mirror of
https://github.com/danny-avila/LibreChat.git
synced 2025-09-22 08:12:00 +02:00
🚀 feat: o1 (#4019)
* feat: o1 default response sender string * feat: add o1 models to default openai models list, add `no_system_messages` error type; refactor: use error type as localization key * refactor(MessageEndpointIcon): differentiate openAI icon model color for o1 models * refactor(AnthropicClient): use new input/output tokens keys; add prompt caching for claude-3-opus * refactor(BaseClient): to use new input/output tokens keys; update typedefs * feat: initial o1 model handling, including token cost complexity * EXPERIMENTAL: special handling for o1 model with custom instructions
This commit is contained in:
Danny Avila
GitHub
parent
9a393be012
commit
45b42830a5
12 changed files with 229 additions and 36 deletions
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@ -64,6 +64,12 @@ class AnthropicClient extends BaseClient {
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/** Whether or not the model supports Prompt Caching
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* @type {boolean} */
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this.supportsCacheControl;
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/** The key for the usage object's input tokens
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* @type {string} */
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this.inputTokensKey = 'input_tokens';
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/** The key for the usage object's output tokens
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* @type {string} */
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this.outputTokensKey = 'output_tokens';
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}
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setOptions(options) {
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@ -200,7 +206,7 @@ class AnthropicClient extends BaseClient {
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}
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/**
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* Calculates the correct token count for the current message based on the token count map and API usage.
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* Calculates the correct token count for the current user message based on the token count map and API usage.
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* Edge case: If the calculation results in a negative value, it returns the original estimate.
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* If revisiting a conversation with a chat history entirely composed of token estimates,
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* the cumulative token count going forward should become more accurate as the conversation progresses.
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@ -208,7 +214,7 @@ class AnthropicClient extends BaseClient {
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* @param {Record<string, number>} params.tokenCountMap - A map of message IDs to their token counts.
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* @param {string} params.currentMessageId - The ID of the current message to calculate.
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* @param {AnthropicStreamUsage} params.usage - The usage object returned by the API.
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* @returns {number} The correct token count for the current message.
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* @returns {number} The correct token count for the current user message.
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*/
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calculateCurrentTokenCount({ tokenCountMap, currentMessageId, usage }) {
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const originalEstimate = tokenCountMap[currentMessageId] || 0;
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@ -680,7 +686,11 @@ class AnthropicClient extends BaseClient {
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*/
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checkPromptCacheSupport(modelName) {
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const modelMatch = matchModelName(modelName, EModelEndpoint.anthropic);
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if (modelMatch === 'claude-3-5-sonnet' || modelMatch === 'claude-3-haiku') {
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if (
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modelMatch === 'claude-3-5-sonnet' ||
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modelMatch === 'claude-3-haiku' ||
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modelMatch === 'claude-3-opus'
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) {
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return true;
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}
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return false;
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@ -42,6 +42,12 @@ class BaseClient {
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this.conversationId;
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/** @type {string} */
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this.responseMessageId;
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/** The key for the usage object's input tokens
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* @type {string} */
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this.inputTokensKey = 'prompt_tokens';
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/** The key for the usage object's output tokens
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* @type {string} */
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this.outputTokensKey = 'completion_tokens';
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}
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setOptions() {
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@ -604,8 +610,8 @@ class BaseClient {
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* @type {StreamUsage | null} */
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const usage = this.getStreamUsage != null ? this.getStreamUsage() : null;
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if (usage != null && Number(usage.output_tokens) > 0) {
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responseMessage.tokenCount = usage.output_tokens;
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if (usage != null && Number(usage[this.outputTokensKey]) > 0) {
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responseMessage.tokenCount = usage[this.outputTokensKey];
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completionTokens = responseMessage.tokenCount;
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await this.updateUserMessageTokenCount({ usage, tokenCountMap, userMessage, opts });
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} else {
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@ -655,7 +661,7 @@ class BaseClient {
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/** @type {boolean} */
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const shouldUpdateCount =
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this.calculateCurrentTokenCount != null &&
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Number(usage.input_tokens) > 0 &&
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Number(usage[this.inputTokensKey]) > 0 &&
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(this.options.resendFiles ||
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(!this.options.resendFiles && !this.options.attachments?.length)) &&
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!this.options.promptPrefix;
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@ -19,6 +19,7 @@ const {
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constructAzureURL,
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getModelMaxTokens,
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genAzureChatCompletion,
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getModelMaxOutputTokens,
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} = require('~/utils');
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const {
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truncateText,
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@ -64,6 +65,9 @@ class OpenAIClient extends BaseClient {
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/** @type {string | undefined} - The API Completions URL */
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this.completionsUrl;
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/** @type {OpenAIUsageMetadata | undefined} */
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this.usage;
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}
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// TODO: PluginsClient calls this 3x, unneeded
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@ -138,7 +142,8 @@ class OpenAIClient extends BaseClient {
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const { model } = this.modelOptions;
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this.isChatCompletion = this.useOpenRouter || !!reverseProxy || model.includes('gpt');
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this.isChatCompletion =
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/\bo1\b/i.test(model) || model.includes('gpt') || this.useOpenRouter || !!reverseProxy;
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this.isChatGptModel = this.isChatCompletion;
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if (
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model.includes('text-davinci') ||
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@ -169,7 +174,14 @@ class OpenAIClient extends BaseClient {
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logger.debug('[OpenAIClient] maxContextTokens', this.maxContextTokens);
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}
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this.maxResponseTokens = this.modelOptions.max_tokens || 1024;
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this.maxResponseTokens =
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this.modelOptions.max_tokens ??
