refactor(nlp): enhance EPUB text splitting for oversized sentences and remove unused functions

- Add logic to split oversized sentences in `splitTextToTtsBlocksEPUB` using `splitOversizedText` to ensure blocks stay within `MAX_BLOCK_LENGTH`
- Remove `extractRawSentences` and `processTextWithMapping` functions as they are no longer needed
- Update tests to reflect the changes, including a new test for oversized sentence splitting and removal of related test suites

src/lib/nlp.ts

@@ -203,14 +203,20 @@ export const splitTextToTtsBlocksEPUB = (text: string): string[] => {
 
     for (const sentence of mergedSentences) {
       const trimmedSentence = sentence.trim();
+      const sentenceParts =
+        trimmedSentence.length > MAX_BLOCK_LENGTH
+          ? splitOversizedText(trimmedSentence, MAX_BLOCK_LENGTH)
+          : [trimmedSentence];
 
-      if (currentBlock && (currentBlock.length + trimmedSentence.length + 1) > MAX_BLOCK_LENGTH) {
+      for (const sentencePart of sentenceParts) {
-        blocks.push(currentBlock.trim());
+        if (currentBlock && (currentBlock.length + sentencePart.length + 1) > MAX_BLOCK_LENGTH) {
-        currentBlock = trimmedSentence;
+          blocks.push(currentBlock.trim());
-      } else {
+          currentBlock = sentencePart;
-        currentBlock = currentBlock
+        } else {
-          ? `${currentBlock} ${trimmedSentence}`
+          currentBlock = currentBlock
-          : trimmedSentence;
+            ? `${currentBlock} ${sentencePart}`
+            : sentencePart;
+        }
       }
     }
 
@@ -232,72 +238,6 @@ export const splitTextToTtsBlocksEPUB = (text: string): string[] => {
 export const normalizeTextForTts = (text: string): string =>
   splitTextToTtsBlocks(text).join(' ');
 
-/**
- * Extracts raw sentence strings from text without preprocessing or block grouping.
- * Useful for text matching and highlighting.
- * 
- * @param {string} text - The text to extract sentences from
- * @returns {string[]} Array of raw sentences
- */
-export const extractRawSentences = (text: string): string[] => {
-  if (!text || text.length < 1) {
-    return [];
-  }
-  
-  return nlp(text).sentences().out('array') as string[];
-};
-
-/**
- * Enhanced sentence processing that returns both processed sentences and raw sentences
- * This allows for better mapping between the two for click-to-highlight functionality
- * 
- * @param {string} text - The text to process
- * @returns {Object} Object containing processed sentences and raw sentences with mapping
- */
-export const processTextWithMapping = (text: string): {
-  processedSentences: string[];
-  rawSentences: string[];
-  sentenceMapping: Array<{ processedIndex: number; rawIndices: number[] }>;
-} => {
-  const rawSentences = extractRawSentences(text);
-  const processedSentences = splitTextToTtsBlocks(text);
-  
-  // Create a mapping between processed sentences and raw sentences
-  const sentenceMapping: Array<{ processedIndex: number; rawIndices: number[] }> = [];
-  
-  // For simple mapping, we'll track which raw sentences contributed to each processed sentence
-  let rawIndex = 0;
-  
-  for (let processedIndex = 0; processedIndex < processedSentences.length; processedIndex++) {
-    const processedSentence = processedSentences[processedIndex];
-    const rawIndices: number[] = [];
-    
-    // Find which raw sentences are contained in this processed sentence
-    const remainingText = processedSentence;
-    
-    while (rawIndex < rawSentences.length && remainingText.length > 0) {
-      const rawSentence = rawSentences[rawIndex];
-      const cleanedRawSentence = preprocessSentenceForAudio(rawSentence);
-      
-      if (remainingText.includes(cleanedRawSentence) || cleanedRawSentence.includes(remainingText)) {
-        rawIndices.push(rawIndex);
-        rawIndex++;
-        break;
-      } else {
-        rawIndex++;
-      }
-    }
-    
-    sentenceMapping.push({ processedIndex, rawIndices });
-  }
-  
-  return {
-    processedSentences,
-    rawSentences,
-    sentenceMapping
-  };
-}; 
-
 // Helper functions to merge quoted dialogue across sentences
 const countDoubleQuotes = (s: string): number => {
   const matches = s.match(/["“”]/g);

tests/unit/nlp.spec.ts

@@ -4,8 +4,6 @@ import {
   splitTextToTtsBlocks, 
   splitTextToTtsBlocksEPUB,
   normalizeTextForTts,
-  extractRawSentences,
-  processTextWithMapping,
   MAX_BLOCK_LENGTH
 } from '../../src/lib/nlp';
 
@@ -169,6 +167,14 @@ test.describe('splitTextToTtsBlocksEPUB (highlight-friendly)', () => {
     expect(result[0]).toBe('One.');
     expect(result[1]).toBe('Two.');
   });
+
+  test('splits oversized sentences to keep blocks bounded', () => {
+    const input = Array(1200).fill('word').join(' '); // no punctuation; guaranteed to exceed MAX_BLOCK_LENGTH
+    const result = splitTextToTtsBlocksEPUB(input);
+
+    expect(result.length).toBeGreaterThan(1);
+    expectNormalizedBlocks(result, MAX_BLOCK_LENGTH);
+  });
 });
 
 test.describe('normalizeTextForTts', () => {
@@ -180,36 +186,3 @@ test.describe('normalizeTextForTts', () => {
     expect(normalized.length).toBeGreaterThan(0);
   });
 });
-
-test.describe('extractRawSentences', () => {
-  test('returns [] for empty input', () => {
-    expect(extractRawSentences('')).toEqual([]);
-  });
-
-  test('returns sentence-like strings without preprocessing', () => {
-    const input = 'First sentence. Second sentence.';
-    const result = extractRawSentences(input);
-    expect(result.length).toBeGreaterThanOrEqual(2);
-    expect(result[0]).toContain('First');
-  });
-});
-
-test.describe('processTextWithMapping', () => {
-  test('returns mapping entries with valid indices', () => {
-    const text = 'First (1). Second (2).';
-    const { processedSentences, rawSentences, sentenceMapping } = processTextWithMapping(text);
-
-    expect(processedSentences.length).toBeGreaterThan(0);
-    expect(rawSentences.length).toBeGreaterThan(0);
-    expect(sentenceMapping).toHaveLength(processedSentences.length);
-
-    for (let i = 0; i < sentenceMapping.length; i++) {
-      const entry = sentenceMapping[i];
-      expect(entry.processedIndex).toBe(i);
-      for (const rawIndex of entry.rawIndices) {
-        expect(rawIndex).toBeGreaterThanOrEqual(0);
-        expect(rawIndex).toBeLessThan(rawSentences.length);
-      }
-    }
-  });
-});