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refactor: update tokens.ts to export constants and functions, enhance type definitions, and adjust default values
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Danny Avila
parent
5b63aceda9
commit
088d90cf13
1 changed files with 45 additions and 66 deletions
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@ -260,7 +260,7 @@ const aggregateModels = {
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'gpt-oss-120b': 131000,
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};
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const maxTokensMap = {
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export const maxTokensMap = {
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[EModelEndpoint.azureOpenAI]: openAIModels,
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[EModelEndpoint.openAI]: aggregateModels,
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[EModelEndpoint.agents]: aggregateModels,
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@ -270,7 +270,7 @@ const maxTokensMap = {
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[EModelEndpoint.bedrock]: bedrockModels,
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};
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const modelMaxOutputs = {
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export const modelMaxOutputs = {
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o1: 32268, // -500 from max: 32,768
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'o1-mini': 65136, // -500 from max: 65,536
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'o1-preview': 32268, // -500 from max: 32,768
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@ -279,7 +279,7 @@ const modelMaxOutputs = {
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'gpt-5-nano': 128000,
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'gpt-oss-20b': 131000,
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'gpt-oss-120b': 131000,
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system_default: 1024,
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system_default: 32000,
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};
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/** Outputs from https://docs.anthropic.com/en/docs/about-claude/models/all-models#model-names */
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@ -295,7 +295,7 @@ const anthropicMaxOutputs = {
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'claude-3-7-sonnet': 128000,
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};
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const maxOutputTokensMap = {
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export const maxOutputTokensMap = {
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[EModelEndpoint.anthropic]: anthropicMaxOutputs,
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[EModelEndpoint.azureOpenAI]: modelMaxOutputs,
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[EModelEndpoint.openAI]: modelMaxOutputs,
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@ -308,7 +308,7 @@ const maxOutputTokensMap = {
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* @param {Record<string, number> | EndpointTokenConfig} tokensMap
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* @returns {string|null}
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*/
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function findMatchingPattern(
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export function findMatchingPattern(
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modelName: string,
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tokensMap: Record<string, number> | EndpointTokenConfig,
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): string | null {
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@ -326,66 +326,56 @@ function findMatchingPattern(
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/**
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* Retrieves a token value for a given model name from a tokens map.
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*
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* @param {string} modelName - The name of the model to look up.
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* @param {EndpointTokenConfig | Record<string, number>} tokensMap - The map of model names to token values.
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* @param {string} [key='context'] - The key to look up in the tokens map.
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* @returns {number|undefined} The token value for the given model or undefined if no match is found.
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* @param modelName - The name of the model to look up.
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* @param tokensMap - The map of model names to token values.
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* @param [key='context'] - The key to look up in the tokens map.
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* @returns The token value for the given model or undefined if no match is found.
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*/
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function getModelTokenValue(
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export function getModelTokenValue(
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modelName: string,
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tokensMap: EndpointTokenConfig | Record<string, number>,
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key = 'context',
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tokensMap?: EndpointTokenConfig | Record<string, number>,
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key = 'context' as keyof TokenConfig,
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): number | undefined {
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if (typeof modelName !== 'string' || !tokensMap) {
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return undefined;
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}
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if (
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tokensMap[modelName] &&
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typeof tokensMap[modelName] === 'object' &&
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'context' in (tokensMap[modelName] as object)
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) {
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return (tokensMap[modelName] as TokenConfig).context;
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const value = tokensMap[modelName];
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if (typeof value === 'number') {
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return value;
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}
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if (tokensMap[modelName] && typeof tokensMap[modelName] === 'number') {
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return tokensMap[modelName] as number;
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if (value?.context) {
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return value.context;
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}
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const matchedPattern = findMatchingPattern(modelName, tokensMap);
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if (matchedPattern) {
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const result = tokensMap[matchedPattern];
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if (result && typeof result === 'object' && key in result) {
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return (result as TokenConfig)[key as keyof TokenConfig] as number;
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}
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if (typeof result === 'number') {
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return result;
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}
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const tokenValue = result?.[key];
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if (typeof tokenValue === 'number') {
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return tokenValue;
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}
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return tokensMap.system_default as number | undefined;
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}
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if (typeof tokensMap === 'object' && 'system_default' in tokensMap) {
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return (tokensMap as Record<string, number>).system_default;
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}
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/** Remove this comment once confirmed this shares same functionality with original js version:
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* returning undefined when
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* tokenMaps[modelName] didn't exist,
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* tokenMaps wasn't an object (EndpointTokenConfig),
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* modelName didn't match any pattern in tokenMaps,
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* and tokenMaps didn't have a system_default property */
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return undefined;
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return tokensMap.system_default as number | undefined;
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}
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/**
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* Retrieves the maximum tokens for a given model name.
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*
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* @param {string} modelName - The name of the model to look up.
