Files
ChatLab/tests/chart-runtime/agent-chart-flow.test.mts

382 lines
14 KiB
TypeScript

import { describe, it } from 'node:test'
import assert from 'node:assert/strict'
import {
createAssistantMessageEventStream,
type AssistantMessage,
type Context,
type Message,
type Model,
type ToolCall,
type Usage,
} from '@earendil-works/pi-ai'
import type { AgentTool, AgentToolResult } from '@earendil-works/pi-agent-core'
import {
renderChartTool,
type ToolDataProvider,
type ToolDefinition,
type ToolExecutionContext,
} from '@openchatlab/tools'
import type { ChartPayload } from '@openchatlab/core'
import { runAgentCore, type AgentCoreEvent } from '../../packages/node-runtime/src/ai/agent'
function emptyUsage(): Usage {
return {
input: 0,
output: 0,
cacheRead: 0,
cacheWrite: 0,
totalTokens: 0,
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
}
}
function assistantMessage(
content: AssistantMessage['content'],
stopReason: AssistantMessage['stopReason']
): AssistantMessage {
return {
role: 'assistant',
content,
api: 'openai-completions',
provider: 'chatlab-test',
model: 'fake-chart-model',
usage: emptyUsage(),
stopReason,
timestamp: Date.now(),
}
}
function createToolCallsStream(toolCalls: ToolCall[]) {
const stream = createAssistantMessageEventStream()
const partialStart = assistantMessage([], 'toolUse')
const finalMessage = assistantMessage(toolCalls, 'toolUse')
stream.push({ type: 'start', partial: partialStart })
toolCalls.forEach((toolCall, contentIndex) => {
stream.push({ type: 'toolcall_start', contentIndex, partial: finalMessage })
stream.push({
type: 'toolcall_delta',
contentIndex,
delta: JSON.stringify(toolCall.arguments),
partial: finalMessage,
})
stream.push({ type: 'toolcall_end', contentIndex, toolCall, partial: finalMessage })
})
stream.push({ type: 'done', reason: 'toolUse', message: finalMessage })
return stream
}
function createToolCallStream(toolCall: ToolCall) {
return createToolCallsStream([toolCall])
}
function createTextStream(text: string) {
const stream = createAssistantMessageEventStream()
const partialStart = assistantMessage([], 'stop')
const finalMessage = assistantMessage([{ type: 'text', text }], 'stop')
stream.push({ type: 'start', partial: partialStart })
stream.push({ type: 'text_start', contentIndex: 0, partial: partialStart })
stream.push({ type: 'text_delta', contentIndex: 0, delta: text, partial: finalMessage })
stream.push({ type: 'text_end', contentIndex: 0, content: text, partial: finalMessage })
stream.push({ type: 'done', reason: 'stop', message: finalMessage })
return stream
}
function hasToolResult(messages: Message[]): boolean {
return messages.some((message) => message.role === 'toolResult' && message.toolName === 'render_chart')
}
function countToolResults(messages: Message[]): number {
return messages.filter((message) => message.role === 'toolResult' && message.toolName === 'render_chart').length
}
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 adaptRenderChartTool(dataProvider: ToolDataProvider): AgentTool<any, unknown> {
return {
name: renderChartTool.name,
label: renderChartTool.name,
description: renderChartTool.description,
parameters: convertJsonSchemaToParameters(renderChartTool.inputSchema) as any,
async execute(_toolCallId: string, params: unknown): Promise<AgentToolResult<unknown>> {
const context: ToolExecutionContext = {
sessionId: 'offline-agent-chart-flow',
locale: 'en-US',
dataProvider,
}
const result = await renderChartTool.handler((params ?? {}) as Record<string, unknown>, context)
return {
content: [{ type: 'text', text: result.content }],
details: {
...(typeof result.data === 'object' && result.data !== null ? result.data : {}),
...(result.chart ? { chart: result.chart } : {}),
},
}
},
}
}
describe('offline Agent chart flow', () => {
it('turns a natural-language chart request into a render_chart tool result and final answer', async () => {
