Feat/provider options and built-in tools (#10068)

* refactor(RuntimeExecutor, PluginEngine): streamline parameter handling and improve type definitions for model operations

- Updated parameter handling in RuntimeExecutor methods to use specific types for generate and stream functions.
- Refactored PluginEngine methods to enhance type safety and reduce redundancy in model resolution.
- Introduced new type definitions for generate and stream parameters in types.ts for better clarity and maintainability.
- Adjusted provider options mapping in buildProviderOptions to accommodate new provider types.

* feat(googleToolsPlugin): enhance Google tools integration and update dependencies

- Updated the `ai` package version to `5.0.38` and `@ai-sdk/gateway` to `1.0.20` in `package.json` and `yarn.lock`.
- Introduced `googleToolsPlugin` with improved parameter handling and configuration options for Google tools.
- Added support for `urlContext` in middleware configuration and plugin builder.
- Refactored web search tool to streamline response handling and citation formatting.
- Updated various service methods to include `enableUrlContext` capability.

* fix: update tool response handling and clean up unused code

- Modified the `processKnowledgeReferences` function to accept the full response object instead of just `knowledgeReferences`.
- Cleaned up the `searchOrchestrationPlugin` by removing unnecessary blank lines.
- Removed commented-out code in `telemetryPlugin` to improve readability.
- Updated `KnowledgeSearchTool` to streamline the execution flow and return results more efficiently.
- Adjusted `MessageKnowledgeSearch` components to reflect changes in the data structure returned from the knowledge search tool.
- Enhanced `MemorySearchTool` by simplifying error handling and removing redundant code.

* refactor: clean up KnowledgeSearchTool and WebSearchTool by removing commented-out code

- Removed unnecessary commented-out code in `KnowledgeSearchTool` and `WebSearchTool` to improve code readability and maintainability.
- Simplified the `processKnowledgeReferences` function by eliminating the console log statement for cleaner output.

* chore: bump version to 1.0.0-alpha.14 in aiCore package.json

* chore: update @ai-sdk/google-vertex to version 3.0.25 and add @ai-sdk/anthropic@2.0.15 to dependencies

- Bumped the version of `@ai-sdk/google-vertex` in `package.json` and `yarn.lock` to 3.0.25.
- Added `@ai-sdk/anthropic` version 2.0.15 to `yarn.lock` with updated dependencies.
- Refactored `parameterBuilder.ts` to integrate new tools from `@ai-sdk/google-vertex` for enhanced functionality.

package.json

@@ -91,7 +91,7 @@
     "@agentic/searxng": "^7.3.3",
     "@agentic/tavily": "^7.3.3",
     "@ai-sdk/amazon-bedrock": "^3.0.0",
-    "@ai-sdk/google-vertex": "^3.0.0",
+    "@ai-sdk/google-vertex": "^3.0.25",
     "@ai-sdk/mistral": "^2.0.0",
     "@ant-design/v5-patch-for-react-19": "^1.0.3",
     "@anthropic-ai/sdk": "^0.41.0",
@@ -202,7 +202,7 @@
     "@viz-js/lang-dot": "^1.0.5",
     "@viz-js/viz": "^3.14.0",
     "@xyflow/react": "^12.4.4",
-    "ai": "^5.0.29",
+    "ai": "^5.0.38",
     "antd": "patch:antd@npm%3A5.27.0#~/.yarn/patches/antd-npm-5.27.0-aa91c36546.patch",
     "archiver": "^7.0.1",
     "async-mutex": "^0.5.0",

packages/aiCore/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@cherrystudio/ai-core",
-  "version": "1.0.0-alpha.13",
+  "version": "1.0.0-alpha.14",
   "description": "Cherry Studio AI Core - Unified AI Provider Interface Based on Vercel AI SDK",
   "main": "dist/index.js",
   "module": "dist/index.mjs",

packages/aiCore/src/core/plugins/built-in/googleToolsPlugin/index.ts

@@ -0,0 +1,39 @@
+import { google } from '@ai-sdk/google'
+
+import { definePlugin } from '../../'
+import type { AiRequestContext } from '../../types'
+
+const toolNameMap = {
+  googleSearch: 'google_search',
+  urlContext: 'url_context',
+  codeExecution: 'code_execution'
+} as const
+
+type ToolConfigKey = keyof typeof toolNameMap
+type ToolConfig = { googleSearch?: boolean; urlContext?: boolean; codeExecution?: boolean }
+
+export const googleToolsPlugin = (config?: ToolConfig) =>
+  definePlugin({
+    name: 'googleToolsPlugin',
+    transformParams: <T>(params: T, context: AiRequestContext): T => {
+      const { providerId } = context
+      if (providerId === 'google' && config) {
+        if (typeof params === 'object' && params !== null) {
+          const typedParams = params as T & { tools?: Record<string, unknown> }
+
+          if (!typedParams.tools) {
+            typedParams.tools = {}
+          }
+
+          // 使用类型安全的方式遍历配置
+          ;(Object.keys(config) as ToolConfigKey[]).forEach((key) => {
+            if (config[key] && key in toolNameMap && key in google.tools) {
+              const toolName = toolNameMap[key]
+              typedParams.tools![toolName] = google.tools[key]({})
+            }
+          })
+        }
+      }
+      return params
+    }
+  })

packages/aiCore/src/core/plugins/built-in/index.ts

@@ -4,6 +4,7 @@
  */
 export const BUILT_IN_PLUGIN_PREFIX = 'built-in:'
 
