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LibreChat/api/models/tx.js
Danny Avila f34052c6bb
🌙 feat: Moonshot Provider Support (#11621) 
* ✨ feat: Add Moonshot Provider Support

- Updated the `isKnownCustomProvider` function to include `Providers.MOONSHOT` in the list of recognized custom providers.
- Enhanced the `providerConfigMap` to initialize `MOONSHOT` with the custom initialization function.
- Introduced `MoonshotIcon` component for visual representation in the UI, integrated into the `UnknownIcon` component.
- Updated various files across the API and client to support the new `MOONSHOT` provider, including configuration and response handling.

This update expands the capabilities of the application by integrating support for the Moonshot provider, enhancing both backend and frontend functionalities.

* ✨ feat: Add Moonshot/Kimi Model Pricing and Tests

- Introduced new pricing configurations for Moonshot and Kimi models in `tx.js`, including various model variations and their respective prompt and completion values.
- Expanded unit tests in `tx.spec.js` and `tokens.spec.js` to validate pricing and token limits for the newly added Moonshot/Kimi models, ensuring accurate calculations and handling of model variations.
- Updated utility functions to support the new model structures and ensure compatibility with existing functionalities.

This update enhances the pricing model capabilities and improves test coverage for the Moonshot/Kimi integration.

* ✨ feat: Enhance Token Pricing Documentation and Configuration

- Added comprehensive documentation for token pricing configuration in `tx.js` and `tokens.ts`, emphasizing the importance of key ordering for pattern matching.
- Clarified the process for defining base and specific patterns to ensure accurate pricing retrieval based on model names.
- Improved code comments to guide future additions of model families, enhancing maintainability and understanding of the pricing structure.

This update improves the clarity and usability of the token pricing configuration, facilitating better integration and future enhancements.

* chore: import order

* chore: linting
2026-02-04 10:53:57 +01:00

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const { matchModelName, findMatchingPattern } = require('@librechat/api');
const defaultRate = 6;
/**
* Token Pricing Configuration
*
* 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: { prompt: 0.6, completion: 2.5 }, // Base pattern - checked last
* 'kimi-k2': { prompt: 0.6, completion: 2.5 }, // More specific - checked before "kimi"
* 'kimi-k2.5': { prompt: 0.6, completion: 3.0 }, // 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 and return wrong pricing
* - By defining specific patterns AFTER base patterns, they're checked first in reverse iteration
*
* This applies to BOTH `tokenValues` and `cacheTokenValues` objects.
*
* 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
*/
/**
* AWS Bedrock pricing
* source: https://aws.amazon.com/bedrock/pricing/
*/
const bedrockValues = {
// Basic llama2 patterns (base defaults to smallest variant)
llama2: { prompt: 0.75, completion: 1.0 },
'llama-2': { prompt: 0.75, completion: 1.0 },
'llama2-13b': { prompt: 0.75, completion: 1.0 },
'llama2:70b': { prompt: 1.95, completion: 2.56 },
'llama2-70b': { prompt: 1.95, completion: 2.56 },
// Basic llama3 patterns (base defaults to smallest variant)
llama3: { prompt: 0.3, completion: 0.6 },