const requestedSql: string[] = []
const dataProvider: ToolDataProvider = {
async executeParameterizedSql(sql, params) {
requestedSql.push(sql)
assert.match(sql, /JOIN member/i)
assert.match(sql, /@memberA/)
assert.deepEqual(params, { memberA: 'Alice', memberB: 'Bob', startTs: 1780272000, endTs: 1780444800 })
return [
{ day: '2026-06-01', member_name: 'Alice', message_count: 2 },
{ day: '2026-06-01', member_name: 'Bob', message_count: 1 },
{ day: '2026-06-02', member_name: 'Alice', message_count: 2 },
{ day: '2026-06-02', member_name: 'Bob', message_count: 2 },
]
},
async getSchema() {
return []
},
} as Partial<ToolDataProvider> as ToolDataProvider
const tools = [adaptRenderChartTool(dataProvider)]
const streamFn = (_model: Model<any>, context: Context) => {
const userMessages = context.messages.filter((message) => message.role === 'user')
const latestUser = userMessages[userMessages.length - 1]
const userText = Array.isArray(latestUser?.content)
? latestUser.content.map((part) => (part.type === 'text' ? part.text : '')).join('\n')
: latestUser?.content || ''
assert.match(userText, /Alice/)
assert.match(userText, /Bob/)
assert.match(userText, /line/i)
if (!hasToolResult(context.messages)) {
return createToolCallStream({
type: 'toolCall',
id: 'call_chart_1',
name: 'render_chart',
arguments: {
sql: `
SELECT date(msg.ts, 'unixepoch') AS day,
COALESCE(m.group_nickname, m.account_name, m.platform_id) AS member_name,
COUNT(*) AS message_count
FROM message msg
JOIN member m ON m.id = msg.sender_id
WHERE COALESCE(m.group_nickname, m.account_name, m.platform_id) IN (@memberA, @memberB)
AND msg.ts >= @startTs AND msg.ts < @endTs
GROUP BY day, m.id
ORDER BY day ASC, member_name ASC
`,
params: { memberA: 'Alice', memberB: 'Bob', startTs: 1780272000, endTs: 1780444800 },
chartSpec: {
version: 1,
type: 'line',
title: 'Alice vs Bob daily message trend',
encoding: { x: 'day', y: 'message_count', series: 'member_name' },
filters: { members: [{ name: 'Alice' }, { name: 'Bob' }] },
unit: 'messages',
},
},
})
}
return createTextStream('Alice stayed ahead on both days, while Bob caught up on June 2.')
}
const events: AgentCoreEvent[] = []
const result = await runAgentCore({
piModel: {
id: 'fake-chart-model',
provider: 'chatlab-test',
api: 'openai-completions',
} as Model<any>,
apiKey: 'test-key',
systemPrompt: 'Use render_chart for chart requests.',
tools,
history: [],
userMessage: 'Please draw a line chart comparing Alice and Bob message counts by day.',
maxToolRounds: 3,
steerMessage: 'Please explain the chart briefly.',
streamFn,
onEvent: (event) => events.push(event),
})
assert.equal(result.error, undefined)
assert.deepEqual(result.toolsUsed, ['render_chart'])
assert.equal(result.toolRounds, 1)
assert.equal(requestedSql.length, 1)
const toolEnd = events.find((event) => event.type === 'tool_end' && event.toolName === 'render_chart')
assert.ok(toolEnd && 'toolResult' in toolEnd, 'expected render_chart tool_end event')
const chart = (toolEnd.toolResult as { details?: { chart?: ChartPayload } }).details?.chart
assert.ok(chart, 'expected chart payload in render_chart tool result details')
assert.equal(chart.spec.type, 'line')
assert.deepEqual(chart.data, {
labels: ['2026-06-01', '2026-06-02'],
values: [2, 2],
series: [
{ name: 'Alice', values: [2, 2] },
{ name: 'Bob', values: [1, 2] },
],
})
const content = events
.filter((event) => event.type === 'content')
.map((event) => event.content)
.join('')
assert.match(content, /Bob caught up/)
})
it('runs multiple render_chart calls when the user asks for two charts', async () => {
const requestedSql: string[] = []
const dataProvider: ToolDataProvider = {
async executeParameterizedSql(sql, params) {
requestedSql.push(sql)
if (sql.includes('selected_member_share_source')) {
assert.deepEqual(params, { memberA: 'Alice', memberB: 'Bob' })
