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},
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clearToolInputs: true,
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excludeTools: ['important_tool'],
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},
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{
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role: 'user',
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content: 'compare the two cities.'
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}
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],
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tools: {
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weather: tool({
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description: 'Get the weather of a location',
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inputSchema: z.object({
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location: z.string().describe('The location to get the weather for')
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}),
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execute: async ({ location }) => ({
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location,
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temperature: 72 + Math.floor(Math.random() * 21) - 10,
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condition: 'sunny'
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})
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})
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],
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},
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providerOptions: {
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anthropic: {
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contextManagement: {
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edits: [
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{
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type: 'clear_tool_uses_20250919',
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trigger: {
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type: 'input_tokens',
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value: 1000
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},
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keep: {
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type: 'tool_uses',
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value: 1
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},
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clearAtLeast: {
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type: 'input_tokens',
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value: 500
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},
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clearToolInputs: true,
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excludeTools: ['important_tool']
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}
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]
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}
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} satisfies AnthropicProviderOptions
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}
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});
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} satisfies AnthropicProviderOptions,
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},
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});
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console.log('Text:');
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console.log(result.text);
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console.log();
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console.log('Text:');
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console.log(result.text);
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console.log();
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console.log('Context Management:');
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console.log(JSON.stringify(
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result.providerMetadata?.anthropic?.contextManagement,
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null,
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2
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));
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console.log();
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console.log('Context Management:');
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console.log(
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JSON.stringify(
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result.providerMetadata?.anthropic?.contextManagement,
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null,
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2,
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),
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);
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console.log();
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console.log('Usage:');
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console.log(JSON.stringify(result.usage, null, 2));
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};
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console.log('Usage:');
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console.log(JSON.stringify(result.usage, null, 2));
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}
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main().catch(console.error);
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main().catch(console.error);

‎packages/anthropic/src/anthropic-message-metadata.ts‎

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@@ -48,15 +48,15 @@ export interface AnthropicMessageMetadata {
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contextManagement: {
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appliedEdits: Array<
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| {
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type: 'clear_tool_uses_20250919';
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clearedToolUses: number;
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clearedInputTokens: number;
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}
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type: 'clear_tool_uses_20250919';
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clearedToolUses: number;
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clearedInputTokens: number;
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}
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| {
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type: 'clear_thinking_20251015';
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clearedThinkingTurns: number;
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clearedInputTokens: number;
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}
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type: 'clear_thinking_20251015';
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clearedThinkingTurns: number;
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clearedInputTokens: number;
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}
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>;
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} | null;
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}

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