🦛 CHONK your texts with Chonkie ✨ — The no-nonsense RAG chunking library - chonkie-inc/chonkie

## Summary This article introduces how to use `@kit.NaturalLanguageKit` in HarmonyOS for text word segmentation and implement a simple sentiment analysis function. By creating a `TextProcessingWordSegment` component, users can input evaluation text, click a button to perform sentiment analysis, and finally display the sentiment tendency (positive, negative, or neutral) of the evaluation. ## Implementation Steps 1. Import the `textProcessing` module from `@kit.NaturalLanguageKit`. 2. Create a `TextProcessingWordSegment` component, which includes a text input box, a text area to display results, and an analysis button. 3. Implement the event handler for the button click, and call `textProcessing.getWordSegment` to perform word segmentation. 4. Create a `SentimentAnalysisService` class to perform sentiment analysis based on the word segmentation results. 5. Display the final sentiment label according to the sentiment score. ## Implementation Code ### 1. Import Modules and Define Components import { textProcessing } from '@kit.NaturalLanguageKit'; @Entry @Component struct TextProcessingWordSegment { @State comment: string = 'The logistics is fast, the packaging is good, and I am particularly satisfied with the product'; @State label: string = '' build() { Column({ space: 20 }) { TextArea({ text: this.comment }) .height(200) Text('Evaluation Nature: ' + this.label) Button('Sentiment Analysis') .onClick(async () => { const results = await textProcessing.getWordSegment(this.comment) const words = results.map(item => item.word) const service = new SentimentAnalysisService() this.label = service.analyze(words) }) } .padding(15) .height('100%') .width('100%') } } ### 2. Sentiment Analysis Service Class // Sentiment Analysis Service Class class SentimentAnalysisService { private positiveWords = ['good', 'satisfied', 'great', 'excellent', 'fast']; private negativeWords = ['bad', 'slow', 'expensive', 'awful', 'unsatisfied']; analyze(words: string[]) { let score = 0.5; words.forEach(word => { if (this.positiveWords.includes(word)) { score += 0.1; } if (this.negativeWords.includes(word)) { score -= 0.1; } }); score = Math.max(0, Math.min(1, score)); const label = score > 0.6 ? 'Positive' : score < 0.4 ? 'Negative' : 'Neutral'; return label; } } ## Conclusion This case demonstrates the method of using `@kit.NaturalLanguageKit` for text processing and implementing simple sentiment analysis in HarmonyOS. By creating components and a service class, we have implemented the functions of text input, word segmentation, and sentiment analysis. The key knowledge points include the creation of HarmonyOS components, state management, the use of asynchronous functions, and simple sentiment analysis algorithms. This method can serve as a foundation to expand more complex natural language processing functions.

Write a function which returns the number of words in the given character scalar or vector.