init claude-code
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// biome-ignore-all assist/source/organizeImports: ANT-ONLY import markers must not be reordered
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import { CONTEXT_1M_BETA_HEADER } from '../constants/betas.js'
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import { getGlobalConfig } from './config.js'
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import { isEnvTruthy } from './envUtils.js'
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import { getCanonicalName } from './model/model.js'
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import { getModelCapability } from './model/modelCapabilities.js'
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// Model context window size (200k tokens for all models right now)
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export const MODEL_CONTEXT_WINDOW_DEFAULT = 200_000
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// Maximum output tokens for compact operations
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export const COMPACT_MAX_OUTPUT_TOKENS = 20_000
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// Default max output tokens
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const MAX_OUTPUT_TOKENS_DEFAULT = 32_000
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const MAX_OUTPUT_TOKENS_UPPER_LIMIT = 64_000
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// Capped default for slot-reservation optimization. BQ p99 output = 4,911
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// tokens, so 32k/64k defaults over-reserve 8-16× slot capacity. With the cap
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// enabled, <1% of requests hit the limit; those get one clean retry at 64k
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// (see query.ts max_output_tokens_escalate). Cap is applied in
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// claude.ts:getMaxOutputTokensForModel to avoid the growthbook→betas→context
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// import cycle.
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export const CAPPED_DEFAULT_MAX_TOKENS = 8_000
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export const ESCALATED_MAX_TOKENS = 64_000
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/**
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* Check if 1M context is disabled via environment variable.
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* Used by C4E admins to disable 1M context for HIPAA compliance.
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*/
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export function is1mContextDisabled(): boolean {
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return isEnvTruthy(process.env.CLAUDE_CODE_DISABLE_1M_CONTEXT)
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}
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export function has1mContext(model: string): boolean {
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if (is1mContextDisabled()) {
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return false
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}
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return /\[1m\]/i.test(model)
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}
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// @[MODEL LAUNCH]: Update this pattern if the new model supports 1M context
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export function modelSupports1M(model: string): boolean {
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if (is1mContextDisabled()) {
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return false
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}
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const canonical = getCanonicalName(model)
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return canonical.includes('claude-sonnet-4') || canonical.includes('opus-4-6')
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}
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export function getContextWindowForModel(
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model: string,
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betas?: string[],
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): number {
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// Allow override via environment variable (ant-only)
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// This takes precedence over all other context window resolution, including 1M detection,
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// so users can cap the effective context window for local decisions (auto-compact, etc.)
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// while still using a 1M-capable endpoint.
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if (
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process.env.USER_TYPE === 'ant' &&
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process.env.CLAUDE_CODE_MAX_CONTEXT_TOKENS
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) {
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const override = parseInt(process.env.CLAUDE_CODE_MAX_CONTEXT_TOKENS, 10)
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if (!isNaN(override) && override > 0) {
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return override
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}
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}
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// [1m] suffix — explicit client-side opt-in, respected over all detection
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if (has1mContext(model)) {
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return 1_000_000
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}
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const cap = getModelCapability(model)
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if (cap?.max_input_tokens && cap.max_input_tokens >= 100_000) {
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if (
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cap.max_input_tokens > MODEL_CONTEXT_WINDOW_DEFAULT &&
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is1mContextDisabled()
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) {
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return MODEL_CONTEXT_WINDOW_DEFAULT
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}
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return cap.max_input_tokens
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}
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if (betas?.includes(CONTEXT_1M_BETA_HEADER) && modelSupports1M(model)) {
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return 1_000_000
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}
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if (getSonnet1mExpTreatmentEnabled(model)) {
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return 1_000_000
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}
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if (process.env.USER_TYPE === 'ant') {
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const antModel = resolveAntModel(model)
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if (antModel?.contextWindow) {
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return antModel.contextWindow
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}
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}
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return MODEL_CONTEXT_WINDOW_DEFAULT
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}
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export function getSonnet1mExpTreatmentEnabled(model: string): boolean {
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if (is1mContextDisabled()) {
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return false
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}
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// Only applies to sonnet 4.6 without an explicit [1m] suffix
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if (has1mContext(model)) {
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return false
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}
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if (!getCanonicalName(model).includes('sonnet-4-6')) {
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return false
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}
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return getGlobalConfig().clientDataCache?.['coral_reef_sonnet'] === 'true'
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}
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/**
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* Calculate context window usage percentage from token usage data.