'llama-3': { prompt: 0.3, completion: 0.6 },
'llama3-8b': { prompt: 0.3, completion: 0.6 },
'llama3:8b': { prompt: 0.3, completion: 0.6 },
'llama3-70b': { prompt: 2.65, completion: 3.5 },
'llama3:70b': { prompt: 2.65, completion: 3.5 },
// llama3-x-Nb pattern (base defaults to smallest variant)
'llama3-1': { prompt: 0.22, completion: 0.22 },
'llama3-1-8b': { prompt: 0.22, completion: 0.22 },
'llama3-1-70b': { prompt: 0.72, completion: 0.72 },
'llama3-1-405b': { prompt: 2.4, completion: 2.4 },
'llama3-2': { prompt: 0.1, completion: 0.1 },
'llama3-2-1b': { prompt: 0.1, completion: 0.1 },
'llama3-2-3b': { prompt: 0.15, completion: 0.15 },
'llama3-2-11b': { prompt: 0.16, completion: 0.16 },
'llama3-2-90b': { prompt: 0.72, completion: 0.72 },
'llama3-3': { prompt: 2.65, completion: 3.5 },
'llama3-3-70b': { prompt: 2.65, completion: 3.5 },
// llama3.x:Nb pattern (base defaults to smallest variant)
'llama3.1': { prompt: 0.22, completion: 0.22 },
'llama3.1:8b': { prompt: 0.22, completion: 0.22 },
'llama3.1:70b': { prompt: 0.72, completion: 0.72 },
'llama3.1:405b': { prompt: 2.4, completion: 2.4 },
'llama3.2': { prompt: 0.1, completion: 0.1 },
'llama3.2:1b': { prompt: 0.1, completion: 0.1 },
'llama3.2:3b': { prompt: 0.15, completion: 0.15 },
'llama3.2:11b': { prompt: 0.16, completion: 0.16 },
'llama3.2:90b': { prompt: 0.72, completion: 0.72 },
'llama3.3': { prompt: 2.65, completion: 3.5 },
'llama3.3:70b': { prompt: 2.65, completion: 3.5 },
// llama-3.x-Nb pattern (base defaults to smallest variant)
'llama-3.1': { prompt: 0.22, completion: 0.22 },
'llama-3.1-8b': { prompt: 0.22, completion: 0.22 },
'llama-3.1-70b': { prompt: 0.72, completion: 0.72 },
'llama-3.1-405b': { prompt: 2.4, completion: 2.4 },
'llama-3.2': { prompt: 0.1, completion: 0.1 },
'llama-3.2-1b': { prompt: 0.1, completion: 0.1 },
'llama-3.2-3b': { prompt: 0.15, completion: 0.15 },
'llama-3.2-11b': { prompt: 0.16, completion: 0.16 },
'llama-3.2-90b': { prompt: 0.72, completion: 0.72 },
'llama-3.3': { prompt: 2.65, completion: 3.5 },
'llama-3.3-70b': { prompt: 2.65, completion: 3.5 },
'mistral-7b': { prompt: 0.15, completion: 0.2 },
'mistral-small': { prompt: 0.15, completion: 0.2 },
'mixtral-8x7b': { prompt: 0.45, completion: 0.7 },
'mistral-large-2402': { prompt: 4.0, completion: 12.0 },
'mistral-large-2407': { prompt: 3.0, completion: 9.0 },
'command-text': { prompt: 1.5, completion: 2.0 },
'command-light': { prompt: 0.3, completion: 0.6 },
// AI21 models
'j2-mid': { prompt: 12.5, completion: 12.5 },
'j2-ultra': { prompt: 18.8, completion: 18.8 },
'jamba-instruct': { prompt: 0.5, completion: 0.7 },
// Amazon Titan models
'titan-text-lite': { prompt: 0.15, completion: 0.2 },
'titan-text-express': { prompt: 0.2, completion: 0.6 },
'titan-text-premier': { prompt: 0.5, completion: 1.5 },
// Amazon Nova models
'nova-micro': { prompt: 0.035, completion: 0.14 },
'nova-lite': { prompt: 0.06, completion: 0.24 },
'nova-pro': { prompt: 0.8, completion: 3.2 },
'nova-premier': { prompt: 2.5, completion: 12.5 },
'deepseek.r1': { prompt: 1.35, completion: 5.4 },
// Moonshot/Kimi models on Bedrock
'moonshot.kimi': { prompt: 0.6, completion: 2.5 },
'moonshot.kimi-k2': { prompt: 0.6, completion: 2.5 },
'moonshot.kimi-k2.5': { prompt: 0.6, completion: 3.0 },
'moonshot.kimi-k2-thinking': { prompt: 0.6, completion: 2.5 },
};
/**
* Mapping of model token sizes to their respective multipliers for prompt and completion.