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getModelMaxOutputTokens(
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model,
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this.options.endpointType ?? this.options.endpoint,
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this.options.endpointTokenConfig,
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) ??
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1024;
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this.maxPromptTokens =
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this.options.maxPromptTokens || this.maxContextTokens - this.maxResponseTokens;
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@ -533,7 +545,8 @@ class OpenAIClient extends BaseClient {
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promptPrefix = this.augmentedPrompt + promptPrefix;
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}
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if (promptPrefix) {
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const isO1Model = /\bo1\b/i.test(this.modelOptions.model);
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if (promptPrefix && !isO1Model) {
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promptPrefix = `Instructions:\n${promptPrefix.trim()}`;
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instructions = {
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role: 'system',
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@ -561,6 +574,16 @@ class OpenAIClient extends BaseClient {
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messages,
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};
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/** EXPERIMENTAL */
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if (promptPrefix && isO1Model) {
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const lastUserMessageIndex = payload.findLastIndex((message) => message.role === 'user');
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if (lastUserMessageIndex !== -1) {
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payload[
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lastUserMessageIndex
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].content = `${promptPrefix}\n${payload[lastUserMessageIndex].content}`;
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}
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}
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if (tokenCountMap) {
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tokenCountMap.instructions = instructions?.tokenCount;
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result.tokenCountMap = tokenCountMap;
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@ -885,6 +908,56 @@ ${convo}
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return title;
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}
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/**
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* Get stream usage as returned by this client's API response.
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* @returns {OpenAIUsageMetadata} The stream usage object.
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*/
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getStreamUsage() {
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if (
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typeof this.usage === 'object' &&
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typeof this.usage.completion_tokens_details === 'object'
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) {
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const outputTokens = Math.abs(
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this.usage.completion_tokens_details.reasoning_tokens - this.usage[this.outputTokensKey],
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);
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return {
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...this.usage.completion_tokens_details,
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[this.inputTokensKey]: this.usage[this.inputTokensKey],
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[this.outputTokensKey]: outputTokens,
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};
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}
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return this.usage;
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}
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/**
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* Calculates the correct token count for the current user message based on the token count map and API usage.
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* Edge case: If the calculation results in a negative value, it returns the original estimate.
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* If revisiting a conversation with a chat history entirely composed of token estimates,
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* the cumulative token count going forward should become more accurate as the conversation progresses.
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* @param {Object} params - The parameters for the calculation.
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* @param {Record<string, number>} params.tokenCountMap - A map of message IDs to their token counts.
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* @param {string} params.currentMessageId - The ID of the current message to calculate.
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* @param {OpenAIUsageMetadata} params.usage - The usage object returned by the API.
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* @returns {number} The correct token count for the current user message.