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* Returns used and remaining percentages, or null values if no usage data.
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*/
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export function calculateContextPercentages(
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currentUsage: {
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input_tokens: number
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cache_creation_input_tokens: number
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cache_read_input_tokens: number
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} | null,
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contextWindowSize: number,
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): { used: number | null; remaining: number | null } {
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if (!currentUsage) {
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return { used: null, remaining: null }
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}
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const totalInputTokens =
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currentUsage.input_tokens +
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currentUsage.cache_creation_input_tokens +
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currentUsage.cache_read_input_tokens
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const usedPercentage = Math.round(
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(totalInputTokens / contextWindowSize) * 100,
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)
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const clampedUsed = Math.min(100, Math.max(0, usedPercentage))
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return {
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used: clampedUsed,
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remaining: 100 - clampedUsed,
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}
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}
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/**
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* Returns the model's default and upper limit for max output tokens.
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*/
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export function getModelMaxOutputTokens(model: string): {
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default: number
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upperLimit: number
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} {
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let defaultTokens: number
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let upperLimit: number
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if (process.env.USER_TYPE === 'ant') {
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const antModel = resolveAntModel(model.toLowerCase())
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if (antModel) {
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defaultTokens = antModel.defaultMaxTokens ?? MAX_OUTPUT_TOKENS_DEFAULT
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upperLimit = antModel.upperMaxTokensLimit ?? MAX_OUTPUT_TOKENS_UPPER_LIMIT
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return { default: defaultTokens, upperLimit }
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}
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}
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const m = getCanonicalName(model)
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if (m.includes('opus-4-6')) {
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defaultTokens = 64_000
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upperLimit = 128_000
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} else if (m.includes('sonnet-4-6')) {
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defaultTokens = 32_000
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upperLimit = 128_000
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} else if (
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m.includes('opus-4-5') ||
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m.includes('sonnet-4') ||
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m.includes('haiku-4')
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) {
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defaultTokens = 32_000
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upperLimit = 64_000
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} else if (m.includes('opus-4-1') || m.includes('opus-4')) {
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defaultTokens = 32_000
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upperLimit = 32_000
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} else if (m.includes('claude-3-opus')) {
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defaultTokens = 4_096
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upperLimit = 4_096
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} else if (m.includes('claude-3-sonnet')) {
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defaultTokens = 8_192
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upperLimit = 8_192
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} else if (m.includes('claude-3-haiku')) {
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defaultTokens = 4_096
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upperLimit = 4_096
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} else if (m.includes('3-5-sonnet') || m.includes('3-5-haiku')) {
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defaultTokens = 8_192
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upperLimit = 8_192
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} else if (m.includes('3-7-sonnet')) {
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defaultTokens = 32_000
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upperLimit = 64_000
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} else {
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defaultTokens = MAX_OUTPUT_TOKENS_DEFAULT
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upperLimit = MAX_OUTPUT_TOKENS_UPPER_LIMIT
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}
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const cap = getModelCapability(model)
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if (cap?.max_tokens && cap.max_tokens >= 4_096) {
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upperLimit = cap.max_tokens
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defaultTokens = Math.min(defaultTokens, upperLimit)
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}
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return { default: defaultTokens, upperLimit }
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}
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/**
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* Returns the max thinking budget tokens for a given model. The max
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* thinking tokens should be strictly less than the max output tokens.
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*
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* Deprecated since newer models use adaptive thinking rather than a
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* strict thinking token budget.
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*/
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export function getMaxThinkingTokensForModel(model: string): number {
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return getModelMaxOutputTokens(model).upperLimit - 1
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}
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