* The rates are 1 USD per 1M tokens.
* @type {Object.<string, {prompt: number, completion: number}>}
*/
const tokenValues = Object.assign(
{
// Legacy token size mappings (generic patterns - check LAST)
'8k': { prompt: 30, completion: 60 },
'32k': { prompt: 60, completion: 120 },
'4k': { prompt: 1.5, completion: 2 },
'16k': { prompt: 3, completion: 4 },
// Generic fallback patterns (check LAST)
'claude-': { prompt: 0.8, completion: 2.4 },
deepseek: { prompt: 0.28, completion: 0.42 },
command: { prompt: 0.38, completion: 0.38 },
gemma: { prompt: 0.02, completion: 0.04 }, // Base pattern (using gemma-3n-e4b pricing)
gemini: { prompt: 0.5, completion: 1.5 },
'gpt-oss': { prompt: 0.05, completion: 0.2 },
// Specific model variants (check FIRST - more specific patterns at end)
'gpt-3.5-turbo-1106': { prompt: 1, completion: 2 },
'gpt-3.5-turbo-0125': { prompt: 0.5, completion: 1.5 },
'gpt-4-1106': { prompt: 10, completion: 30 },
'gpt-4.1': { prompt: 2, completion: 8 },
'gpt-4.1-nano': { prompt: 0.1, completion: 0.4 },
'gpt-4.1-mini': { prompt: 0.4, completion: 1.6 },
'gpt-4.5': { prompt: 75, completion: 150 },
'gpt-4o': { prompt: 2.5, completion: 10 },
'gpt-4o-2024-05-13': { prompt: 5, completion: 15 },
'gpt-4o-mini': { prompt: 0.15, completion: 0.6 },
'gpt-5': { prompt: 1.25, completion: 10 },
'gpt-5.1': { prompt: 1.25, completion: 10 },
'gpt-5.2': { prompt: 1.75, completion: 14 },
'gpt-5-nano': { prompt: 0.05, completion: 0.4 },
'gpt-5-mini': { prompt: 0.25, completion: 2 },
'gpt-5-pro': { prompt: 15, completion: 120 },
o1: { prompt: 15, completion: 60 },
'o1-mini': { prompt: 1.1, completion: 4.4 },
'o1-preview': { prompt: 15, completion: 60 },
o3: { prompt: 2, completion: 8 },
'o3-mini': { prompt: 1.1, completion: 4.4 },
'o4-mini': { prompt: 1.1, completion: 4.4 },
'claude-instant': { prompt: 0.8, completion: 2.4 },
'claude-2': { prompt: 8, completion: 24 },
'claude-2.1': { prompt: 8, completion: 24 },
'claude-3-haiku': { prompt: 0.25, completion: 1.25 },
'claude-3-sonnet': { prompt: 3, completion: 15 },
'claude-3-opus': { prompt: 15, completion: 75 },
'claude-3-5-haiku': { prompt: 0.8, completion: 4 },
'claude-3.5-haiku': { prompt: 0.8, completion: 4 },
'claude-3-5-sonnet': { prompt: 3, completion: 15 },
'claude-3.5-sonnet': { prompt: 3, completion: 15 },
'claude-3-7-sonnet': { prompt: 3, completion: 15 },
'claude-3.7-sonnet': { prompt: 3, completion: 15 },
'claude-haiku-4-5': { prompt: 1, completion: 5 },
'claude-opus-4': { prompt: 15, completion: 75 },
'claude-opus-4-5': { prompt: 5, completion: 25 },
'claude-sonnet-4': { prompt: 3, completion: 15 },
'command-r': { prompt: 0.5, completion: 1.5 },
'command-r-plus': { prompt: 3, completion: 15 },
'command-text': { prompt: 1.5, completion: 2.0 },
'deepseek-chat': { prompt: 0.28, completion: 0.42 },
'deepseek-reasoner': { prompt: 0.28, completion: 0.42 },
'deepseek-r1': { prompt: 0.4, completion: 2.0 },
'deepseek-v3': { prompt: 0.2, completion: 0.8 },
