mirror of
https://github.com/danny-avila/LibreChat.git
synced 2026-02-11 12:04:24 +01:00
refactor: remove type re-exports from @librechat/api tokens
Update all imports of TokenConfig and EndpointTokenConfig to import directly from librechat-data-provider instead of re-exporting through packages/api/src/types/tokens.ts. Remove the now-unnecessary re-export file and its barrel export.
This commit is contained in:
Marco Beretta
parent
3e9ddbf073
commit
9ff227a5b2
12 changed files with 584 additions and 592 deletions
|
|
@ -1,13 +1,13 @@
|
|||
/** Note: No hard-coded values should be used in this file. */
|
||||
const { EModelEndpoint } = require('librechat-data-provider');
|
||||
const {
|
||||
EModelEndpoint,
|
||||
maxTokensMap,
|
||||
matchModelName,
|
||||
processModelData,
|
||||
getModelMaxTokens,
|
||||
maxOutputTokensMap,
|
||||
findMatchingPattern,
|
||||
} = require('@librechat/api');
|
||||
} = require('librechat-data-provider');
|
||||
const { processModelData } = require('@librechat/api');
|
||||
|
||||
describe('getModelMaxTokens', () => {
|
||||
test('should return correct tokens for exact match', () => {
|
||||
|
|
@ -485,7 +485,7 @@ describe('getModelMaxTokens', () => {
|
|||
});
|
||||
|
||||
test('should return correct max output tokens for GPT-5 models', () => {
|
||||
const { getModelMaxOutputTokens } = require('@librechat/api');
|
||||
const { getModelMaxOutputTokens } = require('librechat-data-provider');
|
||||
['gpt-5', 'gpt-5-mini', 'gpt-5-nano', 'gpt-5-pro'].forEach((model) => {
|
||||
expect(getModelMaxOutputTokens(model)).toBe(maxOutputTokensMap[EModelEndpoint.openAI][model]);
|
||||
expect(getModelMaxOutputTokens(model, EModelEndpoint.openAI)).toBe(
|
||||
|
|
@ -498,7 +498,7 @@ describe('getModelMaxTokens', () => {
|
|||
});
|
||||
|
||||
test('should return correct max output tokens for GPT-OSS models', () => {
|
||||
const { getModelMaxOutputTokens } = require('@librechat/api');
|
||||
const { getModelMaxOutputTokens } = require('librechat-data-provider');
|
||||
['gpt-oss-20b', 'gpt-oss-120b'].forEach((model) => {
|
||||
expect(getModelMaxOutputTokens(model)).toBe(maxOutputTokensMap[EModelEndpoint.openAI][model]);
|
||||
expect(getModelMaxOutputTokens(model, EModelEndpoint.openAI)).toBe(
|
||||
|
|
@ -745,7 +745,7 @@ describe('Meta Models Tests', () => {
|
|||
});
|
||||
|
||||
describe('DeepSeek Max Output Tokens', () => {
|
||||
const { getModelMaxOutputTokens } = require('@librechat/api');
|
||||
const { getModelMaxOutputTokens } = require('librechat-data-provider');
|
||||
|
||||
test('should return correct max output tokens for deepseek-chat', () => {
|
||||
const expected = maxOutputTokensMap[EModelEndpoint.openAI]['deepseek-chat'];
|
||||
|
|
@ -1123,7 +1123,7 @@ describe('Claude Model Tests', () => {
|
|||
});
|
||||
|
||||
it('should return correct max output tokens for Claude Opus 4.6 (128K)', () => {
|
||||
const { getModelMaxOutputTokens } = require('@librechat/api');
|
||||
const { getModelMaxOutputTokens } = require('librechat-data-provider');
|
||||
expect(getModelMaxOutputTokens('claude-opus-4-6', EModelEndpoint.anthropic)).toBe(
|
||||
maxOutputTokensMap[EModelEndpoint.anthropic]['claude-opus-4-6'],
|
||||
);
|
||||
|
|
|
|||
|
|
@ -1,10 +1,10 @@
|
|||
import { useEffect, useMemo } from 'react';
|
||||
import { useParams } from 'react-router-dom';
|
||||
import { useSetAtom, useAtomValue } from 'jotai';
|
||||
import { getModelMaxTokens, isAgentsEndpoint } from 'librechat-data-provider';
|
||||
import { isAgentsEndpoint, getModelMaxTokens } from 'librechat-data-provider';
|
||||
import type { TMessage } from 'librechat-data-provider';
|
||||
import { tokenUsageAtom, type TokenUsage } from '~/store/tokenUsage';
|
||||
import { useGetMessagesByConvoId, useGetAgentByIdQuery } from '~/data-provider';
|
||||
import { tokenUsageAtom, type TokenUsage } from '~/store/tokenUsage';
|
||||
import { useChatContext } from '~/Providers';
|
||||
|
||||
/**
|
||||
|
|
|
|||
|
|
@ -8,6 +8,7 @@ import {
|
|||
isAgentsEndpoint,
|
||||
replaceSpecialVars,
|
||||
providerEndpointMap,
|
||||
getModelMaxTokens,
|
||||
} from 'librechat-data-provider';
|
||||
import type {
|
||||
AgentToolResources,
|
||||
|
|
@ -21,12 +22,7 @@ import type { GenericTool, LCToolRegistry, ToolMap, LCTool } from '@librechat/ag
|
|||
import type { Response as ServerResponse } from 'express';
|
||||
import type { IMongoFile } from '@librechat/data-schemas';
|
||||
import type { InitializeResultBase, ServerRequest, EndpointDbMethods } from '~/types';
|
||||
import {
|
||||
optionalChainWithEmptyCheck,
|
||||
extractLibreChatParams,
|
||||
getModelMaxTokens,
|
||||
getThreadData,
|
||||
} from '~/utils';
|
||||
import { optionalChainWithEmptyCheck, extractLibreChatParams, getThreadData } from '~/utils';
|
||||
import { filterFilesByEndpointConfig } from '~/files';
|
||||
import { generateArtifactsPrompt } from '~/prompts';
|
||||
import { getProviderConfig } from '~/endpoints';
|
||||
|
|
|
|||
|
|
@ -1,7 +1,7 @@
|
|||
import { logger } from '@librechat/data-schemas';
|
||||
import type { TCustomConfig, TTransactionsConfig } from 'librechat-data-provider';
|
||||
import type { UsageMetadata } from '../stream/interfaces/IJobStore';
|
||||
import type { EndpointTokenConfig } from '../types/tokens';
|
||||
import type { EndpointTokenConfig } from 'librechat-data-provider';
|
||||
|
||||
interface TokenUsage {
|
||||
promptTokens?: number;
|
||||
|
|
|
|||
|
|
@ -6,8 +6,8 @@ import {
|
|||
anthropicSettings,
|
||||
supportsContext1m,
|
||||
supportsAdaptiveThinking,
|
||||
matchModelName,
|
||||
} from 'librechat-data-provider';
|
||||
import { matchModelName } from '~/utils/tokens';
|
||||
|
||||
/**
|
||||
* @param {string} modelName
|
||||
|
|
|
|||
|
|
@ -5,9 +5,9 @@ import {
|
|||
FetchTokenConfig,
|
||||
extractEnvVariable,
|
||||
} from 'librechat-data-provider';
|
||||
import type { TEndpoint } from 'librechat-data-provider';
|
||||
import type { TEndpoint, EndpointTokenConfig } from 'librechat-data-provider';
|
||||
import type { AppConfig } from '@librechat/data-schemas';
|
||||
import type { BaseInitializeParams, InitializeResultBase, EndpointTokenConfig } from '~/types';
|
||||
import type { BaseInitializeParams, InitializeResultBase } from '~/types';
|
||||
import { getOpenAIConfig } from '~/endpoints/openai/config';
|
||||
import { getCustomEndpointConfig } from '~/app/config';
|
||||
import { fetchModels } from '~/endpoints/models';
|
||||
|
|
|
|||
|
|
@ -1,6 +1,7 @@
|
|||
import type { ClientOptions, OpenAIClientOptions } from '@librechat/agents';
|
||||
import type { TConfig } from 'librechat-data-provider';
|
||||
import type { EndpointTokenConfig, ServerRequest } from '~/types';
|
||||
import type { EndpointTokenConfig } from 'librechat-data-provider';
|
||||
import type { ServerRequest } from '~/types';
|
||||
|
||||
export type TCustomEndpointsConfig = Partial<{ [key: string]: Omit<TConfig, 'order'> }>;
|
||||
|
||||
|
|
|
|||
|
|
@ -12,5 +12,4 @@ export * from './mistral';
|
|||
export type * from './openai';
|
||||
export * from './prompts';
|
||||
export * from './run';
|
||||
export * from './tokens';
|
||||
export * from './stream';
|
||||
|
|
|
|||
|
|
@ -1,17 +0,0 @@
|
|||
/** Configuration object mapping model keys to their respective prompt, completion rates, and context limit
|
||||
*
|
||||
* Note: the [key: string]: unknown is not in the original JSDoc typedef in /api/typedefs.js, but I've included it since
|
||||
* getModelMaxOutputTokens calls getModelTokenValue with a key of 'output', which was not in the original JSDoc typedef,
|
||||
* but would be referenced in a TokenConfig in the if(matchedPattern) portion of getModelTokenValue.