+export { googleToolsPlugin } from './googleToolsPlugin'
 export { createLoggingPlugin } from './logging'
 export { createPromptToolUsePlugin } from './toolUsePlugin/promptToolUsePlugin'
 export type { PromptToolUseConfig, ToolUseRequestContext, ToolUseResult } from './toolUsePlugin/type'

packages/aiCore/src/core/runtime/executor.ts

@@ -4,12 +4,12 @@
  */
 import { ImageModelV2, LanguageModelV2, LanguageModelV2Middleware } from '@ai-sdk/provider'
 import {
-  experimental_generateImage as generateImage,
+  experimental_generateImage as _generateImage,
-  generateObject,
+  generateObject as _generateObject,
-  generateText,
+  generateText as _generateText,
   LanguageModel,
-  streamObject,
+  streamObject as _streamObject,
-  streamText
+  streamText as _streamText
 } from 'ai'
 
 import { globalModelResolver } from '../models'
@@ -18,7 +18,14 @@ import { type AiPlugin, type AiRequestContext, definePlugin } from '../plugins'
 import { type ProviderId } from '../providers'
 import { ImageGenerationError, ImageModelResolutionError } from './errors'
 import { PluginEngine } from './pluginEngine'
-import { type RuntimeConfig } from './types'
+import type {
+  generateImageParams,
+  generateObjectParams,
+  generateTextParams,
+  RuntimeConfig,
+  streamObjectParams,
+  streamTextParams
+} from './types'
 
 export class RuntimeExecutor<T extends ProviderId = ProviderId> {
   public pluginEngine: PluginEngine<T>
@@ -75,12 +82,12 @@ export class RuntimeExecutor<T extends ProviderId = ProviderId> {
    * 流式文本生成
    */
   async streamText(
-    params: Parameters<typeof streamText>[0],
+    params: streamTextParams,
     options?: {
       middlewares?: LanguageModelV2Middleware[]
     }
-  ): Promise<ReturnType<typeof streamText>> {
+  ): Promise<ReturnType<typeof _streamText>> {
-    const { model, ...restParams } = params
+    const { model } = params
 
     // 根据 model 类型决定插件配置
     if (typeof model === 'string') {
@@ -94,19 +101,16 @@ export class RuntimeExecutor<T extends ProviderId = ProviderId> {
 
     return this.pluginEngine.executeStreamWithPlugins(
       'streamText',
-      model,
+      params,
-      restParams,
+      (resolvedModel, transformedParams, streamTransforms) => {
-      async (resolvedModel, transformedParams, streamTransforms) => {
         const experimental_transform =
           params?.experimental_transform ?? (streamTransforms.length > 0 ? streamTransforms : undefined)
 
-        const finalParams = {
+        return _streamText({
-          model: resolvedModel,
           ...transformedParams,
+          model: resolvedModel,
           experimental_transform
-        } as Parameters<typeof streamText>[0]
+        })
-
-        return await streamText(finalParams)
       }
     )
   }
@@ -117,12 +121,12 @@ export class RuntimeExecutor<T extends ProviderId = ProviderId> {
    * 生成文本
    */
   async generateText(
-    params: Parameters<typeof generateText>[0],
+    params: generateTextParams,
     options?: {
       middlewares?: LanguageModelV2Middleware[]
     }
-  ): Promise<ReturnType<typeof generateText>> {
+  ): Promise<ReturnType<typeof _generateText>> {
-    const { model, ...restParams } = params
+    const { model } = params
 
     // 根据 model 类型决定插件配置
     if (typeof model === 'string') {
@@ -134,12 +138,10 @@ export class RuntimeExecutor<T extends ProviderId = ProviderId> {
       this.pluginEngine.usePlugins([this.createConfigureContextPlugin()])
     }
 
-    return this.pluginEngine.executeWithPlugins(
+    return this.pluginEngine.executeWithPlugins<Parameters<typeof _generateText>[0], ReturnType<typeof _generateText>>(
       'generateText',
-      model,
+      params,
-      restParams,
+      (resolvedModel, transformedParams) => _generateText({ ...transformedParams, model: resolvedModel })
-      async (resolvedModel, transformedParams) =>
-        generateText({ model: resolvedModel, ...transformedParams } as Parameters<typeof generateText>[0])
     )
   }
 
@@ -147,12 +149,12 @@ export class RuntimeExecutor<T extends ProviderId = ProviderId> {
    * 生成结构化对象
    */
   async generateObject(
-    params: Parameters<typeof generateObject>[0],
+    params: generateObjectParams,
     options?: {
       middlewares?: LanguageModelV2Middleware[]
     }
-  ): Promise<ReturnType<typeof generateObject>> {
+  ): Promise<ReturnType<typeof _generateObject>> {
-    const { model, ...restParams } = params
+    const { model } = params
 
     // 根据 model 类型决定插件配置
     if (typeof model === 'string') {
@@ -164,25 +166,23 @@ export class RuntimeExecutor<T extends ProviderId = ProviderId> {
       this.pluginEngine.usePlugins([this.createConfigureContextPlugin()])
     }
 
-    return this.pluginEngine.executeWithPlugins(
+    return this.pluginEngine.executeWithPlugins<generateObjectParams, ReturnType<typeof _generateObject>>(
       'generateObject',
-      model,
+      params,
-      restParams,
+      async (resolvedModel, transformedParams) => _generateObject({ ...transformedParams, model: resolvedModel })
-      async (resolvedModel, transformedParams) =>
-        generateObject({ model: resolvedModel, ...transformedParams } as Parameters<typeof generateObject>[0])
     )
   }
 
   /**
    * 流式生成结构化对象
    */
-  async streamObject(
+  streamObject(
-    params: Parameters<typeof streamObject>[0],
+    params: streamObjectParams,
     options?: {
       middlewares?: LanguageModelV2Middleware[]
     }
-  ): Promise<ReturnType<typeof streamObject>> {
+  ): Promise<ReturnType<typeof _streamObject>> {
-    const { model, ...restParams } = params
+    const { model } = params
 
     // 根据 model 类型决定插件配置
     if (typeof model === 'string') {
@@ -194,23 +194,17 @@ export class RuntimeExecutor<T extends ProviderId = ProviderId> {
       this.pluginEngine.usePlugins([this.createConfigureContextPlugin()])
     }
 