return [
{ member_name: 'Alice', message_count: 4 },
{ member_name: 'Bob', message_count: 3 },
]
}
if (sql.includes('member_hour_density_source')) {
assert.deepEqual(params, { memberA: 'Alice', memberB: 'Bob' })
return [
{ hour: '09', member_name: 'Alice', message_count: 2 },
{ hour: '10', member_name: 'Alice', message_count: 2 },
{ hour: '09', member_name: 'Bob', message_count: 1 },
{ hour: '10', member_name: 'Bob', message_count: 2 },
]
}
throw new Error(`unexpected SQL: ${sql}`)
},
async getSchema() {
return []
},
} as Partial<ToolDataProvider> as ToolDataProvider
const tools = [adaptRenderChartTool(dataProvider)]
const streamFn = (_model: Model<any>, context: Context) => {
const userMessages = context.messages.filter((message) => message.role === 'user')
const latestUser = userMessages[userMessages.length - 1]
const userText = Array.isArray(latestUser?.content)
? latestUser.content.map((part) => (part.type === 'text' ? part.text : '')).join('\n')
: latestUser?.content || ''
assert.match(userText, /two charts/i)
assert.match(userText, /pie/i)
assert.match(userText, /heatmap/i)
if (countToolResults(context.messages) < 2) {
return createToolCallsStream([
{
type: 'toolCall',
id: 'call_chart_pie',
name: 'render_chart',
arguments: {
sql: `
WITH selected_member_share_source AS (
SELECT @memberA AS member_name, 4 AS message_count
UNION ALL
SELECT @memberB AS member_name, 3 AS message_count
)
SELECT member_name, message_count
FROM selected_member_share_source
`,
params: { memberA: 'Alice', memberB: 'Bob' },
chartSpec: {
version: 1,
type: 'pie',
title: 'Selected members message share',
encoding: { label: 'member_name', value: 'message_count' },
},
},
},
{
type: 'toolCall',
id: 'call_chart_heatmap',
name: 'render_chart',
arguments: {
sql: `
WITH member_hour_density_source AS (
SELECT '09' AS hour, @memberA AS member_name, 2 AS message_count
UNION ALL
SELECT '10' AS hour, @memberA AS member_name, 2 AS message_count
UNION ALL
SELECT '09' AS hour, @memberB AS member_name, 1 AS message_count
UNION ALL
SELECT '10' AS hour, @memberB AS member_name, 2 AS message_count
)
SELECT hour, member_name, message_count
FROM member_hour_density_source
`,
params: { memberA: 'Alice', memberB: 'Bob' },
chartSpec: {
version: 1,
type: 'heatmap',
title: 'Selected members hour density',
encoding: { x: 'hour', y: 'member_name', value: 'message_count' },
},
},
},
])
}
return createTextStream('Here are the requested pie chart and heatmap.')
}
const events: AgentCoreEvent[] = []
const result = await runAgentCore({
piModel: {
id: 'fake-chart-model',
provider: 'chatlab-test',
api: 'openai-completions',
} as Model<any>,
apiKey: 'test-key',
systemPrompt: 'Use render_chart for chart requests.',
tools,
history: [],
userMessage: 'Please generate two charts: a pie chart for Alice and Bob, plus a heatmap by hour.',
maxToolRounds: 3,
steerMessage: 'Please explain both charts briefly.',
streamFn,
onEvent: (event) => events.push(event),
})
assert.equal(result.error, undefined)
assert.deepEqual(result.toolsUsed, ['render_chart', 'render_chart'])
assert.equal(result.toolRounds, 1)
assert.equal(requestedSql.length, 2)
const chartPayloads = 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)
assert.equal(chartPayloads.length, 2)
const chartsByType = new Map(chartPayloads.map((chart) => [chart.spec.type, chart]))
assert.deepEqual([...chartsByType.keys()].sort(), ['heatmap', 'pie'])
assert.deepEqual(chartsByType.get('pie')?.data, { labels: ['Alice', 'Bob'], values: [4, 3] })
assert.deepEqual(chartsByType.get('heatmap')?.data, {
xLabels: ['09', '10'],
yLabels: ['Alice', 'Bob'],
data: [
[0, 0, 2],
[1, 0, 2],
[0, 1, 1],
[1, 1, 2],
],
})
const content = events
.filter((event) => event.type === 'content')
.map((event) => event.content)
.join('')
assert.match(content, /pie chart and heatmap/)
})
})