|
||||
* So in order to preserve functionality for that case and any others which might reference an additional key I'm unaware of,
|
||||
* I've included it here until the interface can be typed more tightly.
|
||||
*/
|
||||
export interface TokenConfig {
|
||||
prompt: number;
|
||||
completion: number;
|
||||
context: number;
|
||||
[key: string]: unknown;
|
||||
}
|
||||
|
||||
/** An endpoint's config object mapping model keys to their respective prompt, completion rates, and context limit */
|
||||
export type EndpointTokenConfig = Record<string, TokenConfig>;
|
||||
|
|
@ -1,558 +1,5 @@
|
|||
import z from 'zod';
|
||||
import { EModelEndpoint } from 'librechat-data-provider';
|
||||
import type { EndpointTokenConfig, TokenConfig } from '~/types';
|
||||
|
||||
/**
|
||||
* Model Token Configuration Maps
|
||||
*
|
||||
* IMPORTANT: Key Ordering for Pattern Matching
|
||||
* ============================================
|
||||
* The `findMatchingPattern` function iterates through object keys in REVERSE order
|
||||
* (last-defined keys are checked first) and uses `modelName.includes(key)` for matching.
|
||||
*
|
||||
* This means:
|
||||
* 1. BASE PATTERNS must be defined FIRST (e.g., "kimi", "moonshot")
|
||||
* 2. SPECIFIC PATTERNS must be defined AFTER their base patterns (e.g., "kimi-k2", "kimi-k2.5")
|
||||
*
|
||||
* Example ordering for Kimi models:
|
||||
* kimi: 262144, // Base pattern - checked last
|
||||
* 'kimi-k2': 262144, // More specific - checked before "kimi"
|
||||
* 'kimi-k2.5': 262144, // Most specific - checked first
|
||||
*
|
||||
* Why this matters:
|
||||
* - Model name "kimi-k2.5" contains both "kimi" and "kimi-k2" as substrings
|
||||
* - If "kimi" were checked first, it would incorrectly match "kimi-k2.5"
|
||||
* - By defining specific patterns AFTER base patterns, they're checked first in reverse iteration
|
||||
*
|
||||
* When adding new model families:
|
||||
* 1. Define the base/generic pattern first
|
||||
* 2. Define increasingly specific patterns after
|
||||
* 3. Ensure no pattern is a substring of another that should match differently
|
||||
*/
|
||||
|
||||
const openAIModels = {
|
||||
'o4-mini': 200000,
|
||||
'o3-mini': 195000, // -5000 from max
|
||||
o3: 200000,
|
||||
o1: 195000, // -5000 from max
|
||||
'o1-mini': 127500, // -500 from max
|
||||
'o1-preview': 127500, // -500 from max
|
||||
'gpt-4': 8187, // -5 from max
|
||||
'gpt-4-0613': 8187, // -5 from max
|
||||
'gpt-4-32k': 32758, // -10 from max
|
||||
'gpt-4-32k-0314': 32758, // -10 from max
|
||||
'gpt-4-32k-0613': 32758, // -10 from max
|
||||
'gpt-4-1106': 127500, // -500 from max
|
||||
'gpt-4-0125': 127500, // -500 from max
|
||||
'gpt-4.5': 127500, // -500 from max
|
||||
'gpt-4.1': 1047576,
|
||||
'gpt-4.1-mini': 1047576,
|
||||
'gpt-4.1-nano': 1047576,
|
||||
'gpt-5': 400000,
|
||||
'gpt-5.1': 400000,
|
||||
'gpt-5.2': 400000,
|
||||
'gpt-5-mini': 400000,
|
||||
'gpt-5-nano': 400000,
|
||||
'gpt-5-pro': 400000,
|
||||
'gpt-4o': 127500, // -500 from max
|
||||
'gpt-4o-mini': 127500, // -500 from max
|
||||
'gpt-4o-2024-05-13': 127500, // -500 from max
|
||||
'gpt-4-turbo': 127500, // -500 from max
|
||||
'gpt-4-vision': 127500, // -500 from max
|
||||
'gpt-3.5-turbo': 16375, // -10 from max
|
||||
'gpt-3.5-turbo-0613': 4092, // -5 from max
|
||||
'gpt-3.5-turbo-0301': 4092, // -5 from max
|
||||
'gpt-3.5-turbo-16k': 16375, // -10 from max
|
||||
'gpt-3.5-turbo-16k-0613': 16375, // -10 from max
|
||||
'gpt-3.5-turbo-1106': 16375, // -10 from max
|
||||
'gpt-3.5-turbo-0125': 16375, // -10 from max
|
||||
};
|
||||
|
||||
const mistralModels = {
|
||||
'mistral-': 31990, // -10 from max
|
||||
'mistral-7b': 31990, // -10 from max
|
||||
'mistral-small': 31990, // -10 from max
|
||||
'mixtral-8x7b': 31990, // -10 from max
|
||||
'mixtral-8x22b': 65536,
|
||||
'mistral-large': 131000,
|
||||
'mistral-large-2402': 127500,
|
||||
'mistral-large-2407': 127500,
|
||||
'mistral-nemo': 131000,
|
||||
'pixtral-large': 131000,
|
||||
'mistral-saba': 32000,
|
||||
codestral: 256000,
|
||||
'ministral-8b': 131000,
|
||||
'ministral-3b': 131000,
|
||||
};
|
||||
|
||||
const cohereModels = {
|
||||
'command-light': 4086, // -10 from max
|
||||
'command-light-nightly': 8182, // -10 from max
|
||||
command: 4086, // -10 from max
|
||||
'command-nightly': 8182, // -10 from max
|
||||
'command-text': 4086, // -10 from max
|
||||
'command-r': 127500, // -500 from max
|
||||
'command-r-plus': 127500, // -500 from max
|
||||
};
|
||||
|
||||
const googleModels = {
|
||||
/* Max I/O is combined so we subtract the amount from max response tokens for actual total */
|
||||
gemma: 8196,
|
||||
'gemma-2': 32768,
|
||||
'gemma-3': 32768,
|
||||
'gemma-3-27b': 131072,
|
||||
gemini: 30720, // -2048 from max
|
||||
'gemini-pro-vision': 12288,
|
||||
'gemini-exp': 2000000,
|
||||
'gemini-3': 1000000, // 1M input tokens, 64k output tokens
|
||||
'gemini-3-pro-image': 1000000,
|
||||
'gemini-2.5': 1000000, // 1M input tokens, 64k output tokens
|
||||
'gemini-2.5-pro': 1000000,
|
||||
'gemini-2.5-flash': 1000000,
|
||||
'gemini-2.5-flash-image': 1000000,
|
||||
'gemini-2.5-flash-lite': 1000000,
|
||||
'gemini-2.0': 2000000,
|
||||
'gemini-2.0-flash': 1000000,
|
||||
