LibreChat/api/models/tx.js
Danny Avila 8263ddda3f
🤖 feat(Anthropic): Claude 3 & Vision Support (#1984)
* chore: bump anthropic SDK

* chore: update anthropic config settings (fileSupport, default models)

* feat: anthropic multi modal formatting

* refactor: update vision models and use endpoint specific max long side resizing

* feat(anthropic): multimodal messages, retry logic, and messages payload

* chore: add more safety to trimming content due to whitespace error for assistant messages

* feat(anthropic): token accounting and resending multiple images in progress

* chore: bump data-provider

* feat(anthropic): resendImages feature

* chore: optimize Edit/Ask controllers, switch model back to req model

* fix: false positive of invalid model

* refactor(validateVisionModel): use object as arg, pass in additional/available models

* refactor(validateModel): use helper function, `getModelsConfig`

* feat: add modelsConfig to endpointOption so it gets passed to all clients, use for properly validating vision models

* refactor: initialize default vision model and make sure it's available before assigning it

* refactor(useSSE): avoid resetting model if user selected a new model between request and response

* feat: show rate in transaction logging

* fix: return tokenCountMap regardless of payload shape
2024-03-06 00:04:52 -05:00

96 lines
3.4 KiB
JavaScript

const { matchModelName } = require('../utils');
const defaultRate = 6;
/**
* Mapping of model token sizes to their respective multipliers for prompt and completion.
* @type {Object.<string, {prompt: number, completion: number}>}
*/
const tokenValues = {
'8k': { prompt: 30, completion: 60 },
'32k': { prompt: 60, completion: 120 },
'4k': { prompt: 1.5, completion: 2 },
'16k': { prompt: 3, completion: 4 },
'gpt-3.5-turbo-1106': { prompt: 1, completion: 2 },
'gpt-4-1106': { prompt: 10, completion: 30 },
'gpt-3.5-turbo-0125': { prompt: 0.5, completion: 1.5 },
'claude-3-opus': { prompt: 15, completion: 75 },
'claude-3-sonnet': { prompt: 3, completion: 15 },
'claude-3-haiku': { prompt: 0.25, completion: 1.25 },
'claude-2.1': { prompt: 8, completion: 24 },
'claude-2': { prompt: 8, completion: 24 },
'claude-': { prompt: 0.8, completion: 2.4 },
};
/**
* 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) => {
const modelName = matchModelName(model, endpoint);
if (!modelName) {
return undefined;
}
if (modelName.includes('gpt-3.5-turbo-16k')) {
return '16k';
} else if (modelName.includes('gpt-3.5-turbo-0125')) {
return 'gpt-3.5-turbo-0125';
} else if (modelName.includes('gpt-3.5-turbo-1106')) {
return 'gpt-3.5-turbo-1106';
} else if (modelName.includes('gpt-3.5')) {
return '4k';
} else if (modelName.includes('gpt-4-1106')) {
return 'gpt-4-1106';
} else if (modelName.includes('gpt-4-0125')) {
return 'gpt-4-1106';
} else if (modelName.includes('gpt-4-turbo')) {
return 'gpt-4-1106';
} else if (modelName.includes('gpt-4-32k')) {
return '32k';
} else if (modelName.includes('gpt-4')) {
return '8k';
} else if (tokenValues[modelName]) {
return modelName;
}
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 {string} [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;
};
module.exports = { tokenValues, getValueKey, getMultiplier, defaultRate };