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feat: Implement multi-dimensional cell data generation in CrosstabChat, enhancing AI task management and improving data processing for both rows and columns
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‎src/renderer/src/components/pages/crosstab/CrosstabChat.tsx‎

Lines changed: 235 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -9,7 +9,7 @@ import {
99

1010
import { useAppContext } from '../../../store/AppContext'
1111
import { createAIService } from '../../../services/aiService'
12-
import { PROMPT_TEMPLATES, extractJsonContent } from './CrosstabUtils'
12+
import { PROMPT_TEMPLATES, extractJsonContent, generateAxisCombinations, generateDimensionPath } from './CrosstabUtils'
1313
import { AITask } from '../../../types'
1414
import { v4 as uuidv4 } from 'uuid'
1515
import StepFlow from './StepFlow'
@@ -84,8 +84,123 @@ export default function CrosstabChat({ chatId }: CrosstabChatProps) {
8484

8585
// 生成该列的所有单元格数据
8686
try {
87-
// 这里可以调用新的多维度单元格生成逻辑
88-
// 暂时显示成功消息
87+
// 使用已经导入的函数
88+
const verticalCombinations = generateAxisCombinations(chat.crosstabData.metadata.verticalDimensions)
89+
const aiService = createAIService(llmConfig)
90+
91+
const updatedTableData = { ...chat.crosstabData.tableData }
92+
93+
// 为该列的每个单元格生成数据
94+
for (const vCombination of verticalCombinations) {
95+
const rowPath = generateDimensionPath(vCombination)
96+
const cellKey = `${columnPath}|${rowPath}`
97+
98+
const taskId = uuidv4()
99+
const task: AITask = {
100+
id: taskId,
101+
requestId: aiService.id,
102+
type: 'crosstab_cell',
103+
status: 'running',
104+
title: '生成单元格数据',
105+
description: `生成单元格 ${columnPath} × ${rowPath} 的数据`,
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chatId,
107+
modelId: llmConfig.id,
108+
startTime: Date.now()
109+
}
110+
111+
dispatch({
112+
type: 'ADD_AI_TASK',
113+
payload: { task }
114+
})
115+
116+
try {
117+
const prompt = PROMPT_TEMPLATES.cell_values
118+
.replace('[METADATA_JSON]', JSON.stringify(chat.crosstabData.metadata, null, 2))
119+
.replace('[HORIZONTAL_PATH]', columnPath)
120+
.replace('[VERTICAL_PATH]', rowPath)
121+
.replace('[VALUE_DIMENSIONS]', JSON.stringify(chat.crosstabData.metadata.valueDimensions, null, 2))
122+
123+
const response = await new Promise<string>((resolve, reject) => {
124+
aiService.sendMessage(
125+
[{ id: 'temp', role: 'user', content: prompt, timestamp: Date.now() }],
126+
{
127+
onChunk: () => {},
128+
onComplete: (response) => resolve(response),
129+
onError: (error) => reject(error)
130+
}
131+
)
132+
})
133+
134+
const jsonContent = extractJsonContent(response)
135+
const cellValues = JSON.parse(jsonContent)
136+
137+
// 处理AI生成的数据格式
138+
const processedCellValues: { [key: string]: string } = {}
139+
if (chat.crosstabData.metadata.valueDimensions.length > 0) {
140+
const valueDimensions = chat.crosstabData.metadata.valueDimensions
141+
142+
const keys = Object.keys(cellValues)
143+
const hasGenericKeys = keys.some(key => key.match(/^value\d+$/))
144+
145+
if (hasGenericKeys) {
146+
valueDimensions.forEach((dimension, index) => {
147+
const genericKey = `value${index + 1}`
148+
if (cellValues[genericKey]) {
149+
processedCellValues[dimension.id] = cellValues[genericKey]
150+
}
151+
})
152+
} else {
153+
valueDimensions.forEach(dimension => {
154+
if (cellValues[dimension.id]) {
155+
processedCellValues[dimension.id] = cellValues[dimension.id]
156+
}
157+
})
158+
}
159+
160+
if (Object.keys(processedCellValues).length === 0 && Object.keys(cellValues).length > 0) {
161+
const firstDimension = valueDimensions[0]
162+
const firstValue = Object.values(cellValues)[0]
163+
processedCellValues[firstDimension.id] = firstValue as string
164+
}
165+
}
166+
167+
updatedTableData[cellKey] = processedCellValues
168+
169+
dispatch({
170+
type: 'UPDATE_AI_TASK',
171+
payload: {
172+
taskId,
173+
updates: {
174+
status: 'completed',
175+
endTime: Date.now()
176+
}
177+
}
178+
})
179+
} catch (error) {
180+
dispatch({
181+
type: 'UPDATE_AI_TASK',
182+
payload: {
183+
taskId,
184+
updates: {
185+
status: 'failed',
186+
endTime: Date.now(),
187+
error: error instanceof Error ? error.message : 'Unknown error'
188+
}
189+
}
190+
})
191+
console.error(`单元格 ${cellKey} 生成失败:`, error)
192+
}
193+
}
194+
195+
// 批量更新表格数据
196+
dispatch({
197+
type: 'UPDATE_CROSSTAB_DATA',
198+
payload: {
199+
chatId,
200+
data: { tableData: updatedTableData }
201+
}
202+
})
203+
89204
message.success(`列 "${columnPath}" 数据生成完成`)
90205
} catch (error) {
91206
console.error('列数据生成失败:', error)
@@ -124,8 +239,123 @@ export default function CrosstabChat({ chatId }: CrosstabChatProps) {
124239