'gemini-2.0-flash-lite': 1000000,
|
||||
'gemini-1.5': 1000000,
|
||||
'gemini-1.5-flash': 1000000,
|
||||
'gemini-1.5-flash-8b': 1000000,
|
||||
'text-bison-32k': 32758, // -10 from max
|
||||
'chat-bison-32k': 32758, // -10 from max
|
||||
'code-bison-32k': 32758, // -10 from max
|
||||
'codechat-bison-32k': 32758,
|
||||
/* Codey, -5 from max: 6144 */
|
||||
'code-': 6139,
|
||||
'codechat-': 6139,
|
||||
/* PaLM2, -5 from max: 8192 */
|
||||
'text-': 8187,
|
||||
'chat-': 8187,
|
||||
};
|
||||
|
||||
const anthropicModels = {
|
||||
'claude-': 100000,
|
||||
'claude-instant': 100000,
|
||||
'claude-2': 100000,
|
||||
'claude-2.1': 200000,
|
||||
'claude-3': 200000,
|
||||
'claude-3-haiku': 200000,
|
||||
'claude-3-sonnet': 200000,
|
||||
'claude-3-opus': 200000,
|
||||
'claude-3.5-haiku': 200000,
|
||||
'claude-3-5-haiku': 200000,
|
||||
'claude-3-5-sonnet': 200000,
|
||||
'claude-3.5-sonnet': 200000,
|
||||
'claude-3-7-sonnet': 200000,
|
||||
'claude-3.7-sonnet': 200000,
|
||||
'claude-3-5-sonnet-latest': 200000,
|
||||
'claude-3.5-sonnet-latest': 200000,
|
||||
'claude-haiku-4-5': 200000,
|
||||
'claude-sonnet-4': 1000000,
|
||||
'claude-4': 200000,
|
||||
'claude-opus-4': 200000,
|
||||
'claude-opus-4-5': 200000,
|
||||
'claude-opus-4-6': 1000000,
|
||||
};
|
||||
|
||||
const deepseekModels = {
|
||||
deepseek: 128000,
|
||||
'deepseek-chat': 128000,
|
||||
'deepseek-reasoner': 128000,
|
||||
'deepseek-r1': 128000,
|
||||
'deepseek-v3': 128000,
|
||||
'deepseek.r1': 128000,
|
||||
};
|
||||
|
||||
const moonshotModels = {
|
||||
// Base patterns (check last due to reverse iteration)
|
||||
kimi: 262144,
|
||||
moonshot: 131072,
|
||||
// kimi-k2 series (specific patterns)
|
||||
'kimi-latest': 128000,
|
||||
'kimi-k2': 262144,
|
||||
'kimi-k2.5': 262144,
|
||||
'kimi-k2-turbo': 262144,
|
||||
'kimi-k2-turbo-preview': 262144,
|
||||
'kimi-k2-0905': 262144,
|
||||
'kimi-k2-0905-preview': 262144,
|
||||
'kimi-k2-0711': 131072,
|
||||
'kimi-k2-0711-preview': 131072,
|
||||
'kimi-k2-thinking': 262144,
|
||||
'kimi-k2-thinking-turbo': 262144,
|
||||
// moonshot-v1 series (specific patterns)
|
||||
'moonshot-v1': 131072,
|
||||
'moonshot-v1-auto': 131072,
|
||||
'moonshot-v1-8k': 8192,
|
||||
'moonshot-v1-8k-vision': 8192,
|
||||
'moonshot-v1-8k-vision-preview': 8192,
|
||||
'moonshot-v1-32k': 32768,
|
||||
'moonshot-v1-32k-vision': 32768,
|
||||
'moonshot-v1-32k-vision-preview': 32768,
|
||||
'moonshot-v1-128k': 131072,
|
||||
'moonshot-v1-128k-vision': 131072,
|
||||
'moonshot-v1-128k-vision-preview': 131072,
|
||||
// Bedrock moonshot models
|
||||
'moonshot.kimi': 262144,
|
||||
'moonshot.kimi-k2': 262144,
|
||||
'moonshot.kimi-k2.5': 262144,
|
||||
'moonshot.kimi-k2-thinking': 262144,
|
||||
'moonshot.kimi-k2-0711': 131072,
|
||||
};
|
||||
|
||||
const metaModels = {
|
||||
// Basic patterns
|
||||
llama3: 8000,
|
||||
llama2: 4000,
|
||||
'llama-3': 8000,
|
||||
'llama-2': 4000,
|
||||
|
||||
// llama3.x pattern
|
||||
'llama3.1': 127500,
|
||||
'llama3.2': 127500,
|
||||
'llama3.3': 127500,
|
||||
|
||||
// llama3-x pattern
|
||||
'llama3-1': 127500,
|
||||
'llama3-2': 127500,
|
||||
'llama3-3': 127500,
|
||||
|
||||
// llama-3.x pattern
|
||||
'llama-3.1': 127500,
|
||||
'llama-3.2': 127500,
|
||||
'llama-3.3': 127500,
|
||||
|
||||
// llama3.x:Nb pattern
|
||||
'llama3.1:405b': 127500,
|
||||
'llama3.1:70b': 127500,
|
||||
'llama3.1:8b': 127500,
|
||||
'llama3.2:1b': 127500,
|
||||
'llama3.2:3b': 127500,
|
||||
'llama3.2:11b': 127500,
|
||||
'llama3.2:90b': 127500,
|
||||
'llama3.3:70b': 127500,
|
||||
|
||||
// llama3-x-Nb pattern
|
||||
'llama3-1-405b': 127500,
|
||||
'llama3-1-70b': 127500,
|
||||
'llama3-1-8b': 127500,
|
||||
'llama3-2-1b': 127500,
|
||||
'llama3-2-3b': 127500,
|
||||
'llama3-2-11b': 127500,
|
||||
'llama3-2-90b': 127500,
|
||||
'llama3-3-70b': 127500,
|
||||
|
||||
// llama-3.x-Nb pattern
|
||||
'llama-3.1-405b': 127500,
|
||||
'llama-3.1-70b': 127500,
|
||||
'llama-3.1-8b': 127500,
|
||||
'llama-3.2-1b': 127500,
|
||||
'llama-3.2-3b': 127500,
|
||||
'llama-3.2-11b': 127500,
|
||||
'llama-3.2-90b': 127500,
|
||||
'llama-3.3-70b': 127500,
|
||||
|
||||
// Original llama2/3 patterns
|
||||
'llama3-70b': 8000,
|
||||
'llama3-8b': 8000,
|
||||
'llama2-70b': 4000,
|
||||
'llama2-13b': 4000,
|
||||
'llama3:70b': 8000,
|
||||
'llama3:8b': 8000,
|
||||
'llama2:70b': 4000,
|
||||
};
|
||||
|
||||
const qwenModels = {
|
||||
qwen: 32000,
|
||||
'qwen2.5': 32000,
|
||||
'qwen-turbo': 1000000,
|
||||
'qwen-plus': 131000,
|
||||
'qwen-max': 32000,
|
||||
'qwq-32b': 32000,
|
||||
// Qwen3 models
|
||||
qwen3: 40960, // Qwen3 base pattern (using qwen3-4b context)
|
||||
'qwen3-8b': 128000,
|
||||
'qwen3-14b': 40960,
|
||||
'qwen3-30b-a3b': 40960,
|
||||
'qwen3-32b': 40960,
|
||||
'qwen3-235b-a22b': 40960,
|
||||
// Qwen3 VL (Vision-Language) models
|
||||
'qwen3-vl-8b-thinking': 256000,
|
||||
'qwen3-vl-8b-instruct': 262144,
|
||||
'qwen3-vl-30b-a3b': 262144,
|
||||
'qwen3-vl-235b-a22b': 131072,
|
||||
// Qwen3 specialized models
|
||||
'qwen3-max': 256000,
|
||||
'qwen3-coder': 262144,
|
||||
'qwen3-coder-30b-a3b': 262144,
|
||||
'qwen3-coder-plus': 128000,
|
||||
'qwen3-coder-flash': 128000,
|
||||
'qwen3-next-80b-a3b': 262144,
|
||||
};
|
||||
|
||||
const ai21Models = {
