Files
ChatLab/tests/chart-runtime/real-llm-chart-flow.e2e.test.ts

205 lines
8.6 KiB
TypeScript

import { describe, it } from 'node:test'
import assert from 'node:assert/strict'
import { existsSync, mkdtempSync, rmSync } from 'node:fs'
import { tmpdir } from 'node:os'
import path from 'node:path'
import type { AgentTool, AgentToolResult } from '@earendil-works/pi-agent-core'
import { CHAT_DB_SCHEMA, getChartCapabilitySkill, type ChartPayload } from '@openchatlab/core'
import {
CoreDataProvider,
renderChartTool,
schemaTool,
type ToolDataProvider,
type ToolDefinition,
type ToolExecutionContext,
} from '@openchatlab/tools'
import { buildPiModel } from '../../packages/node-runtime/src/ai/llm-builder'
import { runAgentCore, type AgentCoreEvent } from '../../packages/node-runtime/src/ai/agent'
import { openBetterSqliteDatabase } from '../../packages/node-runtime/src/better-sqlite3-adapter'
const shouldRunRealLlmE2E = process.env.CHATLAB_RUN_REAL_LLM_CHART_E2E === '1'
function resolveNativeBinding(): string | undefined {
if (process.env.CHATLAB_TEST_SQLITE_NATIVE_BINDING) return process.env.CHATLAB_TEST_SQLITE_NATIVE_BINDING
const repoNativeBinding = path.resolve('apps/cli/native/better_sqlite3.node')
return existsSync(repoNativeBinding) ? repoNativeBinding : undefined
}
function unixTs(iso: string): number {
return Math.floor(Date.parse(iso) / 1000)
}
function createTempDir(): string {
return mkdtempSync(path.join(tmpdir(), 'chatlab-real-llm-chart-e2e-'))
}
function seedChatDb(db: ReturnType<typeof openBetterSqliteDatabase>): void {
db.exec(CHAT_DB_SCHEMA)
db.prepare(
`INSERT INTO meta (name, platform, type, imported_at, group_id, owner_id)
VALUES ('Chart E2E Group', 'wechat', 'group', ?, 'g1', 'u_alice')`
).run(unixTs('2026-06-03T00:00:00Z'))
const insertMember = db.prepare(
`INSERT INTO member (platform_id, account_name, group_nickname)
VALUES (?, ?, ?)`
)
insertMember.run('u_alice', 'Alice Account', 'Alice')
insertMember.run('u_bob', 'Bob Account', 'Bob')
insertMember.run('u_cara', 'Cara Account', 'Cara')
const memberRows = db.prepare('SELECT id, group_nickname FROM member').all() as Array<{
id: number
group_nickname: string
}>
const memberId = new Map(memberRows.map((row) => [row.group_nickname, row.id]))
const insertMessage = db.prepare(
`INSERT INTO message (sender_id, sender_account_name, sender_group_nickname, ts, type, content, platform_message_id)
VALUES (?, ?, ?, ?, ?, ?, ?)`
)
const add = (name: 'Alice' | 'Bob' | 'Cara', ts: string, type: number, content: string) => {
const id = memberId.get(name)
assert.ok(id, `missing member id for ${name}`)
insertMessage.run(id, `${name} Account`, name, unixTs(ts), type, content, `${name}-${ts}`)
}
add('Alice', '2026-06-01T09:00:00Z', 0, 'morning hello')
add('Alice', '2026-06-01T10:00:00Z', 0, 'standup note')
add('Alice', '2026-06-02T09:00:00Z', 1, '[图片]')
add('Alice', '2026-06-02T10:00:00Z', 0, 'follow up')
add('Bob', '2026-06-01T09:00:00Z', 0, 'first reply')
add('Bob', '2026-06-02T10:00:00Z', 0, 'second reply')
add('Bob', '2026-06-02T11:00:00Z', 0, 'third reply')
add('Cara', '2026-06-01T09:00:00Z', 0, 'other member')
add('Cara', '2026-06-03T12:00:00Z', 0, 'outside selected members')
}
function convertJsonSchemaToParameters(schema: ToolDefinition['inputSchema']) {
const properties: Record<string, unknown> = {}
for (const [key, prop] of Object.entries(schema.properties)) {
properties[key] = { ...prop }
}
return {
type: 'object' as const,
properties,
required: schema.required || [],
}
}
function adaptTool(tool: ToolDefinition, dataProvider: ToolDataProvider): AgentTool<any, unknown> {
return {
name: tool.name,
label: tool.name,
description: tool.description,
parameters: convertJsonSchemaToParameters(tool.inputSchema) as any,
async execute(_toolCallId: string, params: unknown): Promise<AgentToolResult<unknown>> {
const context: ToolExecutionContext = {
sessionId: 'real-llm-chart-flow',
locale: 'en-US',
dataProvider,
}
const result = await tool.handler((params ?? {}) as Record<string, unknown>, context)
return {