-    return this.pluginEngine.executeWithPlugins(
+    return this.pluginEngine.executeStreamWithPlugins('streamObject', params, (resolvedModel, transformedParams) =>
-      'streamObject',
+      _streamObject({ ...transformedParams, model: resolvedModel })
-      model,
-      restParams,
-      async (resolvedModel, transformedParams) =>
-        streamObject({ model: resolvedModel, ...transformedParams } as Parameters<typeof streamObject>[0])
     )
   }
 
   /**
    * 生成图像
    */
-  async generateImage(
+  generateImage(params: generateImageParams): Promise<ReturnType<typeof _generateImage>> {
-    params: Omit<Parameters<typeof generateImage>[0], 'model'> & { model: string | ImageModelV2 }
-  ): Promise<ReturnType<typeof generateImage>> {
     try {
-      const { model, ...restParams } = params
+      const { model } = params
 
       // 根据 model 类型决定插件配置
       if (typeof model === 'string') {
@@ -219,13 +213,8 @@ export class RuntimeExecutor<T extends ProviderId = ProviderId> {
         this.pluginEngine.usePlugins([this.createConfigureContextPlugin()])
       }
 
-      return await this.pluginEngine.executeImageWithPlugins(
+      return this.pluginEngine.executeImageWithPlugins('generateImage', params, (resolvedModel, transformedParams) =>
-        'generateImage',
+        _generateImage({ ...transformedParams, model: resolvedModel })
-        model,
-        restParams,
-        async (resolvedModel, transformedParams) => {
-          return await generateImage({ model: resolvedModel, ...transformedParams })
-        }
       )
     } catch (error) {
       if (error instanceof Error) {

packages/aiCore/src/core/runtime/pluginEngine.ts

@@ -1,6 +1,6 @@
 /* eslint-disable @eslint-react/naming-convention/context-name */
 import { ImageModelV2 } from '@ai-sdk/provider'
-import { LanguageModel } from 'ai'
+import { experimental_generateImage, generateObject, generateText, LanguageModel, streamObject, streamText } from 'ai'
 
 import { type AiPlugin, createContext, PluginManager } from '../plugins'
 import { type ProviderId } from '../providers/types'
@@ -62,17 +62,19 @@ export class PluginEngine<T extends ProviderId = ProviderId> {
    * 执行带插件的操作（非流式）
    * 提供给AiExecutor使用
    */
-  async executeWithPlugins<TParams, TResult>(
+  async executeWithPlugins<
+    TParams extends Parameters<typeof generateText | typeof generateObject>[0],
+    TResult extends ReturnType<typeof generateText | typeof generateObject>
+  >(
     methodName: string,
-    model: LanguageModel,
     params: TParams,
-    executor: (model: LanguageModel, transformedParams: TParams) => Promise<TResult>,
+    executor: (model: LanguageModel, transformedParams: TParams) => TResult,
     _context?: ReturnType<typeof createContext>
   ): Promise<TResult> {
     // 统一处理模型解析
     let resolvedModel: LanguageModel | undefined
     let modelId: string
-
+    const { model } = params
     if (typeof model === 'string') {
       // 字符串：需要通过插件解析
       modelId = model
@@ -89,7 +91,7 @@ export class PluginEngine<T extends ProviderId = ProviderId> {
     context.recursiveCall = async (newParams: any): Promise<TResult> => {
       // 递归调用自身，重新走完整的插件流程
       context.isRecursiveCall = true
-      const result = await this.executeWithPlugins(methodName, model, newParams, executor, context)
+      const result = await this.executeWithPlugins(methodName, newParams, executor, context)
       context.isRecursiveCall = false
       return result
     }
@@ -138,17 +140,19 @@ export class PluginEngine<T extends ProviderId = ProviderId> {
    * 执行带插件的图像生成操作
    * 提供给AiExecutor使用
    */
-  async executeImageWithPlugins<TParams, TResult>(
+  async executeImageWithPlugins<
+    TParams extends Omit<Parameters<typeof experimental_generateImage>[0], 'model'> & { model: string | ImageModelV2 },
+    TResult extends ReturnType<typeof experimental_generateImage>
+  >(
     methodName: string,
-    model: ImageModelV2 | string,
     params: TParams,
-    executor: (model: ImageModelV2, transformedParams: TParams) => Promise<TResult>,
+    executor: (model: ImageModelV2, transformedParams: TParams) => TResult,
     _context?: ReturnType<typeof createContext>
   ): Promise<TResult> {
     // 统一处理模型解析
     let resolvedModel: ImageModelV2 | undefined
     let modelId: string
-
+    const { model } = params
     if (typeof model === 'string') {
       // 字符串：需要通过插件解析
       modelId = model
@@ -165,7 +169,7 @@ export class PluginEngine<T extends ProviderId = ProviderId> {
     context.recursiveCall = async (newParams: any): Promise<TResult> => {
       // 递归调用自身，重新走完整的插件流程
       context.isRecursiveCall = true
-      const result = await this.executeImageWithPlugins(methodName, model, newParams, executor, context)
+      const result = await this.executeImageWithPlugins(methodName, newParams, executor, context)
       context.isRecursiveCall = false
       return result
     }
@@ -214,17 +218,19 @@ export class PluginEngine<T extends ProviderId = ProviderId> {
    * 执行流式调用的通用逻辑（支持流转换器）
    * 提供给AiExecutor使用
    */
-  async executeStreamWithPlugins<TParams, TResult>(
+  async executeStreamWithPlugins<
+    TParams extends Parameters<typeof streamText | typeof streamObject>[0],
+    TResult extends ReturnType<typeof streamText | typeof streamObject>
+  >(
     methodName: string,
-    model: LanguageModel,
     params: TParams,
-    executor: (model: LanguageModel, transformedParams: TParams, streamTransforms: any[]) => Promise<TResult>,
+    executor: (model: LanguageModel, transformedParams: TParams, streamTransforms: any[]) => TResult,
     _context?: ReturnType<typeof createContext>
   ): Promise<TResult> {
     // 统一处理模型解析
     let resolvedModel: LanguageModel | undefined
     let modelId: string
-
+    const { model } = params
     if (typeof model === 'string') {
       // 字符串：需要通过插件解析
       modelId = model
@@ -241,7 +247,7 @@ export class PluginEngine<T extends ProviderId = ProviderId> {
     context.recursiveCall = async (newParams: any): Promise<TResult> => {
       // 递归调用自身，重新走完整的插件流程
       context.isRecursiveCall = true
-      const result = await this.executeStreamWithPlugins(methodName, model, newParams, executor, context)
+      const result = await this.executeStreamWithPlugins(methodName, newParams, executor, context)
       context.isRecursiveCall = false
       return result
     }