|
||||
'j2-mid': 8182, // -10 from max
|
||||
'j2-ultra': 8182, // -10 from max
|
||||
'jamba-instruct': 255500, // -500 from max
|
||||
};
|
||||
|
||||
const amazonModels = {
|
||||
// Amazon Titan models
|
||||
'titan-text-lite': 4000,
|
||||
'titan-text-express': 8000,
|
||||
'titan-text-premier': 31500, // -500 from max
|
||||
// Amazon Nova models
|
||||
// https://aws.amazon.com/ai/generative-ai/nova/
|
||||
'nova-micro': 127000, // -1000 from max
|
||||
'nova-lite': 295000, // -5000 from max
|
||||
'nova-pro': 295000, // -5000 from max
|
||||
'nova-premier': 995000, // -5000 from max
|
||||
};
|
||||
|
||||
const bedrockModels = {
|
||||
...anthropicModels,
|
||||
...mistralModels,
|
||||
...cohereModels,
|
||||
...deepseekModels,
|
||||
...moonshotModels,
|
||||
...metaModels,
|
||||
...ai21Models,
|
||||
...amazonModels,
|
||||
};
|
||||
|
||||
const xAIModels = {
|
||||
grok: 131072,
|
||||
'grok-beta': 131072,
|
||||
'grok-vision-beta': 8192,
|
||||
'grok-2': 131072,
|
||||
'grok-2-latest': 131072,
|
||||
'grok-2-1212': 131072,
|
||||
'grok-2-vision': 32768,
|
||||
'grok-2-vision-latest': 32768,
|
||||
'grok-2-vision-1212': 32768,
|
||||
'grok-3': 131072,
|
||||
'grok-3-fast': 131072,
|
||||
'grok-3-mini': 131072,
|
||||
'grok-3-mini-fast': 131072,
|
||||
'grok-4': 256000, // 256K context
|
||||
'grok-4-fast': 2000000, // 2M context
|
||||
'grok-4-1-fast': 2000000, // 2M context (covers reasoning & non-reasoning variants)
|
||||
'grok-code-fast': 256000, // 256K context
|
||||
};
|
||||
|
||||
const aggregateModels = {
|
||||
...openAIModels,
|
||||
...googleModels,
|
||||
...bedrockModels,
|
||||
...xAIModels,
|
||||
...qwenModels,
|
||||
// GPT-OSS
|
||||
'gpt-oss': 131000,
|
||||
'gpt-oss:20b': 131000,
|
||||
'gpt-oss-20b': 131000,
|
||||
'gpt-oss:120b': 131000,
|
||||
'gpt-oss-120b': 131000,
|
||||
// GLM models (Zhipu AI)
|
||||
glm4: 128000,
|
||||
'glm-4': 128000,
|
||||
'glm-4-32b': 128000,
|
||||
'glm-4.5': 131000,
|
||||
'glm-4.5-air': 131000,
|
||||
'glm-4.5v': 66000,
|
||||
'glm-4.6': 200000,
|
||||
};
|
||||
|
||||
export const maxTokensMap = {
|
||||
[EModelEndpoint.azureOpenAI]: openAIModels,
|
||||
[EModelEndpoint.openAI]: aggregateModels,
|
||||
[EModelEndpoint.agents]: aggregateModels,
|
||||
[EModelEndpoint.custom]: aggregateModels,
|
||||
[EModelEndpoint.google]: googleModels,
|
||||
[EModelEndpoint.anthropic]: anthropicModels,
|
||||
[EModelEndpoint.bedrock]: bedrockModels,
|
||||
};
|
||||
|
||||
export const modelMaxOutputs = {
|
||||
o1: 32268, // -500 from max: 32,768
|
||||
'o1-mini': 65136, // -500 from max: 65,536
|
||||
'o1-preview': 32268, // -500 from max: 32,768
|
||||
'gpt-5': 128000,
|
||||
'gpt-5.1': 128000,
|
||||
'gpt-5.2': 128000,
|
||||
'gpt-5-mini': 128000,
|
||||
'gpt-5-nano': 128000,
|
||||
'gpt-5-pro': 128000,
|
||||
'gpt-oss-20b': 131000,
|
||||
'gpt-oss-120b': 131000,
|
||||
system_default: 32000,
|
||||
};
|
||||
|
||||
/** Outputs from https://docs.anthropic.com/en/docs/about-claude/models/all-models#model-names */
|
||||
const anthropicMaxOutputs = {
|
||||
'claude-3-haiku': 4096,
|
||||
'claude-3-sonnet': 4096,
|
||||
'claude-3-opus': 4096,
|
||||
'claude-haiku-4-5': 64000,
|
||||
'claude-sonnet-4': 64000,
|
||||
'claude-opus-4': 32000,
|
||||
'claude-opus-4-5': 64000,
|
||||
'claude-opus-4-6': 128000,
|
||||
'claude-3.5-sonnet': 8192,
|
||||
'claude-3-5-sonnet': 8192,
|
||||
'claude-3.7-sonnet': 128000,
|
||||
'claude-3-7-sonnet': 128000,
|
||||
};
|
||||
|
||||
/** Outputs from https://api-docs.deepseek.com/quick_start/pricing */
|
||||
const deepseekMaxOutputs = {
|
||||
deepseek: 8000, // deepseek-chat default: 4K, max: 8K
|
||||
'deepseek-chat': 8000,
|
||||
'deepseek-reasoner': 64000, // default: 32K, max: 64K
|
||||
'deepseek-r1': 64000,
|
||||
'deepseek-v3': 8000,
|
||||
'deepseek.r1': 64000,
|
||||
};
|
||||
|
||||
export const maxOutputTokensMap = {
|
||||
[EModelEndpoint.anthropic]: anthropicMaxOutputs,
|
||||
[EModelEndpoint.azureOpenAI]: modelMaxOutputs,
|
||||
[EModelEndpoint.openAI]: { ...modelMaxOutputs, ...deepseekMaxOutputs },
|
||||
[EModelEndpoint.custom]: { ...modelMaxOutputs, ...deepseekMaxOutputs },
|
||||
};
|
||||
|
||||
/**
|
||||
* Finds the first matching pattern in the tokens map.
|
||||
* @param {string} modelName
|
||||
* @param {Record<string, number> | EndpointTokenConfig} tokensMap
|
||||
* @returns {string|null}
|
||||
*/
|
||||
export function findMatchingPattern(
|
||||
modelName: string,
|
||||
tokensMap: Record<string, number> | EndpointTokenConfig,
|
||||
): string | null {
|
||||
const keys = Object.keys(tokensMap);
|
||||
const lowerModelName = modelName.toLowerCase();
|
||||
for (let i = keys.length - 1; i >= 0; i--) {
|
||||
const modelKey = keys[i];
|
||||
if (lowerModelName.includes(modelKey)) {
|
||||
return modelKey;
|
||||
}
|
||||
}
|
||||
|
||||
return null;
|
||||
}
|
||||
|
||||
/**
|
||||
* Retrieves a token value for a given model name from a tokens map.
|
||||
*
|
||||
* @param modelName - The name of the model to look up.
|
||||
* @param tokensMap - The map of model names to token values.
|
||||
* @param [key='context'] - The key to look up in the tokens map.
|
||||
* @returns The token value for the given model or undefined if no match is found.
