feat: timeout in tool of chatbi lark

meta-d · Sep 29, 2024 · dce15d5 · dce15d5
1 parent 4fdf462
commit dce15d5
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Showing 5 changed files with 49 additions and 54 deletions.
diff --git a/packages/analytics/src/chatbi/conversation.ts b/packages/analytics/src/chatbi/conversation.ts
@@ -18,11 +18,9 @@ import {
 } from '@metad/ocap-core'
 import {
 	AgentState,
-	Copilot,
 	CopilotCheckpointSaver,
 	CopilotKnowledgeService,
 	createExampleFewShotPrompt,
-	createLLM,
 	createReactAgent,
 	createReferencesRetrieverTool,
 } from '@metad/server-ai'
@@ -51,8 +49,9 @@ import { createIndicatorTool } from './tools/indicator'
  * ChatBI conversation for Lark
  */
 export class ChatBIConversation implements IChatBIConversation {
+	static readonly toolCallTimeout = 30 * 1000 // 30s
+
 	private readonly logger = new Logger(ChatBIConversation.name)
-	static readonly toolCallTimeout = 10000
 	readonly commandName = 'chatbi'
 
 	public id: string = null
@@ -339,7 +338,7 @@ ${createAgentStepsInstructions(
 						if (isString(content) && content.startsWith('Error:')) {
 							this.logger.error(content)
 							const toolCallMessage = state.messages[state.messages.length - 2]
-							this.logger.debug((<ToolMessage>toolCallMessage).lc_kwargs)
+							this.logger.verbose((<ToolMessage>toolCallMessage).lc_kwargs)
 							return 'agent'
 						}
 
@@ -443,7 +442,7 @@ ${createAgentStepsInstructions(
 
 					if (content) {
 						verboseContent = content
-						this.logger.debug(`[ChatBI] [Graph]: verbose content`, verboseContent)
+						this.logger.debug(`[ChatBI] [Graph] verbose content: `, verboseContent)
 						// 对话结束时还有正在思考的消息，则意味着出现错误
 						if (['thinking', 'continuing', 'waiting'].includes(this.message?.status)) {
 							this.message.update({
@@ -462,7 +461,7 @@ ${createAgentStepsInstructions(
 			this.status = 'idle'
 
 		} catch (err: any) {
-			console.error(err)
+			this.logger.error(err)
 			this.status = 'error'
 			if (err instanceof ToolInputParsingException) {
 				this.chatContext.larkService.errorMessage(this.chatContext, err)

diff --git a/packages/analytics/src/chatbi/tools/answer.ts b/packages/analytics/src/chatbi/tools/answer.ts
@@ -31,7 +31,7 @@ import {
 	tryFixVariableSlicer,
 	workOutTimeRangeSlicers
 } from '@metad/ocap-core'
-import { race } from '@metad/server-common'
+import { getErrorMessage, race } from '@metad/server-common'
 import { firstValueFrom, Subject, takeUntil } from 'rxjs'
 import { ChatBIConversation } from '../conversation'
 import { ChatLarkMessage } from '../message'
@@ -63,52 +63,46 @@ export function createChatAnswerTool(context: ChatContext, larkContext: ChatBILa
 		async (answer): Promise<string> => {
 			logger.debug(`Execute copilot action 'answerQuestion':`, JSON.stringify(answer, null, 2))
 			try {
-				try {
-					// 限制总体超时时间
-					return await race(
-						ChatBIConversation.toolCallTimeout,
-						(async () => {
-							let entityType = null
-							if (answer.dataSettings) {
-								// Make sure datasource exists
-								const _dataSource = await dsCoreService._getDataSource(answer.dataSettings.dataSource)
-								const entity = await firstValueFrom(
-									dsCoreService.selectEntitySet(
-										answer.dataSettings.dataSource,
-										answer.dataSettings.entitySet
-									)
+				// 限制总体超时时间
+				return await race(
+					ChatBIConversation.toolCallTimeout,
+					(async () => {
+						let entityType = null
+						if (answer.dataSettings) {
+							// Make sure datasource exists
+							const _dataSource = await dsCoreService._getDataSource(answer.dataSettings.dataSource)
+							const entity = await firstValueFrom(
+								dsCoreService.selectEntitySet(
+									answer.dataSettings.dataSource,
+									answer.dataSettings.entitySet
 								)
-								entityType = entity.entityType
-							}
-
-							// Fetch data for chart or table or kpi
-							if (answer.dimensions?.length || answer.measures?.length) {
-								const { categoryMembers } = await drawChartMessage(
-									{ ...context, entityType: entityType || context.entityType },
-									conversation,
-									answer as ChatAnswer
-								)
-								// Max limit 20 members
-								const members = categoryMembers
-									? JSON.stringify(Object.values(categoryMembers).slice(0, 20))
-									: 'Empty'
+							)
+							entityType = entity.entityType
+						}
 