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* @param {string} endpoint - The endpoint (default is 'openAI').
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* @param {EndpointTokenConfig} [endpointTokenConfig] - Token Config for current endpoint to use for max tokens lookup
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* @returns {number|undefined} The maximum tokens for the given model or undefined if no match is found.
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* @param modelName - The name of the model to look up.
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* @param endpoint - The endpoint (default is 'openAI').
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* @param [endpointTokenConfig] - Token Config for current endpoint to use for max tokens lookup
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* @returns The maximum tokens for the given model or undefined if no match is found.
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*/
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function getModelMaxTokens(
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export function getModelMaxTokens(
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modelName: string,
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endpoint = EModelEndpoint.openAI,
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endpointTokenConfig?: EndpointTokenConfig,
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@ -397,12 +387,12 @@ function getModelMaxTokens(
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/**
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* Retrieves the maximum output tokens for a given model name.
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*
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* @param {string} modelName - The name of the model to look up.
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* @param {string} endpoint - The endpoint (default is 'openAI').
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* @param {EndpointTokenConfig} [endpointTokenConfig] - Token Config for current endpoint to use for max tokens lookup
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* @returns {number|undefined} The maximum output tokens for the given model or undefined if no match is found.
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* @param modelName - The name of the model to look up.
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* @param endpoint - The endpoint (default is 'openAI').
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* @param [endpointTokenConfig] - Token Config for current endpoint to use for max tokens lookup
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* @returns The maximum output tokens for the given model or undefined if no match is found.
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*/
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function getModelMaxOutputTokens(
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export function getModelMaxOutputTokens(
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modelName: string,
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endpoint = EModelEndpoint.openAI,
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endpointTokenConfig?: EndpointTokenConfig,
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@ -416,16 +406,19 @@ function getModelMaxOutputTokens(
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* Retrieves the model name key for a given model name input. If the exact model name isn't found,
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* it searches for partial matches within the model name, checking keys in reverse order.
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*
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* @param {string} modelName - The name of the model to look up.
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* @param {string} endpoint - The endpoint (default is 'openAI').
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* @returns {string|undefined} The model name key for the given model; returns input if no match is found and is string.
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* @param modelName - The name of the model to look up.
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* @param endpoint - The endpoint (default is 'openAI').
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* @returns The model name key for the given model; returns input if no match is found and is string.
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*
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* @example
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* matchModelName('gpt-4-32k-0613'); // Returns 'gpt-4-32k-0613'
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* matchModelName('gpt-4-32k-unknown'); // Returns 'gpt-4-32k'
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* matchModelName('unknown-model'); // Returns undefined
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*/
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function matchModelName(modelName: string, endpoint = EModelEndpoint.openAI): string | undefined {
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export function matchModelName(
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modelName: string,
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endpoint = EModelEndpoint.openAI,
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): string | undefined {
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if (typeof modelName !== 'string') {
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return undefined;
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}
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@ -443,7 +436,7 @@ function matchModelName(modelName: string, endpoint = EModelEndpoint.openAI): st
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return matchedPattern || modelName;
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}
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const modelSchema = z.object({
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export const modelSchema = z.object({
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id: z.string(),
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pricing: z.object({
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prompt: z.string(),
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@ -452,7 +445,7 @@ const modelSchema = z.object({
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context_length: z.number(),
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});
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const inputSchema = z.object({
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export const inputSchema = z.object({
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data: z.array(modelSchema),
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});
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@ -461,7 +454,7 @@ const inputSchema = z.object({
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* @param {{ data: Array<z.infer<typeof modelSchema>> }} input The input object containing base URL and data fetched from the API.
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* @returns {EndpointTokenConfig} The processed model data.
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*/
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function processModelData(input: z.infer<typeof inputSchema>): EndpointTokenConfig {
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export function processModelData(input: z.infer<typeof inputSchema>): EndpointTokenConfig {
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const validationResult = inputSchema.safeParse(input);
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if (!validationResult.success) {
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throw new Error('Invalid input data');
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@ -492,7 +485,7 @@ function processModelData(input: z.infer<typeof inputSchema>): EndpointTokenConf
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return tokenConfig;
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}
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const tiktokenModels = new Set([
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export const tiktokenModels = new Set([
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'text-davinci-003',
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'text-davinci-002',
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'text-davinci-001',
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@ -530,17 +523,3 @@ const tiktokenModels = new Set([
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'gpt-3.5-turbo',
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'gpt-3.5-turbo-0301',
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]);
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export {
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inputSchema,
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modelSchema,
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maxTokensMap,
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tiktokenModels,
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matchModelName,
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processModelData,
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getModelMaxTokens,
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maxOutputTokensMap,
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getModelTokenValue,
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findMatchingPattern,
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getModelMaxOutputTokens,
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};
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