|
||||
*/
|
||||
export function getModelTokenValue(
|
||||
modelName: string,
|
||||
tokensMap?: EndpointTokenConfig | Record<string, number>,
|
||||
key = 'context' as keyof TokenConfig,
|
||||
): number | undefined {
|
||||
if (typeof modelName !== 'string' || !tokensMap) {
|
||||
return undefined;
|
||||
}
|
||||
|
||||
const value = tokensMap[modelName];
|
||||
if (typeof value === 'number') {
|
||||
return value;
|
||||
}
|
||||
|
||||
if (value?.context) {
|
||||
return value.context;
|
||||
}
|
||||
|
||||
const matchedPattern = findMatchingPattern(modelName, tokensMap);
|
||||
|
||||
if (matchedPattern) {
|
||||
const result = tokensMap[matchedPattern];
|
||||
if (typeof result === 'number') {
|
||||
return result;
|
||||
}
|
||||
|
||||
const tokenValue = result?.[key];
|
||||
if (typeof tokenValue === 'number') {
|
||||
return tokenValue;
|
||||
}
|
||||
return tokensMap.system_default as number | undefined;
|
||||
}
|
||||
|
||||
return tokensMap.system_default as number | undefined;
|
||||
}
|
||||
|
||||
/**
|
||||
* Retrieves the maximum tokens for a given model name.
|
||||
*
|
||||
* @param modelName - The name of the model to look up.
|
||||
* @param endpoint - The endpoint (default is 'openAI').
|
||||
* @param [endpointTokenConfig] - Token Config for current endpoint to use for max tokens lookup
|
||||
* @returns The maximum tokens for the given model or undefined if no match is found.
|
||||
*/
|
||||
export function getModelMaxTokens(
|
||||
modelName: string,
|
||||
endpoint = EModelEndpoint.openAI,
|
||||
endpointTokenConfig?: EndpointTokenConfig,
|
||||
): number | undefined {
|
||||
const tokensMap = endpointTokenConfig ?? maxTokensMap[endpoint as keyof typeof maxTokensMap];
|
||||
return getModelTokenValue(modelName, tokensMap);
|
||||
}
|
||||
|
||||
/**
|
||||
* Retrieves the maximum output tokens for a given model name.
|
||||
*
|
||||
* @param modelName - The name of the model to look up.
|
||||
* @param endpoint - The endpoint (default is 'openAI').
|
||||
* @param [endpointTokenConfig] - Token Config for current endpoint to use for max tokens lookup
|
||||
* @returns The maximum output tokens for the given model or undefined if no match is found.
|
||||
*/
|
||||
export function getModelMaxOutputTokens(
|
||||
modelName: string,
|
||||
endpoint = EModelEndpoint.openAI,
|
||||
endpointTokenConfig?: EndpointTokenConfig,
|
||||
): number | undefined {
|
||||
const tokensMap =
|
||||
endpointTokenConfig ?? maxOutputTokensMap[endpoint as keyof typeof maxOutputTokensMap];
|
||||
return getModelTokenValue(modelName, tokensMap, 'output');
|
||||
}
|
||||
|
||||
/**
|
||||
* Retrieves the model name key for a given model name input. If the exact model name isn't found,
|
||||
* it searches for partial matches within the model name, checking keys in reverse order.
|
||||
*
|
||||
* @param modelName - The name of the model to look up.
|
||||
* @param endpoint - The endpoint (default is 'openAI').
|
||||
* @returns The model name key for the given model; returns input if no match is found and is string.
|
||||
*
|
||||
* @example
|
||||
* matchModelName('gpt-4-32k-0613'); // Returns 'gpt-4-32k-0613'
|
||||
* matchModelName('gpt-4-32k-unknown'); // Returns 'gpt-4-32k'
|
||||
* matchModelName('unknown-model'); // Returns undefined
|
||||
*/
|
||||
export function matchModelName(
|
||||
modelName: string,
|
||||
endpoint = EModelEndpoint.openAI,
|
||||
): string | undefined {
|
||||
if (typeof modelName !== 'string') {
|
||||
return undefined;
|
||||
}
|
||||
|
||||
const tokensMap: Record<string, number> = maxTokensMap[endpoint as keyof typeof maxTokensMap];
|
||||
if (!tokensMap) {
|
||||
return modelName;
|
||||
}
|
||||
|
||||
if (tokensMap[modelName]) {
|
||||
return modelName;
|
||||
}
|
||||
|
||||
const matchedPattern = findMatchingPattern(modelName, tokensMap);
|
||||
return matchedPattern || modelName;
|
||||
}
|
||||
import type { EndpointTokenConfig } from 'librechat-data-provider';
|
||||
|
||||
export const modelSchema = z.object({
|
||||
id: z.string(),
|
||||
|
|
|
|||
|
|
@ -40,6 +40,8 @@ export { dataService };
|
|||
import * as dataService from './data-service';
|
||||
/* general helpers */
|
||||
export * from './utils';
|
||||
/* tokens */
|
||||
export * from './tokens';
|
||||
export * from './actions';
|
||||
export { default as createPayload } from './createPayload';
|
||||
// /* react query hooks */
|
||||
|
|
|
|||
564
packages/data-provider/src/tokens.ts
Normal file
564
packages/data-provider/src/tokens.ts
Normal file
|
|
@ -0,0 +1,564 @@
|
|||
import { EModelEndpoint } from './schemas';
|
||||
|
||||
/** Configuration object mapping model keys to their respective prompt, completion rates, and context limit */
|
||||
export interface TokenConfig {
|
||||
prompt: number;
|
||||
completion: number;
|
||||
context: number;
|
||||
[key: string]: unknown;
|
||||
}
|
||||
|
||||
/** An endpoint's config object mapping model keys to their respective prompt, completion rates, and context limit */
|
||||
export type EndpointTokenConfig = Record<string, TokenConfig>;
|
||||
|
||||
/**
|
||||
* Model Token Configuration Maps
|
||||
*
|
||||
* IMPORTANT: Key Ordering for Pattern Matching
|
||||
* ============================================
|
||||
* The `findMatchingPattern` function iterates through object keys in REVERSE order
|
||||
* (last-defined keys are checked first) and uses `modelName.includes(key)` for matching.