'gemma-2': { prompt: 0.01, completion: 0.03 }, // Base pattern (using gemma-2-9b pricing)
'gemma-3': { prompt: 0.02, completion: 0.04 }, // Base pattern (using gemma-3n-e4b pricing)
'gemma-3-27b': { prompt: 0.09, completion: 0.16 },
'gemini-1.5': { prompt: 2.5, completion: 10 },
'gemini-1.5-flash': { prompt: 0.15, completion: 0.6 },
'gemini-1.5-flash-8b': { prompt: 0.075, completion: 0.3 },
'gemini-2.0': { prompt: 0.1, completion: 0.4 }, // Base pattern (using 2.0-flash pricing)
'gemini-2.0-flash': { prompt: 0.1, completion: 0.4 },
'gemini-2.0-flash-lite': { prompt: 0.075, completion: 0.3 },
'gemini-2.5': { prompt: 0.3, completion: 2.5 }, // Base pattern (using 2.5-flash pricing)
'gemini-2.5-flash': { prompt: 0.3, completion: 2.5 },
'gemini-2.5-flash-lite': { prompt: 0.1, completion: 0.4 },
'gemini-2.5-pro': { prompt: 1.25, completion: 10 },
'gemini-2.5-flash-image': { prompt: 0.15, completion: 30 },
'gemini-3': { prompt: 2, completion: 12 },
'gemini-3-pro-image': { prompt: 2, completion: 120 },
'gemini-pro-vision': { prompt: 0.5, completion: 1.5 },
grok: { prompt: 2.0, completion: 10.0 }, // Base pattern defaults to grok-2
'grok-beta': { prompt: 5.0, completion: 15.0 },
'grok-vision-beta': { prompt: 5.0, completion: 15.0 },
'grok-2': { prompt: 2.0, completion: 10.0 },
'grok-2-1212': { prompt: 2.0, completion: 10.0 },
'grok-2-latest': { prompt: 2.0, completion: 10.0 },
'grok-2-vision': { prompt: 2.0, completion: 10.0 },
'grok-2-vision-1212': { prompt: 2.0, completion: 10.0 },
'grok-2-vision-latest': { prompt: 2.0, completion: 10.0 },
'grok-3': { prompt: 3.0, completion: 15.0 },
'grok-3-fast': { prompt: 5.0, completion: 25.0 },
'grok-3-mini': { prompt: 0.3, completion: 0.5 },
'grok-3-mini-fast': { prompt: 0.6, completion: 4 },
'grok-4': { prompt: 3.0, completion: 15.0 },
'grok-4-fast': { prompt: 0.2, completion: 0.5 },
'grok-4-1-fast': { prompt: 0.2, completion: 0.5 }, // covers reasoning & non-reasoning variants
'grok-code-fast': { prompt: 0.2, completion: 1.5 },
codestral: { prompt: 0.3, completion: 0.9 },
'ministral-3b': { prompt: 0.04, completion: 0.04 },
'ministral-8b': { prompt: 0.1, completion: 0.1 },
'mistral-nemo': { prompt: 0.15, completion: 0.15 },
'mistral-saba': { prompt: 0.2, completion: 0.6 },
'pixtral-large': { prompt: 2.0, completion: 6.0 },
'mistral-large': { prompt: 2.0, completion: 6.0 },
'mixtral-8x22b': { prompt: 0.65, completion: 0.65 },
// Moonshot/Kimi models (base patterns first, specific patterns last for correct matching)
kimi: { prompt: 0.6, completion: 2.5 }, // Base pattern
moonshot: { prompt: 2.0, completion: 5.0 }, // Base pattern (using 128k pricing)
'kimi-latest': { prompt: 0.2, completion: 2.0 }, // Uses 8k/32k/128k pricing dynamically
'kimi-k2': { prompt: 0.6, completion: 2.5 },
'kimi-k2.5': { prompt: 0.6, completion: 3.0 },
'kimi-k2-turbo': { prompt: 1.15, completion: 8.0 },
'kimi-k2-turbo-preview': { prompt: 1.15, completion: 8.0 },
'kimi-k2-0905': { prompt: 0.6, completion: 2.5 },