packages/aiCore/src/core/runtime/types.ts

@@ -1,6 +1,9 @@
 /**
  * Runtime 层类型定义
  */
+import { ImageModelV2 } from '@ai-sdk/provider'
+import { experimental_generateImage, generateObject, generateText, streamObject, streamText } from 'ai'
+
 import { type ModelConfig } from '../models/types'
 import { type AiPlugin } from '../plugins'
 import { type ProviderId } from '../providers/types'
@@ -13,3 +16,11 @@ export interface RuntimeConfig<T extends ProviderId = ProviderId> {
   providerSettings: ModelConfig<T>['providerSettings'] & { mode?: 'chat' | 'responses' }
   plugins?: AiPlugin[]
 }
+
+export type generateImageParams = Omit<Parameters<typeof experimental_generateImage>[0], 'model'> & {
+  model: string | ImageModelV2
+}
+export type generateObjectParams = Parameters<typeof generateObject>[0]
+export type generateTextParams = Parameters<typeof generateText>[0]
+export type streamObjectParams = Parameters<typeof streamObject>[0]
+export type streamTextParams = Parameters<typeof streamText>[0]

src/renderer/src/aiCore/chunk/handleToolCallChunk.ts

@@ -281,7 +281,7 @@ export class ToolCallChunkHandler {
     // 工具特定的后处理
     switch (toolResponse.tool.name) {
       case 'builtin_knowledge_search': {
-        processKnowledgeReferences(toolResponse.response?.knowledgeReferences, this.onChunk)
+        processKnowledgeReferences(toolResponse.response, this.onChunk)
         break
       }
       // 未来可以在这里添加其他工具的后处理逻辑

src/renderer/src/aiCore/middleware/AiSdkMiddlewareBuilder.ts

@@ -22,6 +22,7 @@ export interface AiSdkMiddlewareConfig {
   isImageGenerationEndpoint: boolean
   enableWebSearch: boolean
   enableGenerateImage: boolean
+  enableUrlContext: boolean
   mcpTools?: MCPTool[]
   uiMessages?: Message[]
 }

src/renderer/src/aiCore/plugins/PluginBuilder.ts

@@ -1,5 +1,5 @@
 import { AiPlugin } from '@cherrystudio/ai-core'
-import { createPromptToolUsePlugin, webSearchPlugin } from '@cherrystudio/ai-core/built-in/plugins'
+import { createPromptToolUsePlugin, googleToolsPlugin, webSearchPlugin } from '@cherrystudio/ai-core/built-in/plugins'
 import { loggerService } from '@logger'
 import { getEnableDeveloperMode } from '@renderer/hooks/useSettings'
 import { Assistant } from '@renderer/types'
@@ -70,9 +70,10 @@ export function buildPlugins(
     )
   }
 
-  // if (!middlewareConfig.enableTool && middlewareConfig.mcpTools && middlewareConfig.mcpTools.length > 0) {
+  if (middlewareConfig.enableUrlContext) {
-  //   plugins.push(createNativeToolUsePlugin())
+    plugins.push(googleToolsPlugin({ urlContext: true }))
-  // }
+  }
+
   logger.debug(
     'Final plugin list:',
     plugins.map((p) => p.name)

src/renderer/src/aiCore/plugins/searchOrchestrationPlugin.ts

@@ -267,7 +267,6 @@ export const searchOrchestrationPlugin = (assistant: Assistant, topicId: string)
         const hasKnowledgeBase = !isEmpty(knowledgeBaseIds)
         const knowledgeRecognition = assistant.knowledgeRecognition || 'on'
         const globalMemoryEnabled = selectGlobalMemoryEnabled(store.getState())
-
         const shouldWebSearch = !!assistant.webSearchProviderId
         const shouldKnowledgeSearch = hasKnowledgeBase && knowledgeRecognition === 'on'
         const shouldMemorySearch = globalMemoryEnabled && assistant.enableMemory

src/renderer/src/aiCore/plugins/telemetryPlugin.ts

@@ -58,91 +58,6 @@ class AdapterTracer {
     })
   }
 
-  // startSpan(name: string, options?: any, context?: any): Span {
-  //   // 如果提供了父 SpanContext 且未显式传入 context，则使用父上下文
-  //   const contextToUse = context ?? this.cachedParentContext ?? otelContext.active()
-
-  //   const span = this.originalTracer.startSpan(name, options, contextToUse)
-
-  //   // 标记父子关系，便于在转换阶段兜底重建层级
-  //   try {
-  //     if (this.parentSpanContext) {
-  //       span.setAttribute('trace.parentSpanId', this.parentSpanContext.spanId)
-  //       span.setAttribute('trace.parentTraceId', this.parentSpanContext.traceId)
-  //     }
-  //     if (this.topicId) {
-  //       span.setAttribute('trace.topicId', this.topicId)
-  //     }
-  //   } catch (e) {
-  //     logger.debug('Failed to set trace parent attributes', e as Error)
-  //   }
-
-  //   logger.info('AI SDK span created via AdapterTracer', {
-  //     spanName: name,
-  //     spanId: span.spanContext().spanId,
-  //     traceId: span.spanContext().traceId,
-  //     parentTraceId: this.parentSpanContext?.traceId,
-  //     topicId: this.topicId,
-  //     modelName: this.modelName,
-  //     traceIdMatches: this.parentSpanContext ? span.spanContext().traceId === this.parentSpanContext.traceId : undefined
-  //   })
-
-  //   // 包装 span 的 end 方法，在结束时进行数据转换
-  //   const originalEnd = span.end.bind(span)
-  //   span.end = (endTime?: any) => {
-  //     logger.info('AI SDK span.end() called - about to convert span', {
-  //       spanName: name,
-  //       spanId: span.spanContext().spanId,
-  //       traceId: span.spanContext().traceId,
-  //       topicId: this.topicId,
-  //       modelName: this.modelName
-  //     })
-
-  //     // 调用原始 end 方法
-  //     originalEnd(endTime)
-
-  //     // 转换并保存 span 数据
-  //     try {
-  //       logger.info('Converting AI SDK span to SpanEntity', {
-  //         spanName: name,
-  //         spanId: span.spanContext().spanId,
-  //         traceId: span.spanContext().traceId,
-  //         topicId: this.topicId,
-  //         modelName: this.modelName
-  //       })
-  //       logger.info('spanspanspanspanspanspan', span)
-  //       const spanEntity = AiSdkSpanAdapter.convertToSpanEntity({
-  //         span,
-  //         topicId: this.topicId,
-  //         modelName: this.modelName
-  //       })
-
-  //       // 保存转换后的数据
-  //       window.api.trace.saveEntity(spanEntity)
-
-  //       logger.info('AI SDK span converted and saved successfully', {
-  //         spanName: name,
-  //         spanId: span.spanContext().spanId,
-  //         traceId: span.spanContext().traceId,
-  //         topicId: this.topicId,
-  //         modelName: this.modelName,
-  //         hasUsage: !!spanEntity.usage,
-  //         usage: spanEntity.usage
-  //       })
-  //     } catch (error) {
-  //       logger.error('Failed to convert AI SDK span', error as Error, {
-  //         spanName: name,
-  //         spanId: span.spanContext().spanId,
-  //         traceId: span.spanContext().traceId,
-  //         topicId: this.topicId,
-  //         modelName: this.modelName
-  //       })
-  //     }
-  //   }
-
-  //   return span
-  // }
-
   startActiveSpan<F extends (span: Span) => any>(name: string, fn: F): ReturnType<F>
   startActiveSpan<F extends (span: Span) => any>(name: string, options: any, fn: F): ReturnType<F>
   startActiveSpan<F extends (span: Span) => any>(name: string, options: any, context: any, fn: F): ReturnType<F>

src/renderer/src/aiCore/prepareParams/parameterBuilder.ts

@@ -3,6 +3,8 @@
  * 构建AI SDK的流式和非流式参数
  */
 
+import { vertexAnthropic } from '@ai-sdk/google-vertex/anthropic/edge'
+import { vertex } from '@ai-sdk/google-vertex/edge'
 import { loggerService } from '@logger'
 import {
   isGenerateImageModel,
@@ -19,6 +21,7 @@ import type { StreamTextParams } from '@renderer/types/aiCoreTypes'
 import type { ModelMessage } from 'ai'
 import { stepCountIs } from 'ai'
 
+import { getAiSdkProviderId } from '../provider/factory'
 import { setupToolsConfig } from '../utils/mcp'
 import { buildProviderOptions } from '../utils/options'
 import { getAnthropicThinkingBudget } from '../utils/reasoning'
@@ -56,6 +59,7 @@ export async function buildStreamTextParams(
   const { mcpTools } = options
 
   const model = assistant.model || getDefaultModel()
+  const aiSdkProviderId = getAiSdkProviderId(provider)
 
   let { maxTokens } = getAssistantSettings(assistant)
 
@@ -80,7 +84,7 @@ export async function buildStreamTextParams(
 
   const enableGenerateImage = !!(isGenerateImageModel(model) && assistant.enableGenerateImage)
 
-  const tools = setupToolsConfig(mcpTools)
+  let tools = setupToolsConfig(mcpTools)
 
   // if (webSearchProviderId) {
   //   tools['builtin_web_search'] = webSearchTool(webSearchProviderId)
@@ -103,6 +107,26 @@ export async function buildStreamTextParams(
     maxTokens -= getAnthropicThinkingBudget(assistant, model)
   }
 
+  // google-vertex | google-vertex-anthropic
+  if (enableWebSearch) {
+    if (!tools) {
+      tools = {}
+    }
+    if (aiSdkProviderId === 'google-vertex') {
+      tools.google_search = vertex.tools.googleSearch({})
+    } else if (aiSdkProviderId === 'google-vertex-anthropic') {
+      tools.web_search = vertexAnthropic.tools.webSearch_20250305({})
+    }
+  }
+
+  // google-vertex
+  if (enableUrlContext && aiSdkProviderId === 'google-vertex') {
+    if (!tools) {
+      tools = {}
+    }
+    tools.url_context = vertex.tools.urlContext({})
+  }
+
   // 构建基础参数
   const params: StreamTextParams = {
     messages: sdkMessages,
@@ -112,10 +136,12 @@ export async function buildStreamTextParams(
     abortSignal: options.requestOptions?.signal,
     headers: options.requestOptions?.headers,
     providerOptions,
-    tools,
     stopWhen: stepCountIs(10),
     maxRetries: 0
   }
+  if (tools) {
+    params.tools = tools
+  }
   if (assistant.prompt) {
     params.system = assistant.prompt
   }

src/renderer/src/aiCore/tools/KnowledgeSearchTool.ts

@@ -23,8 +23,6 @@ export const knowledgeSearchTool = (
 Pre-extracted search queries: "${extractedKeywords.question.join(', ')}"
 Rewritten query: "${extractedKeywords.rewrite}"
 
-This tool searches for relevant information and formats results for easy citation. The returned sources should be cited using [1], [2], etc. format in your response.
-
 Call this tool to execute the search. You can optionally provide additional context to refine the search.`,
 
     inputSchema: z.object({
@@ -35,7 +33,7 @@ Call this tool to execute the search. You can optionally provide additional cont
     }),
 
     execute: async ({ additionalContext }) => {
-      try {
+      // try {
       // 获取助手的知识库配置
       const knowledgeBaseIds = assistant.knowledge_bases?.map((base) => base.id)
       const hasKnowledgeBase = !isEmpty(knowledgeBaseIds)
@@ -43,11 +41,7 @@ Call this tool to execute the search. You can optionally provide additional cont
 
       // 检查是否有知识库
       if (!hasKnowledgeBase) {
-          return {
+        return []
-            summary: 'No knowledge base configured for this assistant.',
-            knowledgeReferences: [],
-            instructions: ''
-          }
       }
 
       let finalQueries = [...extractedKeywords.question]
@@ -64,11 +58,7 @@ Call this tool to execute the search. You can optionally provide additional cont
 
       // 检查是否需要搜索
       if (finalQueries[0] === 'not_needed') {
-          return {
+        return []
-            summary: 'No search needed based on the query analysis.',
-            knowledgeReferences: [],
-            instructions: ''
-          }
       }
 
       // 构建搜索条件
@@ -106,28 +96,39 @@ Call this tool to execute the search. You can optionally provide additional cont
         metadata: ref.metadata
       }))
 
-        // const referenceContent = `\`\`\`json\n${JSON.stringify(knowledgeReferencesData, null, 2)}\n\`\`\``
       // TODO 在工具函数中添加搜索缓存机制
       // const searchCacheKey = `${topicId}-${JSON.stringify(finalQueries)}`
-        // 可以在插件层面管理已搜索的查询，避免重复搜索
+
+      // 返回结果
+      return knowledgeReferencesData
+    },
+    toModelOutput: (results) => {
+      let summary = 'No search needed based on the query analysis.'
+      if (results.length > 0) {
+        summary = `Found ${results.length} relevant sources. Use [number] format to cite specific information.`
+      }
+      const referenceContent = `\`\`\`json\n${JSON.stringify(results, null, 2)}\n\`\`\``
       const fullInstructions = REFERENCE_PROMPT.replace(
         '{question}',
         "Based on the knowledge references, please answer the user's question with proper citations."
-        ).replace('{references}', 'knowledgeReferences:')
+      ).replace('{references}', referenceContent)
 
-        // 返回结果
       return {
-          summary: `Found ${knowledgeReferencesData.length} relevant sources. Use [number] format to cite specific information.`,
+        type: 'content',
-          knowledgeReferences: knowledgeReferencesData,
+        value: [
-          instructions: fullInstructions
+          {
-        }
+            type: 'text',
-      } catch (error) {
+            text: 'This tool searches for relevant information and formats results for easy citation. The returned sources should be cited using [1], [2], etc. format in your response.'
-        // 返回空对象而不是抛出错误，避免中断对话流程
+          },
-        return {
+          {
-          summary: `Search failed: ${error instanceof Error ? error.message : 'Unknown error'}`,
+            type: 'text',
-          knowledgeReferences: [],
+            text: summary
-          instructions: ''
+          },
+          {
+            type: 'text',
+            text: fullInstructions
           }
+        ]
       }
     }
   })

src/renderer/src/aiCore/tools/MemorySearchTool.ts

@@ -1,6 +1,5 @@
 import store from '@renderer/store'
 import { selectCurrentUserId, selectGlobalMemoryEnabled, selectMemoryConfig } from '@renderer/store/memory'
-import type { Assistant } from '@renderer/types'
 import { type InferToolInput, type InferToolOutput, tool } from 'ai'
 import { z } from 'zod'
 
@@ -19,7 +18,6 @@ export const memorySearchTool = () => {
       limit: z.number().min(1).max(20).default(5).describe('Maximum number of memories to return')
     }),
     execute: async ({ query, limit = 5 }) => {
-      try {
       const globalMemoryEnabled = selectGlobalMemoryEnabled(store.getState())
       if (!globalMemoryEnabled) {
         return []
@@ -40,102 +38,9 @@ export const memorySearchTool = () => {
         return relevantMemories
       }
       return []
-      } catch (error) {
-        return []
-      }
     }
   })
 }
 
-// 方案4: 为第二个工具也使用类型断言
-type MessageRole = 'user' | 'assistant' | 'system'
-type MessageType = {
-  content: string
-  role: MessageRole
-}
-type MemorySearchWithExtractionInput = {
-  userMessage: MessageType
-  lastAnswer?: MessageType
-}
-
-/**
- * 🧠 智能记忆搜索工具（带上下文提取）
- * 从用户消息和对话历史中自动提取关键词进行记忆搜索
- */
-export const memorySearchToolWithExtraction = (assistant: Assistant) => {
-  return tool({
-    name: 'memory_search_with_extraction',
-    description: 'Search memories with automatic keyword extraction from conversation context',
-    inputSchema: z.object({
-      userMessage: z.object({
-        content: z.string().describe('The main content of the user message'),
-        role: z.enum(['user', 'assistant', 'system']).describe('Message role')
-      }),
-      lastAnswer: z
-        .object({
-          content: z.string().describe('The main content of the last assistant response'),
-          role: z.enum(['user', 'assistant', 'system']).describe('Message role')
-        })
-        .optional()
-    }) satisfies z.ZodSchema<MemorySearchWithExtractionInput>,
-    execute: async ({ userMessage }) => {
-      try {
-        const globalMemoryEnabled = selectGlobalMemoryEnabled(store.getState())
-        if (!globalMemoryEnabled || !assistant.enableMemory) {
-          return {
-            extractedKeywords: 'Memory search disabled',
-            searchResults: []
-          }
-        }
-
-        const memoryConfig = selectMemoryConfig(store.getState())
-        if (!memoryConfig.llmApiClient || !memoryConfig.embedderApiClient) {
-          return {
-            extractedKeywords: 'Memory models not configured',
-            searchResults: []
-          }
-        }
-
-        // 🔍 使用用户消息内容作为搜索关键词
-        const content = userMessage.content
-
-        if (!content) {
-          return {
-            extractedKeywords: 'No content to search',
-            searchResults: []
-          }
-        }
-
-        const currentUserId = selectCurrentUserId(store.getState())
-        const processorConfig = MemoryProcessor.getProcessorConfig(memoryConfig, assistant.id, currentUserId)
-
-        const memoryProcessor = new MemoryProcessor()
-        const relevantMemories = await memoryProcessor.searchRelevantMemories(
-          content,
-          processorConfig,
-          5 // Limit to top 5 most relevant memories
-        )
-
-        if (relevantMemories?.length > 0) {
-          return {
-            extractedKeywords: content,
-            searchResults: relevantMemories
-          }
-        }
-
-        return {
-          extractedKeywords: content,
-          searchResults: []
-        }
-      } catch (error) {
-        return {
-          extractedKeywords: 'Search failed',
-          searchResults: []
-        }
-      }
-    }
-  })
-}
 export type MemorySearchToolInput = InferToolInput<ReturnType<typeof memorySearchTool>>
 export type MemorySearchToolOutput = InferToolOutput<ReturnType<typeof memorySearchTool>>
-export type MemorySearchToolWithExtractionOutput = InferToolOutput<ReturnType<typeof memorySearchToolWithExtraction>>

src/renderer/src/aiCore/tools/WebSearchTool.ts

@@ -30,8 +30,6 @@ Relevant links: ${extractedKeywords.links.join(', ')}`
         : ''
     }
 
-This tool searches for relevant information and formats results for easy citation. The returned sources should be cited using [1], [2], etc. format in your response.
-
 Call this tool to execute the search. You can optionally provide additional context to refine the search.`,
 
     inputSchema: z.object({
@@ -58,15 +56,9 @@ Call this tool to execute the search. You can optionally provide additional cont
       }
       // 检查是否需要搜索
       if (finalQueries[0] === 'not_needed') {
-        return {
+        return searchResults
-          summary: 'No search needed based on the query analysis.',
-          searchResults,
-          sources: '',
-          instructions: ''
-        }
       }
 
-      try {
       // 构建 ExtractResults 结构用于 processWebsearch
       const extractResults: ExtractResults = {
         websearch: {
@@ -75,23 +67,16 @@ Call this tool to execute the search. You can optionally provide additional cont
         }
       }
       searchResults = await WebSearchService.processWebsearch(webSearchProvider!, extractResults, requestId)
-      } catch (error) {
+
-        return {
+      return searchResults
-          summary: `Search failed: ${error instanceof Error ? error.message : 'Unknown error'}`,
+    },
-          sources: [],
+    toModelOutput: (results) => {
-          instructions: ''
+      let summary = 'No search needed based on the query analysis.'
-        }
+      if (results.query && results.results.length > 0) {
-      }
+        summary = `Found ${results.results.length} relevant sources. Use [number] format to cite specific information.`
-      if (searchResults.results.length === 0) {
-        return {
-          summary: 'No search results found for the given query.',
-          sources: [],
-          instructions: ''
-        }
       }
 
-      const results = searchResults.results
+      const citationData = results.results.map((result, index) => ({
-      const citationData = results.map((result, index) => ({
         number: index + 1,
         title: result.title,
         content: result.content,
@@ -99,18 +84,27 @@ Call this tool to execute the search. You can optionally provide additional cont
       }))
 
       // 🔑 返回引用友好的格式，复用 REFERENCE_PROMPT 逻辑
-      // const referenceContent = `\`\`\`json\n${JSON.stringify(citationData, null, 2)}\n\`\`\``
+      const referenceContent = `\`\`\`json\n${JSON.stringify(citationData, null, 2)}\n\`\`\``
-
-      // 构建完整的引用指导文本
       const fullInstructions = REFERENCE_PROMPT.replace(
         '{question}',
         "Based on the search results, please answer the user's question with proper citations."
-      ).replace('{references}', 'searchResults:')
+      ).replace('{references}', referenceContent)
-
       return {
-        summary: `Found ${citationData.length} relevant sources. Use [number] format to cite specific information.`,
+        type: 'content',
-        searchResults,
+        value: [
-        instructions: fullInstructions
+          {
+            type: 'text',
+            text: 'This tool searches for relevant information and formats results for easy citation. The returned sources should be cited using [1], [2], etc. format in your response.'
+          },
+          {
+            type: 'text',
+            text: summary
+          },
+          {
+            type: 'text',
+            text: fullInstructions
+          }
+        ]
       }
     }
   })

src/renderer/src/aiCore/utils/options.ts

@@ -120,6 +120,9 @@ export function buildProviderOptions(
         case 'google-vertex':
           providerSpecificOptions = buildGeminiProviderOptions(assistant, model, capabilities)
           break
+        case 'google-vertex-anthropic':
+          providerSpecificOptions = buildAnthropicProviderOptions(assistant, model, capabilities)
+          break
         default:
           // 对于其他 provider，使用通用的构建逻辑
           providerSpecificOptions = {
@@ -137,10 +140,16 @@ export function buildProviderOptions(
     ...providerSpecificOptions,
     ...getCustomParameters(assistant)
   }
+  // vertex需要映射到google或anthropic
+  const rawProviderKey =
+    {
+      'google-vertex': 'google',
+      'google-vertex-anthropic': 'anthropic'
+    }[rawProviderId] || rawProviderId
 