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*/
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calculateCurrentTokenCount({ tokenCountMap, currentMessageId, usage }) {
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const originalEstimate = tokenCountMap[currentMessageId] || 0;
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if (!usage || typeof usage[this.inputTokensKey] !== 'number') {
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return originalEstimate;
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}
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tokenCountMap[currentMessageId] = 0;
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const totalTokensFromMap = Object.values(tokenCountMap).reduce((sum, count) => {
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const numCount = Number(count);
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return sum + (isNaN(numCount) ? 0 : numCount);
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}, 0);
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const totalInputTokens = usage[this.inputTokensKey] ?? 0;
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const currentMessageTokens = totalInputTokens - totalTokensFromMap;
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return currentMessageTokens > 0 ? currentMessageTokens : originalEstimate;
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}
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async summarizeMessages({ messagesToRefine, remainingContextTokens }) {
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logger.debug('[OpenAIClient] Summarizing messages...');
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let context = messagesToRefine;
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@ -1000,7 +1073,16 @@ ${convo}
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}
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}
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async recordTokenUsage({ promptTokens, completionTokens, context = 'message' }) {
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/**
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* @param {object} params
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* @param {number} params.promptTokens
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* @param {number} params.completionTokens
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* @param {OpenAIUsageMetadata} [params.usage]
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* @param {string} [params.model]
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* @param {string} [params.context='message']
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* @returns {Promise<void>}
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*/
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async recordTokenUsage({ promptTokens, completionTokens, usage, context = 'message' }) {
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await spendTokens(
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{
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context,
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@ -1011,6 +1093,19 @@ ${convo}
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},
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{ promptTokens, completionTokens },
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);
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if (typeof usage === 'object' && typeof usage.reasoning_tokens === 'number') {
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await spendTokens(
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{
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context: 'reasoning',
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model: this.modelOptions.model,
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conversationId: this.conversationId,
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user: this.user ?? this.options.req.user?.id,
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endpointTokenConfig: this.options.endpointTokenConfig,
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},
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{ completionTokens: usage.reasoning_tokens },
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);
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}
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}
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getTokenCountForResponse(response) {
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@ -1191,6 +1286,10 @@ ${convo}
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/** @type {(value: void | PromiseLike<void>) => void} */
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let streamResolve;
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if (modelOptions.stream && /\bo1\b/i.test(modelOptions.model)) {
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delete modelOptions.stream;
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}
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if (modelOptions.stream) {
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streamPromise = new Promise((resolve) => {
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streamResolve = resolve;
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@ -1269,6 +1368,8 @@ ${convo}
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}
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const { choices } = chatCompletion;
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this.usage = chatCompletion.usage;
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if (!Array.isArray(choices) || choices.length === 0) {
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logger.warn('[OpenAIClient] Chat completion response has no choices');
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return intermediateReply.join('');
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@ -37,6 +37,9 @@ const tokenValues = Object.assign(
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'4k': { prompt: 1.5, completion: 2 },
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'16k': { prompt: 3, completion: 4 },
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'gpt-3.5-turbo-1106': { prompt: 1, completion: 2 },
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'o1-preview': { prompt: 15, completion: 60 },
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'o1-mini': { prompt: 3, completion: 12 },
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o1: { prompt: 15, completion: 60 },
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'gpt-4o-2024-08-06': { prompt: 2.5, completion: 10 },
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'gpt-4o-mini': { prompt: 0.15, completion: 0.6 },
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'gpt-4o': { prompt: 5, completion: 15 },
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@ -95,6 +98,12 @@ const getValueKey = (model, endpoint) => {
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return 'gpt-3.5-turbo-1106';
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} else if (modelName.includes('gpt-3.5')) {
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return '4k';
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} else if (modelName.includes('o1-preview')) {
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return 'o1-preview';
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} else if (modelName.includes('o1-mini')) {
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return 'o1-mini';
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} else if (modelName.includes('o1')) {
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return 'o1';
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} else if (modelName.includes('gpt-4o-2024-08-06')) {
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return 'gpt-4o-2024-08-06';
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} else if (modelName.includes('gpt-4o-mini')) {
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@ -173,6 +173,10 @@ const handleAbortError = async (res, req, error, data) => {
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errorText = `{"type":"${ErrorTypes.INVALID_REQUEST}"}`;
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}
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if (error?.message?.includes('does not support \'system\'')) {
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errorText = `{"type":"${ErrorTypes.NO_SYSTEM_MESSAGES}"}`;
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}
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const respondWithError = async (partialText) => {
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let options = {
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sender,
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@ -1443,7 +1443,19 @@
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*/
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/**
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* @typedef {AnthropicStreamUsage} StreamUsage - Stream usage for all providers (currently only Anthropic)
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* @exports OpenAIUsageMetadata
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* @typedef {Object} OpenAIUsageMetadata - Usage statistics related to the run. This value will be `null` if the run is not in a terminal state (i.e. `in_progress`, `queued`, etc.).
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* @property {number} [usage.completion_tokens] - Number of completion tokens used over the course of the run.
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* @property {number} [usage.prompt_tokens] - Number of prompt tokens used over the course of the run.
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* @property {number} [usage.total_tokens] - Total number of tokens used (prompt + completion).
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* @property {number} [usage.reasoning_tokens] - Total number of tokens used for reasoning (OpenAI o1 models).
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* @property {Object} [usage.completion_tokens_details] - Further details on the completion tokens used (OpenAI o1 models).