|
||||
*
|
||||
* This means:
|
||||
* 1. BASE PATTERNS must be defined FIRST (e.g., "kimi", "moonshot")
|
||||
* 2. SPECIFIC PATTERNS must be defined AFTER their base patterns (e.g., "kimi-k2", "kimi-k2.5")
|
||||
*
|
||||
* Example ordering for Kimi models:
|
||||
* kimi: 262144, // Base pattern - checked last
|
||||
* 'kimi-k2': 262144, // More specific - checked before "kimi"
|
||||
* 'kimi-k2.5': 262144, // Most specific - checked first
|
||||
*
|
||||
* Why this matters:
|
||||
* - Model name "kimi-k2.5" contains both "kimi" and "kimi-k2" as substrings
|
||||
* - If "kimi" were checked first, it would incorrectly match "kimi-k2.5"
|
||||
* - By defining specific patterns AFTER base patterns, they're checked first in reverse iteration
|
||||
*
|
||||
* When adding new model families:
|
||||
* 1. Define the base/generic pattern first
|
||||
* 2. Define increasingly specific patterns after
|
||||
* 3. Ensure no pattern is a substring of another that should match differently
|
||||
*/
|
||||
|
||||
const openAIModels = {
|
||||
'o4-mini': 200000,
|
||||
'o3-mini': 195000, // -5000 from max
|
||||
o3: 200000,
|
||||
o1: 195000, // -5000 from max
|
||||
'o1-mini': 127500, // -500 from max
|
||||
'o1-preview': 127500, // -500 from max
|
||||
'gpt-4': 8187, // -5 from max
|
||||
'gpt-4-0613': 8187, // -5 from max
|
||||
'gpt-4-32k': 32758, // -10 from max
|
||||
'gpt-4-32k-0314': 32758, // -10 from max
|
||||
'gpt-4-32k-0613': 32758, // -10 from max
|
||||
'gpt-4-1106': 127500, // -500 from max
|
||||
'gpt-4-0125': 127500, // -500 from max
|
||||
'gpt-4.5': 127500, // -500 from max
|
||||
'gpt-4.1': 1047576,
|
||||
'gpt-4.1-mini': 1047576,
|
||||
'gpt-4.1-nano': 1047576,
|
||||
'gpt-5': 400000,
|
||||
'gpt-5.1': 400000,
|
||||
'gpt-5.2': 400000,
|
||||
'gpt-5-mini': 400000,
|
||||
'gpt-5-nano': 400000,
|
||||
'gpt-5-pro': 400000,
|
||||
'gpt-4o': 127500, // -500 from max
|
||||
'gpt-4o-mini': 127500, // -500 from max
|
||||
'gpt-4o-2024-05-13': 127500, // -500 from max
|
||||
'gpt-4-turbo': 127500, // -500 from max
|
||||
'gpt-4-vision': 127500, // -500 from max
|
||||
'gpt-3.5-turbo': 16375, // -10 from max
|
||||
'gpt-3.5-turbo-0613': 4092, // -5 from max
|
||||
'gpt-3.5-turbo-0301': 4092, // -5 from max
|
||||
'gpt-3.5-turbo-16k': 16375, // -10 from max
|
||||
'gpt-3.5-turbo-16k-0613': 16375, // -10 from max
|
||||
'gpt-3.5-turbo-1106': 16375, // -10 from max
|
||||
'gpt-3.5-turbo-0125': 16375, // -10 from max
|
||||
};
|
||||
|
||||
const mistralModels = {
|
||||
'mistral-': 31990, // -10 from max
|
||||
'mistral-7b': 31990, // -10 from max
|
||||
'mistral-small': 31990, // -10 from max
|
||||
'mixtral-8x7b': 31990, // -10 from max
|
||||
'mixtral-8x22b': 65536,
|
||||
'mistral-large': 131000,
|
||||
'mistral-large-2402': 127500,
|
||||
'mistral-large-2407': 127500,
|
||||
'mistral-nemo': 131000,
|
||||
'pixtral-large': 131000,
|
||||
'mistral-saba': 32000,
|
||||
codestral: 256000,
|
||||
'ministral-8b': 131000,
|
||||
'ministral-3b': 131000,
|
||||
};
|
||||
|
||||
const cohereModels = {
|
||||
'command-light': 4086, // -10 from max
|
||||
'command-light-nightly': 8182, // -10 from max
|
||||
command: 4086, // -10 from max
|
||||
'command-nightly': 8182, // -10 from max
|
||||
'command-text': 4086, // -10 from max
|
||||
'command-r': 127500, // -500 from max
|
||||
'command-r-plus': 127500, // -500 from max
|
||||
};
|
||||
|
||||
const googleModels = {
|
||||
/* Max I/O is combined so we subtract the amount from max response tokens for actual total */
|
||||
gemma: 8196,
|
||||
'gemma-2': 32768,
|
||||
'gemma-3': 32768,
|
||||
'gemma-3-27b': 131072,
|
||||
gemini: 30720, // -2048 from max
|
||||
'gemini-pro-vision': 12288,
|
||||
'gemini-exp': 2000000,
|
||||
'gemini-3': 1000000, // 1M input tokens, 64k output tokens
|
||||
'gemini-3-pro-image': 1000000,
|
||||
'gemini-2.5': 1000000, // 1M input tokens, 64k output tokens
|
||||
'gemini-2.5-pro': 1000000,
|
||||
'gemini-2.5-flash': 1000000,
|
||||
'gemini-2.5-flash-image': 1000000,
|
||||
'gemini-2.5-flash-lite': 1000000,
|
||||
'gemini-2.0': 2000000,
|
||||
'gemini-2.0-flash': 1000000,
|
||||
'gemini-2.0-flash-lite': 1000000,
|
||||
'gemini-1.5': 1000000,
|
||||
'gemini-1.5-flash': 1000000,
|
||||
'gemini-1.5-flash-8b': 1000000,
|
||||
'text-bison-32k': 32758, // -10 from max
|
||||
'chat-bison-32k': 32758, // -10 from max
|
||||
'code-bison-32k': 32758, // -10 from max
|
||||
'codechat-bison-32k': 32758,
|
||||
/* Codey, -5 from max: 6144 */
|
||||
'code-': 6139,
|
||||
'codechat-': 6139,
|
||||
/* PaLM2, -5 from max: 8192 */
|
||||
'text-': 8187,
|
||||
'chat-': 8187,
|
||||
};
|
||||
|
||||
const anthropicModels = {
|
||||
'claude-': 100000,
|
||||
'claude-instant': 100000,
|
||||
'claude-2': 100000,
|
||||
'claude-2.1': 200000,
|
||||
'claude-3': 200000,
|
||||
'claude-3-haiku': 200000,
|
||||
'claude-3-sonnet': 200000,
|
||||
'claude-3-opus': 200000,
|
||||
'claude-3.5-haiku': 200000,
|
||||
'claude-3-5-haiku': 200000,
|
||||
'claude-3-5-sonnet': 200000,
|
||||
'claude-3.5-sonnet': 200000,
|
||||
'claude-3-7-sonnet': 200000,
|
||||
'claude-3.7-sonnet': 200000,
|
||||
'claude-3-5-sonnet-latest': 200000,
|
||||
'claude-3.5-sonnet-latest': 200000,
|
||||
'claude-haiku-4-5': 200000,
|
||||
'claude-sonnet-4': 1000000,
|
||||
'claude-4': 200000,
|
||||
'claude-opus-4': 200000,
|
||||
'claude-opus-4-5': 200000,
|
||||
'claude-opus-4-6': 1000000,
|
||||
};
|
||||
|
||||
const deepseekModels = {
|
||||
deepseek: 128000,
|
||||
'deepseek-chat': 128000,
|
||||
'deepseek-reasoner': 128000,
|
||||
'deepseek-r1': 128000,
|
||||
'deepseek-v3': 128000,
|
||||
'deepseek.r1': 128000,
|
||||
};
|
||||
|
||||
const moonshotModels = {
|
||||
// Base patterns (check last due to reverse iteration)
|
||||
kimi: 262144,
|
||||
moonshot: 131072,
|
||||
// kimi-k2 series (specific patterns)
|
||||
'kimi-latest': 128000,
|
||||
'kimi-k2': 262144,
|
||||
'kimi-k2.5': 262144,
|
||||
'kimi-k2-turbo': 262144,
|
||||
'kimi-k2-turbo-preview': 262144,
|
||||
'kimi-k2-0905': 262144,
|
||||
'kimi-k2-0905-preview': 262144,
|
||||
'kimi-k2-0711': 131072,
|
||||
'kimi-k2-0711-preview': 131072,
|
||||
'kimi-k2-thinking': 262144,
|
||||
'kimi-k2-thinking-turbo': 262144,
|
||||
// moonshot-v1 series (specific patterns)
|
||||
'moonshot-v1': 131072,
|
||||
'moonshot-v1-auto': 131072,
|
||||
'moonshot-v1-8k': 8192,
|
||||
'moonshot-v1-8k-vision': 8192,
|
||||
'moonshot-v1-8k-vision-preview': 8192,
|
||||
'moonshot-v1-32k': 32768,
|
||||
'moonshot-v1-32k-vision': 32768,
|
||||
'moonshot-v1-32k-vision-preview': 32768,
|
||||
'moonshot-v1-128k': 131072,
|
||||
'moonshot-v1-128k-vision': 131072,
|
||||
'moonshot-v1-128k-vision-preview': 131072,
|
||||
// Bedrock moonshot models
|
||||
'moonshot.kimi': 262144,
|
||||
'moonshot.kimi-k2': 262144,
|
||||
'moonshot.kimi-k2.5': 262144,
|
||||