125240
// 生成该行的所有单元格数据
126241
try {
127-
// 这里可以调用新的多维度单元格生成逻辑
128-
// 暂时显示成功消息
242+
// 使用已经导入的函数
243+
const horizontalCombinations = generateAxisCombinations(chat.crosstabData.metadata.horizontalDimensions)
244+
const aiService = createAIService(llmConfig)
245+
246+
const updatedTableData = { ...chat.crosstabData.tableData }
247+
248+
// 为该行的每个单元格生成数据
249+
for (const hCombination of horizontalCombinations) {
250+
const columnPath = generateDimensionPath(hCombination)
251+
const cellKey = `${columnPath}|${rowPath}`
252+
253+
const taskId = uuidv4()
254+
const task: AITask = {
255+
id: taskId,
256+
requestId: aiService.id,
257+
type: 'crosstab_cell',
258+
status: 'running',
259+
title: '生成单元格数据',
260+
description: `生成单元格 ${columnPath} × ${rowPath} 的数据`,
261+
chatId,
262+
modelId: llmConfig.id,
263+
startTime: Date.now()
264+
}
265+
266+
dispatch({
267+
type: 'ADD_AI_TASK',
268+
payload: { task }
269+
})
270+
271+
try {
272+
const prompt = PROMPT_TEMPLATES.cell_values
273+
.replace('[METADATA_JSON]', JSON.stringify(chat.crosstabData.metadata, null, 2))
274+
.replace('[HORIZONTAL_PATH]', columnPath)
275+
.replace('[VERTICAL_PATH]', rowPath)
276+
.replace('[VALUE_DIMENSIONS]', JSON.stringify(chat.crosstabData.metadata.valueDimensions, null, 2))
277+
278+
const response = await new Promise<string>((resolve, reject) => {
279+
aiService.sendMessage(
280+
[{ id: 'temp', role: 'user', content: prompt, timestamp: Date.now() }],
281+
{
282+
onChunk: () => {},
283+
onComplete: (response) => resolve(response),
284+
onError: (error) => reject(error)
285+
}
286+
)
287+
})
288+
289+
const jsonContent = extractJsonContent(response)
290+
const cellValues = JSON.parse(jsonContent)
291+
292+
// 处理AI生成的数据格式
293+
const processedCellValues: { [key: string]: string } = {}
294+
if (chat.crosstabData.metadata.valueDimensions.length > 0) {
295+
const valueDimensions = chat.crosstabData.metadata.valueDimensions
296+
297+
const keys = Object.keys(cellValues)
298+
const hasGenericKeys = keys.some(key => key.match(/^value\d+$/))
299+
300+
if (hasGenericKeys) {
301+
valueDimensions.forEach((dimension, index) => {
302+
const genericKey = `value${index + 1}`
303+
if (cellValues[genericKey]) {
304+
processedCellValues[dimension.id] = cellValues[genericKey]
305+
}
306+
})
307+
} else {
308+
valueDimensions.forEach(dimension => {
309+
if (cellValues[dimension.id]) {
310+
processedCellValues[dimension.id] = cellValues[dimension.id]
311+
}
312+
})
313+
}
314+
315+
if (Object.keys(processedCellValues).length === 0 && Object.keys(cellValues).length > 0) {
316+
const firstDimension = valueDimensions[0]
317+
const firstValue = Object.values(cellValues)[0]
318+
processedCellValues[firstDimension.id] = firstValue as string
319+
}
320+
}
321+
322+
updatedTableData[cellKey] = processedCellValues
323+
324+
dispatch({
325+
type: 'UPDATE_AI_TASK',
326+
payload: {
327+
taskId,
328+
updates: {
329+
status: 'completed',
330+
endTime: Date.now()
331+
}
332+
}
333+
})
334+
} catch (error) {
335+
dispatch({
336+
type: 'UPDATE_AI_TASK',
337+
payload: {
338+
taskId,
339+
updates: {
340+
status: 'failed',
341+
endTime: Date.now(),
342+
error: error instanceof Error ? error.message : 'Unknown error'
343+
}
344+
}
345+
})
346+
console.error(`单元格 ${cellKey} 生成失败:`, error)
347+
}
348+
}
349+
350+
// 批量更新表格数据
351+
dispatch({
352+
type: 'UPDATE_CROSSTAB_DATA',
353+
payload: {
354+
chatId,
355+
data: { tableData: updatedTableData }
356+
}
357+
})
358+
129359
message.success(`行 "${rowPath}" 数据生成完成`)
130360
} catch (error) {
131361
console.error('行数据生成失败:', error)

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