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* @property {number} [usage.completion_tokens_details.reasoning_tokens] - Total number of tokens used for reasoning (OpenAI o1 models).
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* @memberof typedefs
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*/
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/**
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* @typedef {AnthropicStreamUsage | OpenAIUsageMetadata | UsageMetadata} StreamUsage - Stream usage for all providers (currently only Anthropic, OpenAI, LangChain)
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*/
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/* Native app/client methods */
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@ -2,6 +2,9 @@ const z = require('zod');
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const { EModelEndpoint } = require('librechat-data-provider');
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const openAIModels = {
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o1: 127500, // -500 from max
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'o1-mini': 127500, // -500 from max
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'o1-preview': 127500, // -500 from max
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'gpt-4': 8187, // -5 from max
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'gpt-4-0613': 8187, // -5 from max
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'gpt-4-32k': 32758, // -10 from max
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@ -113,6 +116,19 @@ const maxTokensMap = {
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[EModelEndpoint.bedrock]: bedrockModels,
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};
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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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system_default: 1024,
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};
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const maxOutputTokensMap = {
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[EModelEndpoint.azureOpenAI]: modelMaxOutputs,
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[EModelEndpoint.openAI]: modelMaxOutputs,
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[EModelEndpoint.custom]: modelMaxOutputs,
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};
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/**
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* Finds the first matching pattern in the tokens map.
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* @param {string} modelName
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@ -132,27 +148,15 @@ function findMatchingPattern(modelName, tokensMap) {
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}
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/**
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* Retrieves the maximum tokens for a given model name. 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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* 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 {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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*
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* @example
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* getModelMaxTokens('gpt-4-32k-0613'); // Returns 32767
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* getModelMaxTokens('gpt-4-32k-unknown'); // Returns 32767
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* getModelMaxTokens('unknown-model'); // Returns undefined
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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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*/
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function getModelMaxTokens(modelName, endpoint = EModelEndpoint.openAI, endpointTokenConfig) {
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if (typeof modelName !== 'string') {
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return undefined;
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}
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/** @type {EndpointTokenConfig | Record<string, number>} */
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const tokensMap = endpointTokenConfig ?? maxTokensMap[endpoint];
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if (!tokensMap) {
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function getModelTokenValue(modelName, tokensMap, key = 'context') {
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if (typeof modelName !== 'string' || !tokensMap) {
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return undefined;
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}
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@ -168,10 +172,36 @@ function getModelMaxTokens(modelName, endpoint = EModelEndpoint.openAI, endpoint
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if (matchedPattern) {
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const result = tokensMap[matchedPattern];
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return result?.context ?? result;
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return result?.[key] ?? result ?? tokensMap.system_default;
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}
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return undefined;
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return tokensMap.system_default;
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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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*/
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function getModelMaxTokens(modelName, endpoint = EModelEndpoint.openAI, endpointTokenConfig) {
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const tokensMap = endpointTokenConfig ?? maxTokensMap[endpoint];
|
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return getModelTokenValue(modelName, tokensMap);
|
||||
}
|
||||
|
||||
/**
|
||||
* Retrieves the maximum output tokens for a given model name.
|
||||
*
|
||||
* @param {string} modelName - The name of the model to look up.
|
||||
* @param {string} endpoint - The endpoint (default is 'openAI').
|
||||
* @param {EndpointTokenConfig} [endpointTokenConfig] - Token Config for current endpoint to use for max tokens lookup
|
||||
* @returns {number|undefined} The maximum output tokens for the given model or undefined if no match is found.
