mirror of
https://github.com/danny-avila/LibreChat.git
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66 lines
1.7 KiB
TypeScript
66 lines
1.7 KiB
TypeScript
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import { logger } from '@librechat/data-schemas';
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/**
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* Processes text content by counting tokens and truncating if it exceeds the specified limit.
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* @param text - The text content to process
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* @param tokenLimit - The maximum number of tokens allowed
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* @param tokenCountFn - Function to count tokens
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* @returns Promise resolving to object with processed text, token count, and truncation status
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*/
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export async function processTextWithTokenLimit({
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text,
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tokenLimit,
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tokenCountFn,
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}: {
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text: string;
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tokenLimit: number;
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tokenCountFn: (text: string) => number;
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}): Promise<{ text: string; tokenCount: number; wasTruncated: boolean }> {
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const originalTokenCount = await tokenCountFn(text);
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if (originalTokenCount <= tokenLimit) {
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return {
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text,
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tokenCount: originalTokenCount,
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wasTruncated: false,
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};
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}
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/**
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* Doing binary search here to find the truncation point efficiently
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* (May be a better way to go about this)
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*/
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let low = 0;
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let high = text.length;
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let bestText = '';
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logger.debug(
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`[textTokenLimiter] Text content exceeds token limit: ${originalTokenCount} > ${tokenLimit}, truncating...`,
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);
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while (low <= high) {
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const mid = Math.floor((low + high) / 2);
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const truncatedText = text.substring(0, mid);
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const tokenCount = await tokenCountFn(truncatedText);
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if (tokenCount <= tokenLimit) {
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bestText = truncatedText;
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low = mid + 1;
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} else {
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high = mid - 1;
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}
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}
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const finalTokenCount = await tokenCountFn(bestText);
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logger.warn(
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`[textTokenLimiter] Text truncated from ${originalTokenCount} to ${finalTokenCount} tokens (limit: ${tokenLimit})`,
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);
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return {
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text: bestText,
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tokenCount: finalTokenCount,
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wasTruncated: true,
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};
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}
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