'moonshot.kimi-k2-thinking': 262144,
|
||||
'moonshot.kimi-k2-0711': 131072,
|
||||
};
|
||||
|
||||
const metaModels = {
|
||||
// Basic patterns
|
||||
llama3: 8000,
|
||||
llama2: 4000,
|
||||
'llama-3': 8000,
|
||||
'llama-2': 4000,
|
||||
|
||||
// llama3.x pattern
|
||||
'llama3.1': 127500,
|
||||
'llama3.2': 127500,
|
||||
'llama3.3': 127500,
|
||||
|
||||
// llama3-x pattern
|
||||
'llama3-1': 127500,
|
||||
'llama3-2': 127500,
|
||||
'llama3-3': 127500,
|
||||
|
||||
// llama-3.x pattern
|
||||
'llama-3.1': 127500,
|
||||
'llama-3.2': 127500,
|
||||
'llama-3.3': 127500,
|
||||
|
||||
// llama3.x:Nb pattern
|
||||
'llama3.1:405b': 127500,
|
||||
'llama3.1:70b': 127500,
|
||||
'llama3.1:8b': 127500,
|
||||
'llama3.2:1b': 127500,
|
||||
'llama3.2:3b': 127500,
|
||||
'llama3.2:11b': 127500,
|
||||
'llama3.2:90b': 127500,
|
||||
'llama3.3:70b': 127500,
|
||||
|
||||
// llama3-x-Nb pattern
|
||||
'llama3-1-405b': 127500,
|
||||
'llama3-1-70b': 127500,
|
||||
'llama3-1-8b': 127500,
|
||||
'llama3-2-1b': 127500,
|
||||
'llama3-2-3b': 127500,
|
||||
'llama3-2-11b': 127500,
|
||||
'llama3-2-90b': 127500,
|
||||
'llama3-3-70b': 127500,
|
||||
|
||||
// llama-3.x-Nb pattern
|
||||
'llama-3.1-405b': 127500,
|
||||
'llama-3.1-70b': 127500,
|
||||
'llama-3.1-8b': 127500,
|
||||
'llama-3.2-1b': 127500,
|
||||
'llama-3.2-3b': 127500,
|
||||
'llama-3.2-11b': 127500,
|
||||
'llama-3.2-90b': 127500,
|
||||
'llama-3.3-70b': 127500,
|
||||
|
||||
// Original llama2/3 patterns
|
||||
'llama3-70b': 8000,
|
||||
'llama3-8b': 8000,
|
||||
'llama2-70b': 4000,
|
||||
'llama2-13b': 4000,
|
||||
'llama3:70b': 8000,
|
||||
'llama3:8b': 8000,
|
||||
'llama2:70b': 4000,
|
||||
};
|
||||
|
||||
const qwenModels = {
|
||||
qwen: 32000,
|
||||
'qwen2.5': 32000,
|
||||
'qwen-turbo': 1000000,
|
||||
'qwen-plus': 131000,
|
||||
'qwen-max': 32000,
|
||||
'qwq-32b': 32000,
|
||||
// Qwen3 models
|
||||
qwen3: 40960, // Qwen3 base pattern (using qwen3-4b context)
|
||||
'qwen3-8b': 128000,
|
||||
'qwen3-14b': 40960,
|
||||
'qwen3-30b-a3b': 40960,
|
||||
'qwen3-32b': 40960,
|
||||
'qwen3-235b-a22b': 40960,
|
||||
// Qwen3 VL (Vision-Language) models
|
||||
'qwen3-vl-8b-thinking': 256000,
|
||||
'qwen3-vl-8b-instruct': 262144,
|
||||
'qwen3-vl-30b-a3b': 262144,
|
||||
'qwen3-vl-235b-a22b': 131072,
|
||||
// Qwen3 specialized models
|
||||
'qwen3-max': 256000,
|
||||
'qwen3-coder': 262144,
|
||||
'qwen3-coder-30b-a3b': 262144,
|
||||
'qwen3-coder-plus': 128000,
|
||||
'qwen3-coder-flash': 128000,
|
||||
'qwen3-next-80b-a3b': 262144,
|
||||
};
|
||||
|
||||
const ai21Models = {
|
||||
'j2-mid': 8182, // -10 from max
|
||||
'j2-ultra': 8182, // -10 from max
|
||||
'jamba-instruct': 255500, // -500 from max
|
||||
};
|
||||
|
||||
const amazonModels = {
|
||||
// Amazon Titan models
|
||||
'titan-text-lite': 4000,
|
||||
'titan-text-express': 8000,
|
||||
'titan-text-premier': 31500, // -500 from max
|
||||
// Amazon Nova models
|
||||
// https://aws.amazon.com/ai/generative-ai/nova/
|
||||
'nova-micro': 127000, // -1000 from max
|
||||
'nova-lite': 295000, // -5000 from max
|
||||
'nova-pro': 295000, // -5000 from max
|
||||
'nova-premier': 995000, // -5000 from max
|
||||
};
|
||||
|
||||
const bedrockModels = {
|
||||
...anthropicModels,
|
||||
...mistralModels,
|
||||
...cohereModels,
|
||||
...deepseekModels,
|
||||
...moonshotModels,
|
||||
...metaModels,
|
||||
...ai21Models,
|
||||
...amazonModels,
|
||||
};
|
||||
|
||||
const xAIModels = {
|
||||
grok: 131072,
|
||||
'grok-beta': 131072,
|
||||
'grok-vision-beta': 8192,
|
||||
'grok-2': 131072,
|
||||
'grok-2-latest': 131072,
|
||||
'grok-2-1212': 131072,
|
||||
'grok-2-vision': 32768,
|
||||
'grok-2-vision-latest': 32768,
|
||||
'grok-2-vision-1212': 32768,
|
||||
'grok-3': 131072,
|
||||
'grok-3-fast': 131072,
|
||||
'grok-3-mini': 131072,
|
||||
'grok-3-mini-fast': 131072,
|
||||
'grok-4': 256000, // 256K context
|
||||
'grok-4-fast': 2000000, // 2M context
|
||||
'grok-4-1-fast': 2000000, // 2M context (covers reasoning & non-reasoning variants)
|
||||
'grok-code-fast': 256000, // 256K context
|
||||
};
|
||||
|
||||
const aggregateModels = {
|
||||
...openAIModels,
|
||||
...googleModels,
|
||||
...bedrockModels,
|
||||
...xAIModels,
|
||||
...qwenModels,
|
||||
// GPT-OSS
|
||||
'gpt-oss': 131000,
|
||||
'gpt-oss:20b': 131000,
|
||||
'gpt-oss-20b': 131000,
|
||||
'gpt-oss:120b': 131000,
|
||||
'gpt-oss-120b': 131000,
|
||||
// GLM models (Zhipu AI)
|
||||
glm4: 128000,
|
||||
'glm-4': 128000,
|
||||
'glm-4-32b': 128000,
|
||||
'glm-4.5': 131000,
|
||||
'glm-4.5-air': 131000,
|
||||
'glm-4.5v': 66000,
|
||||
'glm-4.6': 200000,
|
||||
};
|
||||
|
||||
export const maxTokensMap = {
|
||||
[EModelEndpoint.azureOpenAI]: openAIModels,
|
||||
[EModelEndpoint.openAI]: aggregateModels,
|
||||
[EModelEndpoint.agents]: aggregateModels,
|
||||
[EModelEndpoint.custom]: aggregateModels,
|
||||
[EModelEndpoint.google]: googleModels,
|
||||
[EModelEndpoint.anthropic]: anthropicModels,
|
||||
[EModelEndpoint.bedrock]: bedrockModels,
|
||||
};
|
||||
|
||||
export const modelMaxOutputs = {
|
||||
o1: 32268, // -500 from max: 32,768
|
||||
'o1-mini': 65136, // -500 from max: 65,536
|
||||
'o1-preview': 32268, // -500 from max: 32,768
|
||||
'gpt-5': 128000,
|
||||
'gpt-5.1': 128000,
|
||||
'gpt-5.2': 128000,
|
||||
'gpt-5-mini': 128000,
|
||||
'gpt-5-nano': 128000,
|
||||
'gpt-5-pro': 128000,
|
||||
'gpt-oss-20b': 131000,
|
||||
'gpt-oss-120b': 131000,
|
||||
system_default: 32000,
|
||||
};
|
||||
|
||||
/** Outputs from https://docs.anthropic.com/en/docs/about-claude/models/all-models#model-names */
|
||||
const anthropicMaxOutputs = {
|
||||
'claude-3-haiku': 4096,
|
||||
'claude-3-sonnet': 4096,
|
||||
'claude-3-opus': 4096,
|
||||
'claude-haiku-4-5': 64000,
|
||||
'claude-sonnet-4': 64000,
|
||||
'claude-opus-4': 32000,
|
||||
'claude-opus-4-5': 64000,
|
||||
'claude-opus-4-6': 128000,
|
||||
'claude-3.5-sonnet': 8192,
|
||||
'claude-3-5-sonnet': 8192,
|
||||
'claude-3.7-sonnet': 128000,
|
||||
'claude-3-7-sonnet': 128000,
|
||||
};
|
||||
|
||||
/** Outputs from https://api-docs.deepseek.com/quick_start/pricing */
|
||||
const deepseekMaxOutputs = {
|
||||
deepseek: 8000, // deepseek-chat default: 4K, max: 8K
|
||||
'deepseek-chat': 8000,
|
||||
'deepseek-reasoner': 64000, // default: 32K, max: 64K
|
||||
'deepseek-r1': 64000,
|
||||
'deepseek-v3': 8000,
|
||||
'deepseek.r1': 64000,
|
||||
};
|
||||
|
||||
export const maxOutputTokensMap = {
|
||||
[EModelEndpoint.anthropic]: anthropicMaxOutputs,
|
||||
[EModelEndpoint.azureOpenAI]: modelMaxOutputs,
|
||||
[EModelEndpoint.openAI]: { ...modelMaxOutputs, ...deepseekMaxOutputs },
|
||||
[EModelEndpoint.custom]: { ...modelMaxOutputs, ...deepseekMaxOutputs },
|
||||
};
|
||||
|
||||
/**
|
||||
* Finds the first matching pattern in the tokens map.
