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🚀 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
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Danny Avila
GitHub
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9a393be012
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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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