content: [{ type: 'text', text: result.content }],
details: {
...(typeof result.data === 'object' && result.data !== null && !Array.isArray(result.data)
? result.data
: {}),
...(result.chart ? { chart: result.chart } : {}),
},
}
},
}
}
function getChartPayloads(events: AgentCoreEvent[]): ChartPayload[] {
return events
.filter((event) => event.type === 'tool_end' && event.toolName === 'render_chart')
.map((event) => (event.toolResult as { details?: { chart?: ChartPayload } }).details?.chart)
.filter((chart): chart is ChartPayload => !!chart)
}
describe('real external LLM chart flow', () => {
it(
'asks a real model to generate two chart payloads from real chat data',
{ skip: !shouldRunRealLlmE2E },
async () => {
const apiKey = process.env.CHATLAB_REAL_LLM_API_KEY || process.env.OPENAI_API_KEY
assert.ok(apiKey, 'Set CHATLAB_REAL_LLM_API_KEY or OPENAI_API_KEY to run the real LLM chart E2E test')
const provider = process.env.CHATLAB_REAL_LLM_PROVIDER || 'openai'
const model = process.env.CHATLAB_REAL_LLM_MODEL || 'gpt-4.1-mini'
const baseUrl = process.env.CHATLAB_REAL_LLM_BASE_URL || undefined
const piModel = buildPiModel({ provider, model, baseUrl })
const dir = createTempDir()
const dbPath = path.join(dir, 'chat.db')
const nativeBinding = resolveNativeBinding()
const db = openBetterSqliteDatabase(dbPath, { nativeBinding })
try {
seedChatDb(db)
const dataProvider = new CoreDataProvider(db)
const tools = [adaptTool(schemaTool, dataProvider), adaptTool(renderChartTool, dataProvider)]
const events: AgentCoreEvent[] = []
const chartPrompt = getChartCapabilitySkill('en-US').prompt
const result = await runAgentCore({
piModel,
apiKey,
systemPrompt: `${chartPrompt}
Test-specific requirements:
- Use get_schema if you need table names or columns.
- Produce exactly two render_chart calls.
- Do not make exploratory, retry, or debugging render_chart calls beyond those two charts.
- The pie chart must include only Alice and Bob and must exclude Cara.
- The heatmap must include only Alice and Bob and use hour on x, member name on y, and message count as value.
- Use the data from June 1-2, 2026 inclusive.
- The database stores Unix seconds in message.ts. Use this exact UTC range:
- start: 1780272000
- end: 1780444799
- Member display names in chat messages are stored as Alice, Bob, and Cara in message.sender_group_nickname.`,
tools,
history: [],
userMessage:
'Create exactly two charts from this chat data: first a pie chart comparing Alice and Bob message share, then a heatmap showing Alice and Bob message density by hour. Briefly explain both.',
maxToolRounds: 4,
steerMessage: 'Explain the generated charts briefly. Do not call more tools.',
thinkingLevel: 'off',
onEvent: (event) => events.push(event),
})
assert.equal(result.error, undefined)
const charts = getChartPayloads(events)
assert.equal(charts.length, 2, `expected exactly two chart payloads, got ${charts.length}`)
const chartsByType = new Map(charts.map((chart) => [chart.spec.type, chart]))
const pie = chartsByType.get('pie')
const heatmap = chartsByType.get('heatmap')
assert.ok(pie, 'expected a pie chart payload')
assert.ok(heatmap, 'expected a heatmap chart payload')
assert.deepEqual(new Set(pie.data.labels), new Set(['Alice', 'Bob']))
assert.equal(
pie.data.values.reduce((sum, value) => sum + value, 0),
7
)
assert.ok(!heatmap.data.yLabels.includes('Cara'), 'heatmap should exclude Cara')
assert.ok(heatmap.data.yLabels.includes('Alice'), 'heatmap should include Alice')
assert.ok(heatmap.data.yLabels.includes('Bob'), 'heatmap should include Bob')
const heatmapHours = new Set(heatmap.data.xLabels.map((label) => Number(label)))
assert.ok(heatmapHours.has(9), 'heatmap should include hour 9')
assert.ok(heatmap.data.data.length > 0, 'heatmap should include density cells')
const finalContent = events
.filter((event) => event.type === 'content')
.map((event) => event.content)
.join('')
assert.match(finalContent, /Alice|Bob|pie|heatmap/i)
} finally {
db.close()
rmSync(dir, { recursive: true, force: true, maxRetries: 5, retryDelay: 50 })
}
}
)
})