'kimi-k2-0905-preview': { prompt: 0.6, completion: 2.5 },
'kimi-k2-0711': { prompt: 0.6, completion: 2.5 },
'kimi-k2-0711-preview': { prompt: 0.6, completion: 2.5 },
'kimi-k2-thinking': { prompt: 0.6, completion: 2.5 },
'kimi-k2-thinking-turbo': { prompt: 1.15, completion: 8.0 },
'moonshot-v1': { prompt: 2.0, completion: 5.0 },
'moonshot-v1-auto': { prompt: 2.0, completion: 5.0 },
'moonshot-v1-8k': { prompt: 0.2, completion: 2.0 },
'moonshot-v1-8k-vision': { prompt: 0.2, completion: 2.0 },
'moonshot-v1-8k-vision-preview': { prompt: 0.2, completion: 2.0 },
'moonshot-v1-32k': { prompt: 1.0, completion: 3.0 },
'moonshot-v1-32k-vision': { prompt: 1.0, completion: 3.0 },
'moonshot-v1-32k-vision-preview': { prompt: 1.0, completion: 3.0 },
'moonshot-v1-128k': { prompt: 2.0, completion: 5.0 },
'moonshot-v1-128k-vision': { prompt: 2.0, completion: 5.0 },
'moonshot-v1-128k-vision-preview': { prompt: 2.0, completion: 5.0 },
// GPT-OSS models (specific sizes)
'gpt-oss:20b': { prompt: 0.05, completion: 0.2 },
'gpt-oss-20b': { prompt: 0.05, completion: 0.2 },
'gpt-oss:120b': { prompt: 0.15, completion: 0.6 },
'gpt-oss-120b': { prompt: 0.15, completion: 0.6 },
// GLM models (Zhipu AI) - general to specific
glm4: { prompt: 0.1, completion: 0.1 },
'glm-4': { prompt: 0.1, completion: 0.1 },
'glm-4-32b': { prompt: 0.1, completion: 0.1 },
'glm-4.5': { prompt: 0.35, completion: 1.55 },
'glm-4.5-air': { prompt: 0.14, completion: 0.86 },
'glm-4.5v': { prompt: 0.6, completion: 1.8 },
'glm-4.6': { prompt: 0.5, completion: 1.75 },
// Qwen models
qwen: { prompt: 0.08, completion: 0.33 }, // Qwen base pattern (using qwen2.5-72b pricing)
'qwen2.5': { prompt: 0.08, completion: 0.33 }, // Qwen 2.5 base pattern
'qwen-turbo': { prompt: 0.05, completion: 0.2 },
'qwen-plus': { prompt: 0.4, completion: 1.2 },
'qwen-max': { prompt: 1.6, completion: 6.4 },
'qwq-32b': { prompt: 0.15, completion: 0.4 },
// Qwen3 models
qwen3: { prompt: 0.035, completion: 0.138 }, // Qwen3 base pattern (using qwen3-4b pricing)
'qwen3-8b': { prompt: 0.035, completion: 0.138 },
'qwen3-14b': { prompt: 0.05, completion: 0.22 },
'qwen3-30b-a3b': { prompt: 0.06, completion: 0.22 },
'qwen3-32b': { prompt: 0.05, completion: 0.2 },
'qwen3-235b-a22b': { prompt: 0.08, completion: 0.55 },
// Qwen3 VL (Vision-Language) models
'qwen3-vl-8b-thinking': { prompt: 0.18, completion: 2.1 },
'qwen3-vl-8b-instruct': { prompt: 0.18, completion: 0.69 },
'qwen3-vl-30b-a3b': { prompt: 0.29, completion: 1.0 },
'qwen3-vl-235b-a22b': { prompt: 0.3, completion: 1.2 },
// Qwen3 specialized models
'qwen3-max': { prompt: 1.2, completion: 6 },
'qwen3-coder': { prompt: 0.22, completion: 0.95 },
'qwen3-coder-30b-a3b': { prompt: 0.06, completion: 0.25 },
'qwen3-coder-plus': { prompt: 1, completion: 5 },
'qwen3-coder-flash': { prompt: 0.3, completion: 1.5 },
'qwen3-next-80b-a3b': { prompt: 0.1, completion: 0.8 },
},
bedrockValues,
);
/**
* Mapping of model token sizes to their respective multipliers for cached input, read and write.