|
||||
*/
|
||||
function getModelMaxOutputTokens(modelName, endpoint = EModelEndpoint.openAI, endpointTokenConfig) {
|
||||
const tokensMap = endpointTokenConfig ?? maxOutputTokensMap[endpoint];
|
||||
return getModelTokenValue(modelName, tokensMap, 'output');
|
||||
}
|
||||
|
||||
/**
|
||||
|
|
@ -298,7 +328,8 @@ module.exports = {
|
|||
maxTokensMap,
|
||||
inputSchema,
|
||||
modelSchema,
|
||||
getModelMaxTokens,
|
||||
matchModelName,
|
||||
processModelData,
|
||||
getModelMaxTokens,
|
||||
getModelMaxOutputTokens,
|
||||
};
|
||||
|
|
|
|||
|
|
@ -17,6 +17,14 @@ import {
|
|||
import { IconProps } from '~/common';
|
||||
import { cn } from '~/utils';
|
||||
|
||||
function getOpenAIColor(_model: string | null | undefined) {
|
||||
const model = _model?.toLowerCase() ?? '';
|
||||
if (model && /\bo1\b/i.test(model)) {
|
||||
return '#000000';
|
||||
}
|
||||
return model.includes('gpt-4') ? '#AB68FF' : '#19C37D';
|
||||
}
|
||||
|
||||
function getGoogleIcon(model: string | null | undefined, size: number) {
|
||||
if (model?.toLowerCase().includes('code') === true) {
|
||||
return <CodeyIcon size={size * 0.75} />;
|
||||
|
|
@ -119,8 +127,7 @@ const MessageEndpointIcon: React.FC<IconProps> = (props) => {
|
|||
},
|
||||
[EModelEndpoint.openAI]: {
|
||||
icon: <GPTIcon size={size * 0.5555555555555556} />,
|
||||
bg:
|
||||
typeof model === 'string' && model.toLowerCase().includes('gpt-4') ? '#AB68FF' : '#19C37D',
|
||||
bg: getOpenAIColor(model),
|
||||
name: 'ChatGPT',
|
||||
},
|
||||
[EModelEndpoint.gptPlugins]: {
|
||||
|
|
|
|||
|
|
@ -42,7 +42,8 @@ const errorMessages = {
|
|||
[ErrorTypes.NO_USER_KEY]: 'com_error_no_user_key',
|
||||
[ErrorTypes.INVALID_USER_KEY]: 'com_error_invalid_user_key',
|
||||
[ErrorTypes.NO_BASE_URL]: 'com_error_no_base_url',
|
||||
[ErrorTypes.INVALID_REQUEST]: 'com_error_invalid_request',
|
||||
[ErrorTypes.INVALID_REQUEST]: `com_error_${ErrorTypes.INVALID_REQUEST}`,
|
||||
[ErrorTypes.NO_SYSTEM_MESSAGES]: `com_error_${ErrorTypes.NO_SYSTEM_MESSAGES}`,
|
||||
[ErrorTypes.EXPIRED_USER_KEY]: (json: TExpiredKey, localize: LocalizeFunction) => {
|
||||
const { expiredAt, endpoint } = json;
|
||||
return localize('com_error_expired_user_key', endpoint, expiredAt);
|
||||
|
|
|
|||
|
|
@ -24,8 +24,10 @@ export default {
|
|||
com_error_no_base_url: 'No base URL found. Please provide one and try again.',
|
||||
com_warning_resubmit_unsupported:
|
||||
'Resubmitting the AI message is not supported for this endpoint.',
|
||||
com_error_invalid_request:
|
||||
com_error_invalid_request_error:
|
||||
'The AI service rejected the request due to an error. This could be caused by an invalid API key or an improperly formatted request.',
|
||||
com_error_no_system_messages:
|
||||
'The selected AI service or model does not support system messages. Try using prompts instead of custom instructions.',
|
||||
com_error_invalid_user_key: 'Invalid key provided. Please provide a valid key and try again.',
|
||||
com_error_expired_user_key:
|
||||
'Provided key for {0} expired at {1}. Please provide a new key and try again.',
|
||||
|
|
|
|||
|
|
@ -11,6 +11,10 @@ export const defaultSocialLogins = ['google', 'facebook', 'openid', 'github', 'd
|
|||
|
||||
export const defaultRetrievalModels = [
|
||||
'gpt-4o',
|
||||
'o1-preview-2024-09-12',
|
||||
'o1-preview',
|
||||
'o1-mini-2024-09-12',
|
||||
'o1-mini',
|
||||
'chatgpt-4o-latest',
|
||||
'gpt-4o-2024-05-13',
|
||||
'gpt-4o-2024-08-06',
|
||||
|
|
@ -951,6 +955,10 @@ export enum ErrorTypes {
|
|||
* Invalid request error, API rejected request
|
||||
*/
|
||||
INVALID_REQUEST = 'invalid_request_error',
|
||||
/**
|
||||
* Invalid request error, API rejected request
|
||||
*/
|
||||
NO_SYSTEM_MESSAGES = 'no_system_messages',
|
||||
}
|
||||
|
||||
/**
|
||||
|
|
|
|||
|
|
@ -240,6 +240,8 @@ export const getResponseSender = (endpointOption: t.TEndpointOption): string =>
|
|||
) {
|
||||
if (chatGptLabel) {
|
||||
return chatGptLabel;
|
||||
} else if (model && /\bo1\b/i.test(model)) {
|
||||
return 'o1';
|
||||
} else if (model && model.includes('gpt-3')) {
|
||||
return 'GPT-3.5';
|
||||
} else if (model && model.includes('gpt-4o')) {
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue