feat(dependencies): update ai-sdk packages and improve logging

- Upgraded `@ai-sdk/gateway` to version 1.0.8 and `@ai-sdk/provider-utils` to version 3.0.4 in yarn.lock for enhanced functionality. - Updated `ai` dependency in package.json to version ^5.0.16 for better compatibility. - Added logging functionality in `AiSdkToChunkAdapter` to track chunk types and improve debugging. - Refactored plugin imports to streamline code and enhance readability. - Removed unnecessary console logs in `searchOrchestrationPlugin` to clean up the codebase.
2025-08-19 16:03:51 +08:00
parent 179b7af9bd
commit d4da7d817d
8 changed files with 55 additions and 67 deletions
@@ -4,11 +4,14 @@
 */

 import { TextStreamPart, ToolSet } from '@cherrystudio/ai-core'
+import { loggerService } from '@logger'
 import { BaseTool, WebSearchResults, WebSearchSource } from '@renderer/types'
 import { Chunk, ChunkType } from '@renderer/types/chunk'

 import { ToolCallChunkHandler } from './handleToolCallChunk'

+const logger = loggerService.withContext('AiSdkToChunkAdapter')
+
 export interface CherryStudioChunk {
  type: 'text-delta' | 'text-complete' | 'tool-call' | 'tool-result' | 'finish' | 'error'
  text?: string
@@ -83,6 +86,7 @@ export class AiSdkToChunkAdapter {
    chunk: TextStreamPart<any>,
    final: { text: string; reasoningContent: string; webSearchResults: any[]; reasoningId: string }
  ) {
+    logger.info(`AI SDK chunk type: ${chunk.type}`, chunk)
    switch (chunk.type) {
      // === 文本相关事件 ===
      case 'text-start':
@@ -105,12 +109,12 @@ export class AiSdkToChunkAdapter {
        final.text = ''
        break
      case 'reasoning-start':
-        if (final.reasoningId !== chunk.id) {
-          final.reasoningId = chunk.id
-          this.onChunk({
-            type: ChunkType.THINKING_START
-          })
-        }
+        // if (final.reasoningId !== chunk.id) {
+        final.reasoningId = chunk.id
+        this.onChunk({
+          type: ChunkType.THINKING_START
+        })
+        // }
        break
      case 'reasoning-delta':
        final.reasoningContent += chunk.text || ''
@@ -171,7 +175,7 @@ export class AiSdkToChunkAdapter {
      //   break

      case 'finish-step': {
-        const { providerMetadata } = chunk
+        const { providerMetadata, finishReason } = chunk
        // googel web search
        if (providerMetadata?.google?.groundingMetadata) {
          this.onChunk({
@@ -182,6 +186,9 @@ export class AiSdkToChunkAdapter {
            }
          })
        }
+        if (finishReason === 'tool-calls') {
+          this.onChunk({ type: ChunkType.LLM_RESPONSE_CREATED })
+        }
        // else {
        //   this.onChunk({
        //     type: ChunkType.LLM_WEB_SEARCH_COMPLETE,
@@ -1,6 +1,6 @@
 import { AiPlugin } from '@cherrystudio/ai-core'
 import { createPromptToolUsePlugin, webSearchPlugin } from '@cherrystudio/ai-core/built-in/plugins'
-import store from '@renderer/store'
+import { getEnableDeveloperMode } from '@renderer/hooks/useSettings'
 import { Assistant } from '@renderer/types'

 import { AiSdkMiddlewareConfig } from '../middleware/AiSdkMiddlewareBuilder'
@@ -16,7 +16,7 @@ export function buildPlugins(
 ): AiPlugin[] {
  const plugins: AiPlugin[] = []

-  if (middlewareConfig.topicId && store.getState().settings.enableDeveloperMode) {
+  if (middlewareConfig.topicId && getEnableDeveloperMode()) {
    // 0. 添加 telemetry 插件
    plugins.push(
      createTelemetryPlugin({
@@ -247,8 +247,6 @@ export const searchOrchestrationPlugin = (assistant: Assistant, topicId: string)
  const userMessages: { [requestId: string]: ModelMessage } = {}
  let currentContext: AiRequestContext | null = null

-  console.log('searchOrchestrationPlugin', assistant)
-
  return definePlugin({
    name: 'search-orchestration',
    enforce: 'pre', // 确保在其他插件之前执行
@@ -264,15 +262,14 @@ export const searchOrchestrationPlugin = (assistant: Assistant, topicId: string)
     * 🔍 Step 1: 意图识别阶段
     */
    onRequestStart: async (context: AiRequestContext) => {
-      console.log('onRequestStart', context)
      if (context.isAnalyzing) return
-      // console.log('🧠 [SearchOrchestration] Starting intent analysis...', context.requestId)
+
+      // 没开启任何搜索则不进行意图分析
+      if (!(assistant.webSearchProviderId || assistant.knowledge_bases?.length || assistant.enableMemory)) return

      try {
        const messages = context.originalParams.messages
-        // console.log('🧠 [SearchOrchestration]', context.isAnalyzing)
        if (!messages || messages.length === 0) {
-          console.log('🧠 [SearchOrchestration] No messages found, skipping analysis')
          return
        }

@@ -283,10 +280,8 @@ export const searchOrchestrationPlugin = (assistant: Assistant, topicId: string)
        userMessages[context.requestId] = lastUserMessage

        // 判断是否需要各种搜索
-        const knowledgeBaseIds = assistant.knowledge_bases?.map((base) => base.id)
-        // console.log('knowledgeBaseIds', knowledgeBaseIds)
+        const knowledgeBaseIds = assistant.knowledge_bases.map((base) => base.id)
        const hasKnowledgeBase = !isEmpty(knowledgeBaseIds)
-        // console.log('hasKnowledgeBase', hasKnowledgeBase)
        const knowledgeRecognition = assistant.knowledgeRecognition || 'on'
        const globalMemoryEnabled = selectGlobalMemoryEnabled(store.getState())

@@ -294,11 +289,6 @@ export const searchOrchestrationPlugin = (assistant: Assistant, topicId: string)
        const shouldKnowledgeSearch = hasKnowledgeBase && knowledgeRecognition === 'on'
        const shouldMemorySearch = globalMemoryEnabled && assistant.enableMemory

-        // console.log('🧠 [SearchOrchestration] Search capabilities:', {
-        //   shouldWebSearch,
-        //   hasKnowledgeBase,
-        //   shouldMemorySearch
-        // })
        // 执行意图分析
        if (shouldWebSearch || hasKnowledgeBase) {
          const analysisResult = await analyzeSearchIntent(lastUserMessage, assistant, {
@@ -84,6 +84,7 @@ const ChooseTool = (toolResponse: MCPToolResponse): { label: React.ReactNode; bo
 export default function MessageTool({ block }: Props) {
  // FIXME: 语义错误，这里已经不是 MCP tool 了
  const toolResponse = block.metadata?.rawMcpToolResponse
+
  if (!toolResponse) return null

  const toolRenderer = ChooseTool(toolResponse)
@@ -9,6 +9,7 @@ import { AiSdkMiddlewareConfig } from '@renderer/aiCore/middleware/AiSdkMiddlewa
 import { buildStreamTextParams } from '@renderer/aiCore/transformParameters'
 import { isDedicatedImageGenerationModel, isEmbeddingModel } from '@renderer/config/models'
 import { getStoreSetting } from '@renderer/hooks/useSettings'
+import { getEnableDeveloperMode } from '@renderer/hooks/useSettings'
 import i18n from '@renderer/i18n'
 import store from '@renderer/store'
 import { Assistant, MCPServer, MCPTool, Model, Provider } from '@renderer/types'
@@ -156,30 +157,9 @@ export async function fetchChatCompletion({
  // }
  // --- Call AI Completions ---
  onChunkReceived({ type: ChunkType.LLM_RESPONSE_CREATED })
-
+  const enableDeveloperMode = getEnableDeveloperMode()
  // 在 AI SDK 调用时设置正确的 OpenTelemetry 上下文
-  if (topicId) {
-    logger.info('Attempting to set OpenTelemetry context', { topicId })
-    const { currentSpan } = await import('@renderer/services/SpanManagerService')
-
-    const parentSpan = currentSpan(topicId, modelId)
-    logger.info('Parent span lookup result', {
-      topicId,
-      hasParentSpan: !!parentSpan,
-      parentSpanId: parentSpan?.spanContext().spanId,
-      parentTraceId: parentSpan?.spanContext().traceId
-    })
-
-    if (parentSpan) {
-      logger.info('Found parent span, using completionsForTrace for proper span hierarchy', {
-        topicId,
-        parentSpanId: parentSpan.spanContext().spanId,
-        parentTraceId: parentSpan.spanContext().traceId
-      })
-    } else {
-      logger.warn('No parent span found for topicId, using completionsForTrace anyway', { topicId })
-    }
-
+  if (topicId && enableDeveloperMode) {
    // 使用带trace支持的completions方法，它会自动创建子span并关联到父span
    await AI.completionsForTrace(modelId, aiSdkParams, {
      ...middlewareConfig,
@@ -188,14 +168,8 @@ export async function fetchChatCompletion({
      callType: 'chat'
    })
  } else {
-    logger.warn('No topicId provided, using regular completions')
-    // 没有topicId时，禁用telemetry以避免警告
-    const configWithoutTelemetry = {
-      ...middlewareConfig,
-      topicId: undefined // 确保telemetryPlugin不会尝试查找span
-    }
    await AI.completions(modelId, aiSdkParams, {
-      ...configWithoutTelemetry,
+      ...middlewareConfig,
      assistant,
      callType: 'chat'
    })
@@ -23,6 +23,8 @@ export const createToolCallbacks = (deps: ToolCallbacksDependencies) => {

  return {
    onToolCallPending: (toolResponse: MCPToolResponse) => {
+      console.log('onToolCallPending', toolResponse)
+
      if (blockManager.hasInitialPlaceholder) {
        const changes = {
          type: MessageBlockType.TOOL,