Files
bilin/tests/main/ai-context-builder.test.ts
bing aa2c7dfed3 feat: ship v0.7.0 with AI knowledge context integration
Add semi-automatic knowledge suggestions and user-confirmed injection across chat, interactive, auto, and wizard modes; fix writing flows to persist full systemPrompt in contextJson.

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-07-07 15:33:53 +08:00

144 lines
4.6 KiB
TypeScript

import { describe, it, expect, beforeEach, afterEach } from 'vitest'
import { DatabaseSync } from 'node:sqlite'
import { mkdtempSync, rmSync } from 'fs'
import { join } from 'path'
import { tmpdir } from 'os'
import { migrate } from '../../src/main/db/migrate'
import { ChapterRepository } from '../../src/main/db/repositories/chapter.repo'
import { VolumeRepository } from '../../src/main/db/repositories/volume.repo'
import { SettingRepository } from '../../src/main/db/repositories/setting.repo'
import { KnowledgeRepository } from '../../src/main/db/repositories/knowledge.repo'
import { BookRegistryService } from '../../src/main/services/book-registry'
import { aiContextBuilder } from '../../src/main/services/ai-context-builder.service'
import type { SqliteDb } from '../../src/main/db/types'
describe('AiContextBuilderService', () => {
let userDir: string
let registry: BookRegistryService
let bookId: string
let volId: string
let db: SqliteDb
beforeEach(() => {
userDir = mkdtempSync(join(tmpdir(), 'bilin-ctx-'))
registry = new BookRegistryService(userDir)
const meta = registry.create({ name: '测试书', category: '玄幻' })
bookId = meta.id
db = registry.getDb(bookId)
volId = new VolumeRepository(db).create('卷一', 0).id
})
afterEach(() => {
db?.close()
rmSync(userDir, { recursive: true, force: true })
})
it('truncates long chapter content to 2000 chars per block', () => {
const chapters = new ChapterRepository(db)
const longHtml = `<p>${'章'.repeat(3000)}</p>`
const chapter = chapters.create(volId, '长章节', 0, longHtml)
const result = aiContextBuilder.build(
{ chapterIds: [chapter.id], outlineIds: [], settingIds: [], inspirationIds: [], knowledgeIds: [] },
registry,
bookId,
'作者'
)
expect(result.preview).toHaveLength(1)
expect(result.preview[0].excerpt.length).toBeLessThanOrEqual(2001)
expect(result.systemPrompt.length).toBeLessThanOrEqual(16 * 1024 + 500)
})
it('keeps total context within 16KB', () => {
const chapters = new ChapterRepository(db)
const ids: string[] = []
for (let i = 0; i < 12; i++) {
const ch = chapters.create(volId, `章节${i}`, i, `<p>${'内容'.repeat(900)}</p>`)
ids.push(ch.id)
}
const result = aiContextBuilder.build(
{ chapterIds: ids, outlineIds: [], settingIds: [], inspirationIds: [], knowledgeIds: [] },
registry,
bookId,
'作者'
)
const blocksText = result.preview.map((p) => p.excerpt).join('')
expect(blocksText.length).toBeLessThanOrEqual(16 * 1024)
expect(result.preview.length).toBeLessThan(ids.length)
})
it('includes setting in preview', () => {
const settings = new SettingRepository(db)
const setting = settings.create('character', '主角林远', '少年修士')
const result = aiContextBuilder.build(
{ chapterIds: [], outlineIds: [], settingIds: [setting.id], inspirationIds: [], knowledgeIds: [] },
registry,
bookId,
'作者'
)
expect(result.preview[0].title).toBe('主角林远')
expect(result.systemPrompt).toContain('主角林远')
})
it('UT-CTX-02: build includes knowledge preview items', () => {
const know = new KnowledgeRepository(db)
const entry = know.create({
type: 'foreshadow',
title: '测灵石',
content: '石头发热',
status: 'approved'
})
const result = aiContextBuilder.build(
{
chapterIds: [],
outlineIds: [],
settingIds: [],
inspirationIds: [],
knowledgeIds: [entry.id]
},
registry,
bookId,
'作者'
)
expect(result.preview.some((p) => p.kind === 'knowledge')).toBe(true)
expect(result.systemPrompt).toContain('【知识·伏笔】')
expect(result.systemPrompt).toContain('测灵石')
})
it('UT-CTX-03: caps knowledge section at 4000 chars', () => {
const know = new KnowledgeRepository(db)
const ids: string[] = []
for (let i = 0; i < 20; i++) {
const e = know.create({
type: 'fact',
title: `条目${i}`,
content: '长'.repeat(400),
importance: 5,
status: 'approved'
})
ids.push(e.id)
}
const result = aiContextBuilder.build(
{
chapterIds: [],
outlineIds: [],
settingIds: [],
inspirationIds: [],
knowledgeIds: ids
},
registry,
bookId,
'作者'
)
const knowledgeChars = result.preview
.filter((p) => p.kind === 'knowledge')
.reduce((s, p) => s + p.charCount, 0)
expect(knowledgeChars).toBeLessThanOrEqual(4000)
})
})