-								return `The analysis data has been displayed to the user. The dimension members involved in this data analysis are:
+						// Fetch data for chart or table or kpi
+						if (answer.dimensions?.length || answer.measures?.length) {
+							const { categoryMembers } = await drawChartMessage(
+								{ ...context, entityType: entityType || context.entityType },
+								conversation,
+								answer as ChatAnswer
+							)
+							// Max limit 20 members
+							const members = categoryMembers
+								? JSON.stringify(Object.values(categoryMembers).slice(0, 20))
+								: 'Empty'
+
+							return `The analysis data has been displayed to the user. The dimension members involved in this data analysis are:
 ${members}
 Please give more analysis suggestions about other dimensions or filter by dimensioin members, 3 will be enough.`
-							}
-
-							return `图表答案已经回复给用户了，请不要重复回答了。`
-						})()
-					)
-				} catch (err) {
-					throw new Error(
-						`Timeout in getting cube context (dataSource=${answer.dataSettings.dataSource}, cube=${answer.dataSettings.entitySet})`
-					)
-				}
+						}
+
+						return `图表答案已经回复给用户了，请不要重复回答了。`
+					})()
+				)
 			} catch (err) {
-				logger.error(err)
-				return `Error: ${err}。如果需要用户提供更多信息，请直接提醒用户。`
+				logger.debug(getErrorMessage(err))
+				return `Error: ${getErrorMessage(err)}; If more information is needed from the user, remind the user directly.`
 			}
 		},
 		{

diff --git a/packages/analytics/src/chatbi/tools/cube-context.ts b/packages/analytics/src/chatbi/tools/cube-context.ts
@@ -1,6 +1,6 @@
 import { tool } from '@langchain/core/tools'
 import { isEntitySet, markdownModelCube } from '@metad/ocap-core'
-import { race } from '@metad/server-common'
+import { getErrorMessage, race } from '@metad/server-common'
 import { firstValueFrom, switchMap } from 'rxjs'
 import { ChatBIModelService } from '../../chatbi-model/'
 import { ChatContext, GetCubesContextSchema } from '../types'
@@ -17,7 +17,7 @@ export function createCubeContextTool(context: ChatContext, modelService: ChatBI
 					(async () => {
 						let context = ''
 						for await (const item of cubes) {
-							logger.debug(`  get context for:`, item.modelId, item.name)
+							logger.debug(`  get context for (modelId=${item.modelId}, cube=${item.name})`)
 
 							let entityType = await conversation.getCubeCache(item.modelId, item.name)
 							if (!entityType) {
@@ -53,7 +53,9 @@ export function createCubeContextTool(context: ChatContext, modelService: ChatBI
 					})()
 				)
 			} catch (err) {
-				return 'Error:' + err.message
+				const errorInfo = 'Error: ' + getErrorMessage(err)
+				logger.debug(`Call getCubeContext: ` + errorInfo)
+				return errorInfo
 			}
 		},
 		{

diff --git a/packages/analytics/src/data-source/queries/handlers/olap-query.handler.ts b/packages/analytics/src/data-source/queries/handlers/olap-query.handler.ts
@@ -27,7 +27,7 @@ export class OlapQueryHandler implements IQueryHandler<DataSourceOlapQuery> {
 		const { id, sessionId, dataSourceId, body, forceRefresh, acceptLanguage } = query.input
 		const user = query.user
 
-		this.logger.debug(`Executing OLAP query [${id}] for dataSource: ${dataSourceId}`)
+		this.logger.verbose(`Executing OLAP query [${id}] for dataSource: ${dataSourceId}`)
 
 		let dataSource = await this.dsService.findOne(dataSourceId, {
 			relations: ['type', 'authentications']

diff --git a/packages/analytics/src/model/queries/handlers/olap-query.handler.ts b/packages/analytics/src/model/queries/handlers/olap-query.handler.ts
@@ -1,4 +1,4 @@
-import { ITryRequest, RequestContext } from '@metad/server-core'
+import { ITryRequest } from '@metad/server-core'
 import { Logger } from '@nestjs/common'
 import { ConfigService } from '@nestjs/config'
 import { IQueryHandler, QueryBus, QueryHandler } from '@nestjs/cqrs'
@@ -26,7 +26,7 @@ export class ModelOlapQueryHandler implements IQueryHandler<ModelOlapQuery> {
 		const { id, sessionId, modelId, body, forceRefresh, acceptLanguage } = query.input
 		const user = query.user
 
-		this.logger.debug(`Executing OLAP query [${id}] for model: ${modelId}`)
+		this.logger.verbose(`Executing OLAP query [${id}] for model: ${modelId}`)
 
 		let key = ''
 		const model = await this.semanticModelService.findOne(modelId, {