* See Anthropic's documentation on this: https://docs.anthropic.com/en/docs/build-with-claude/prompt-caching#pricing
* The rates are 1 USD per 1M tokens.
* @type {Object.<string, {write: number, read: number }>}
*/
const cacheTokenValues = {
'claude-3.7-sonnet': { write: 3.75, read: 0.3 },
'claude-3-7-sonnet': { write: 3.75, read: 0.3 },
'claude-3.5-sonnet': { write: 3.75, read: 0.3 },
'claude-3-5-sonnet': { write: 3.75, read: 0.3 },
'claude-3.5-haiku': { write: 1, read: 0.08 },
'claude-3-5-haiku': { write: 1, read: 0.08 },
'claude-3-haiku': { write: 0.3, read: 0.03 },
'claude-haiku-4-5': { write: 1.25, read: 0.1 },
'claude-sonnet-4': { write: 3.75, read: 0.3 },
'claude-opus-4': { write: 18.75, read: 1.5 },
'claude-opus-4-5': { write: 6.25, read: 0.5 },
// DeepSeek models - cache hit: $0.028/1M, cache miss: $0.28/1M
deepseek: { write: 0.28, read: 0.028 },
'deepseek-chat': { write: 0.28, read: 0.028 },
'deepseek-reasoner': { write: 0.28, read: 0.028 },
// Moonshot/Kimi models - cache hit: $0.15/1M (k2) or $0.10/1M (k2.5), cache miss: $0.60/1M
kimi: { write: 0.6, read: 0.15 },
'kimi-k2': { write: 0.6, read: 0.15 },
'kimi-k2.5': { write: 0.6, read: 0.1 },
'kimi-k2-turbo': { write: 1.15, read: 0.15 },
'kimi-k2-turbo-preview': { write: 1.15, read: 0.15 },
'kimi-k2-0905': { write: 0.6, read: 0.15 },
'kimi-k2-0905-preview': { write: 0.6, read: 0.15 },
'kimi-k2-0711': { write: 0.6, read: 0.15 },
'kimi-k2-0711-preview': { write: 0.6, read: 0.15 },
'kimi-k2-thinking': { write: 0.6, read: 0.15 },
'kimi-k2-thinking-turbo': { write: 1.15, read: 0.15 },
};
/**
* Retrieves the key associated with a given model name.
*
* @param {string} model - The model name to match.
* @param {string} endpoint - The endpoint name to match.
* @returns {string|undefined} The key corresponding to the model name, or undefined if no match is found.