|
||||
* @param {string} modelName
|
||||
* @param {Record<string, number> | EndpointTokenConfig} tokensMap
|
||||
* @returns {string|null}
|
||||
*/
|
||||
export function findMatchingPattern(
|
||||
modelName: string,
|
||||
tokensMap: Record<string, number> | EndpointTokenConfig,
|
||||
): string | null {
|
||||
const keys = Object.keys(tokensMap);
|
||||
const lowerModelName = modelName.toLowerCase();
|
||||
for (let i = keys.length - 1; i >= 0; i--) {
|
||||
const modelKey = keys[i];
|
||||
if (lowerModelName.includes(modelKey)) {
|
||||
return modelKey;
|
||||
}
|
||||
}
|
||||
|
||||
return null;
|
||||
}
|
||||
|
||||
/**
|
||||
* Retrieves a token value for a given model name from a tokens map.
|
||||
*
|
||||
* @param modelName - The name of the model to look up.
|
||||
* @param tokensMap - The map of model names to token values.
|
||||
* @param [key='context'] - The key to look up in the tokens map.
|
||||
* @returns The token value for the given model or undefined if no match is found.
|
||||
*/
|
||||
export function getModelTokenValue(
|
||||
modelName: string,
|
||||
tokensMap?: EndpointTokenConfig | Record<string, number>,
|
||||
key = 'context' as keyof TokenConfig,
|
||||
): number | undefined {
|
||||
if (typeof modelName !== 'string' || !tokensMap) {
|
||||
return undefined;
|
||||
}
|
||||
|
||||
const value = tokensMap[modelName];
|
||||
if (typeof value === 'number') {
|
||||
return value;
|
||||
}
|
||||
|
||||
if (value?.context) {
|
||||
return value.context;
|
||||
}
|
||||
|
||||
const matchedPattern = findMatchingPattern(modelName, tokensMap);
|
||||
|
||||
if (matchedPattern) {
|
||||
const result = tokensMap[matchedPattern];
|
||||
if (typeof result === 'number') {
|
||||
return result;
|
||||
}
|
||||
|
||||
const tokenValue = result?.[key];
|
||||
if (typeof tokenValue === 'number') {
|
||||
return tokenValue;
|
||||
}
|
||||
return tokensMap.system_default as number | undefined;
|
||||
}
|
||||
|
||||
return tokensMap.system_default as number | undefined;
|
||||
}
|
||||
|
||||
/**
|
||||
* Retrieves the maximum tokens for a given model name.
|
||||
*
|
||||
* @param modelName - The name of the model to look up.
|
||||
* @param endpoint - The endpoint (default is 'openAI').
|
||||
* @param [endpointTokenConfig] - Token Config for current endpoint to use for max tokens lookup
|
||||
* @returns The maximum tokens for the given model or undefined if no match is found.
|
||||
*/
|
||||
export function getModelMaxTokens(
|
||||
modelName: string,
|
||||
endpoint = EModelEndpoint.openAI,
|
||||
endpointTokenConfig?: EndpointTokenConfig,
|
||||
): number | undefined {
|
||||
const tokensMap = endpointTokenConfig ?? maxTokensMap[endpoint as keyof typeof maxTokensMap];
|
||||
return getModelTokenValue(modelName, tokensMap);
|
||||
}
|
||||
|
||||
/**
|
||||
* Retrieves the maximum output tokens for a given model name.
|
||||
*
|
||||
* @param modelName - The name of the model to look up.
|
||||
* @param endpoint - The endpoint (default is 'openAI').
|
||||
* @param [endpointTokenConfig] - Token Config for current endpoint to use for max tokens lookup
|
||||
* @returns The maximum output tokens for the given model or undefined if no match is found.
|
||||
*/
|
||||
export function getModelMaxOutputTokens(
|
||||
modelName: string,
|
||||
endpoint = EModelEndpoint.openAI,
|
||||
endpointTokenConfig?: EndpointTokenConfig,
|
||||
): number | undefined {
|
||||
const tokensMap =
|
||||
endpointTokenConfig ?? maxOutputTokensMap[endpoint as keyof typeof maxOutputTokensMap];
|
||||
return getModelTokenValue(modelName, tokensMap, 'output');
|
||||
}
|
||||
|
||||
/**
|
||||
* Retrieves the model name key for a given model name input. If the exact model name isn't found,
|
||||
* it searches for partial matches within the model name, checking keys in reverse order.
|
||||
*
|
||||
* @param modelName - The name of the model to look up.
|
||||
* @param endpoint - The endpoint (default is 'openAI').
|
||||
* @returns The model name key for the given model; returns input if no match is found and is string.
|
||||
*
|
||||
* @example
|
||||
* matchModelName('gpt-4-32k-0613'); // Returns 'gpt-4-32k-0613'
|
||||
* matchModelName('gpt-4-32k-unknown'); // Returns 'gpt-4-32k'
|
||||
* matchModelName('unknown-model'); // Returns undefined
|
||||
*/
|
||||
export function matchModelName(
|
||||
modelName: string,
|
||||
endpoint = EModelEndpoint.openAI,
|
||||
): string | undefined {
|
||||
if (typeof modelName !== 'string') {
|
||||
return undefined;
|
||||
}
|
||||
|
||||
const tokensMap: Record<string, number> = maxTokensMap[endpoint as keyof typeof maxTokensMap];
|
||||
if (!tokensMap) {
|
||||
return modelName;
|
||||
}
|
||||
|
||||
if (tokensMap[modelName]) {
|
||||
return modelName;
|
||||
}
|
||||
|
||||
const matchedPattern = findMatchingPattern(modelName, tokensMap);
|
||||
return matchedPattern || modelName;
|
||||
}
|
||||
Loading…
Add table
Add a link
Reference in a new issue