UNPKG

@caleblawson/rag

Version:

The Retrieval-Augmented Generation (RAG) module contains document processing and embedding utilities.

108 lines (93 loc) 4.25 kB
import { createOpenAI } from '@ai-sdk/openai'; import { describe, it, expect, vi } from 'vitest'; import { TextNode } from '../schema'; import { SummaryExtractor } from './summary'; const openai = createOpenAI({ apiKey: process.env.OPENAI_API_KEY, }); const model = openai('gpt-4o'); vi.setConfig({ testTimeout: 10_000, hookTimeout: 10_000 }); describe('SummaryExtractor', () => { it('can use a custom model from the test suite', async () => { const extractor = new SummaryExtractor({ llm: model }); const node = new TextNode({ text: 'A summary test using a custom model.' }); const summary = await extractor.generateNodeSummary(node); expect(typeof summary).toBe('string'); expect(summary.length).toBeGreaterThan(0); }); it('extracts summary from normal text', async () => { const extractor = new SummaryExtractor(); const node = new TextNode({ text: 'This is a test document.' }); const summary = await extractor.generateNodeSummary(node); expect(typeof summary).toBe('string'); expect(summary.length).toBeGreaterThan(0); }); it('handles empty input gracefully', async () => { const extractor = new SummaryExtractor(); const node = new TextNode({ text: '' }); const summary = await extractor.generateNodeSummary(node); expect(summary).toBe(''); }); it('supports prompt customization', async () => { const extractor = new SummaryExtractor({ promptTemplate: 'Summarize: {context}' }); const node = new TextNode({ text: 'Test document for prompt customization.' }); const summary = await extractor.generateNodeSummary(node); expect(typeof summary).toBe('string'); expect(summary.length).toBeGreaterThan(0); }); it('handles very long input', async () => { const extractor = new SummaryExtractor(); const longText = 'A'.repeat(1000); const node = new TextNode({ text: longText }); const summary = await extractor.generateNodeSummary(node); expect(typeof summary).toBe('string'); }); it('handles whitespace only input', async () => { const extractor = new SummaryExtractor(); const node = new TextNode({ text: ' ' }); const summary = await extractor.generateNodeSummary(node); expect(summary).toBe(''); }); it('handles special characters and emojis', async () => { const extractor = new SummaryExtractor(); const node = new TextNode({ text: '🚀✨🔥' }); const summary = await extractor.generateNodeSummary(node); expect(typeof summary).toBe('string'); expect(summary.length).toBeGreaterThan(0); }); it('handles numbers only', async () => { const extractor = new SummaryExtractor(); const node = new TextNode({ text: '1234567890' }); const summary = await extractor.generateNodeSummary(node); expect(typeof summary).toBe('string'); expect(summary.length).toBeGreaterThan(0); }); it('handles HTML tags', async () => { const extractor = new SummaryExtractor(); const node = new TextNode({ text: '<h1>Test</h1>' }); const summary = await extractor.generateNodeSummary(node); expect(typeof summary).toBe('string'); expect(summary.length).toBeGreaterThan(0); }); it('handles non-English text', async () => { const extractor = new SummaryExtractor(); const node = new TextNode({ text: '这是一个测试文档。' }); const summary = await extractor.generateNodeSummary(node); expect(typeof summary).toBe('string'); expect(summary.length).toBeGreaterThan(0); }); it('handles duplicate/repeated text', async () => { const extractor = new SummaryExtractor(); const node = new TextNode({ text: 'repeat repeat repeat' }); const summary = await extractor.generateNodeSummary(node); expect(typeof summary).toBe('string'); expect(summary.length).toBeGreaterThan(0); }); it('handles only punctuation', async () => { const extractor = new SummaryExtractor(); const node = new TextNode({ text: '!!!???...' }); const summary = await extractor.generateNodeSummary(node); expect(typeof summary).toBe('string'); expect(summary.length).toBeGreaterThan(0); }); });