*/
const getValueKey = (model, endpoint) => {
if (!model || typeof model !== 'string') {
return undefined;
}
// Use findMatchingPattern directly against tokenValues for efficient lookup
if (!endpoint || (typeof endpoint === 'string' && !tokenValues[endpoint])) {
const matchedKey = findMatchingPattern(model, tokenValues);
if (matchedKey) {
return matchedKey;
}
}
// Fallback: use matchModelName for edge cases and legacy handling
const modelName = matchModelName(model, endpoint);
if (!modelName) {
return undefined;
}
// Legacy token size mappings and aliases for older models
if (modelName.includes('gpt-3.5-turbo-16k')) {
return '16k';
} else if (modelName.includes('gpt-3.5')) {
return '4k';
} else if (modelName.includes('gpt-4-vision')) {
return 'gpt-4-1106'; // Alias for gpt-4-vision
} else if (modelName.includes('gpt-4-0125')) {
return 'gpt-4-1106'; // Alias for gpt-4-0125
} else if (modelName.includes('gpt-4-turbo')) {
return 'gpt-4-1106'; // Alias for gpt-4-turbo
} else if (modelName.includes('gpt-4-32k')) {
return '32k';
} else if (modelName.includes('gpt-4')) {
return '8k';
}
return undefined;
};
/**
* Retrieves the multiplier for a given value key and token type. If no value key is provided,
* it attempts to derive it from the model name.
*
* @param {Object} params - The parameters for the function.
* @param {string} [params.valueKey] - The key corresponding to the model name.
* @param {'prompt' | 'completion'} [params.tokenType] - The type of token (e.g., 'prompt' or 'completion').
* @param {string} [params.model] - The model name to derive the value key from if not provided.
* @param {string} [params.endpoint] - The endpoint name to derive the value key from if not provided.
* @param {EndpointTokenConfig} [params.endpointTokenConfig] - The token configuration for the endpoint.
* @returns {number} The multiplier for the given parameters, or a default value if not found.
*/
const getMultiplier = ({ valueKey, tokenType, model, endpoint, endpointTokenConfig }) => {
if (endpointTokenConfig) {
return endpointTokenConfig?.[model]?.[tokenType] ?? defaultRate;
}
if (valueKey && tokenType) {
return tokenValues[valueKey][tokenType] ?? defaultRate;
}
if (!tokenType || !model) {
return 1;
}
valueKey = getValueKey(model, endpoint);
if (!valueKey) {
return defaultRate;
}
// If we got this far, and values[tokenType] is undefined somehow, return a rough average of default multipliers
return tokenValues[valueKey]?.[tokenType] ?? defaultRate;
};
/**
* Retrieves the cache multiplier for a given value key and token type. If no value key is provided,
* it attempts to derive it from the model name.
*
* @param {Object} params - The parameters for the function.
* @param {string} [params.valueKey] - The key corresponding to the model name.
* @param {'write' | 'read'} [params.cacheType] - The type of token (e.g., 'write' or 'read').
* @param {string} [params.model] - The model name to derive the value key from if not provided.
* @param {string} [params.endpoint] - The endpoint name to derive the value key from if not provided.
* @param {EndpointTokenConfig} [params.endpointTokenConfig] - The token configuration for the endpoint.
* @returns {number | null} The multiplier for the given parameters, or `null` if not found.
*/
const getCacheMultiplier = ({ valueKey, cacheType, model, endpoint, endpointTokenConfig }) => {
if (endpointTokenConfig) {
return endpointTokenConfig?.[model]?.[cacheType] ?? null;
}
if (valueKey && cacheType) {
return cacheTokenValues[valueKey]?.[cacheType] ?? null;
}
if (!cacheType || !model) {
return null;
}
valueKey = getValueKey(model, endpoint);
if (!valueKey) {
return null;
}
// If we got this far, and values[cacheType] is undefined somehow, return a rough average of default multipliers
return cacheTokenValues[valueKey]?.[cacheType] ?? null;
};
module.exports = {
tokenValues,
getValueKey,
getMultiplier,
getCacheMultiplier,
defaultRate,
cacheTokenValues,
};
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