   // 返回 AI Core SDK 要求的格式：{ 'providerId': providerOptions }
   return {
-    [rawProviderId]: providerSpecificOptions
+    [rawProviderKey]: providerSpecificOptions
   }
 }
 

src/renderer/src/pages/home/Messages/Tools/MessageKnowledgeSearch.tsx

@@ -23,7 +23,7 @@ export function MessageKnowledgeSearchToolTitle({ toolResponse }: { toolResponse
   ) : (
     <MessageWebSearchToolTitleTextWrapper type="secondary">
       <FileSearch size={16} style={{ color: 'unset' }} />
-      {i18n.t('message.websearch.fetch_complete', { count: toolOutput.knowledgeReferences.length ?? 0 })}
+      {i18n.t('message.websearch.fetch_complete', { count: toolOutput.length ?? 0 })}
     </MessageWebSearchToolTitleTextWrapper>
   )
 }
@@ -33,7 +33,7 @@ export function MessageKnowledgeSearchToolBody({ toolResponse }: { toolResponse:
 
   return toolResponse.status === 'done' ? (
     <MessageWebSearchToolBodyUlWrapper>
-      {toolOutput.knowledgeReferences.map((result) => (
+      {toolOutput.map((result) => (
         <li key={result.id}>
           <span>{result.id}</span>
           <span>{result.content}</span>

src/renderer/src/pages/home/Messages/Tools/MessageWebSearch.tsx

@@ -26,7 +26,7 @@ export const MessageWebSearchToolTitle = ({ toolResponse }: { toolResponse: MCPT
     <MessageWebSearchToolTitleTextWrapper type="secondary">
       <Search size={16} style={{ color: 'unset' }} />
       {t('message.websearch.fetch_complete', {
-        count: toolOutput?.searchResults?.results?.length ?? 0
+        count: toolOutput?.results?.length ?? 0
       })}
     </MessageWebSearchToolTitleTextWrapper>
   )
@@ -36,7 +36,7 @@ export const MessageWebSearchToolTitle = ({ toolResponse }: { toolResponse: MCPT
 //   const toolOutput = toolResponse.response as WebSearchToolOutput
 
 //   return toolResponse.status === 'done'
-//     ? toolOutput?.searchResults?.map((result, index) => (
+//     ? toolOutput?.results?.map((result, index) => (
 //         <MessageWebSearchToolBodyUlWrapper key={result?.query ?? '' + index}>
 //           {result.results.map((item, index) => (
 //             <li key={item.url + index}>

src/renderer/src/services/ApiService.ts

@@ -134,6 +134,7 @@ export async function fetchChatCompletion({
     isImageGenerationEndpoint: isDedicatedImageGenerationModel(assistant.model || getDefaultModel()),
     enableWebSearch: capabilities.enableWebSearch,
     enableGenerateImage: capabilities.enableGenerateImage,
+    enableUrlContext: capabilities.enableUrlContext,
     mcpTools,
     uiMessages
   }
@@ -222,6 +223,7 @@ export async function fetchMessagesSummary({ messages, assistant }: { messages:
     isImageGenerationEndpoint: false,
     enableWebSearch: false,
     enableGenerateImage: false,
+    enableUrlContext: false,
     mcpTools: []
   }
   try {
@@ -308,7 +310,8 @@ export async function fetchGenerate({
     isSupportedToolUse: false,
     isImageGenerationEndpoint: false,
     enableWebSearch: false,
-    enableGenerateImage: false
+    enableGenerateImage: false,
+    enableUrlContext: false
   }
 
   try {
@@ -420,6 +423,7 @@ export async function checkApi(provider: Provider, model: Model, timeout = 15000
         enableWebSearch: false,
         enableGenerateImage: false,
         isPromptToolUse: false,
+        enableUrlContext: false,
         assistant,
         callType: 'check',
         onChunk: (chunk: Chunk) => {

src/renderer/src/services/messageStreaming/callbacks/toolCallbacks.ts

@@ -83,13 +83,12 @@ export const createToolCallbacks = (deps: ToolCallbacksDependencies) => {
           }
         }
         blockManager.smartBlockUpdate(existingBlockId, changes, MessageBlockType.TOOL, true)
-
         // Handle citation block creation for web search results
-        if (toolResponse.tool.name === 'builtin_web_search' && toolResponse.response?.searchResults) {
+        if (toolResponse.tool.name === 'builtin_web_search' && toolResponse.response) {
           const citationBlock = createCitationBlock(
             assistantMsgId,
             {
-              response: { results: toolResponse.response.searchResults, source: WebSearchSource.WEBSEARCH }
+              response: { results: toolResponse.response, source: WebSearchSource.WEBSEARCH }
             },
             {
               status: MessageBlockStatus.SUCCESS
@@ -98,10 +97,10 @@ export const createToolCallbacks = (deps: ToolCallbacksDependencies) => {
           citationBlockId = citationBlock.id
           blockManager.handleBlockTransition(citationBlock, MessageBlockType.CITATION)
         }
-        if (toolResponse.tool.name === 'builtin_knowledge_search' && toolResponse.response?.knowledgeReferences) {
+        if (toolResponse.tool.name === 'builtin_knowledge_search' && toolResponse.response) {
           const citationBlock = createCitationBlock(
             assistantMsgId,
-            { knowledge: toolResponse.response.knowledgeReferences },
+            { knowledge: toolResponse.response },
             {
               status: MessageBlockStatus.SUCCESS
             }

yarn.lock

@@ -90,6 +90,18 @@ __metadata:
   languageName: node
   linkType: hard
 
+"@ai-sdk/anthropic@npm:2.0.15":
+  version: 2.0.15
+  resolution: "@ai-sdk/anthropic@npm:2.0.15"
+  dependencies:
+    "@ai-sdk/provider": "npm:2.0.0"
+    "@ai-sdk/provider-utils": "npm:3.0.8"
+  peerDependencies:
+    zod: ^3.25.76 || ^4
+  checksum: 10c0/9597b32be8b83dab67b23f162ca66cde385213fb1665f54091d59430789becf73e2b4fcd2be66ceb13020409f59cd8f9da7dae23adf183bc9eb7ce94f55bde96
+  languageName: node
+  linkType: hard
+
 "@ai-sdk/anthropic@npm:2.0.4":
   version: 2.0.4
   resolution: "@ai-sdk/anthropic@npm:2.0.4"
@@ -140,46 +152,34 @@ __metadata:
   languageName: node
   linkType: hard
 
-"@ai-sdk/gateway@npm:1.0.15":
+"@ai-sdk/gateway@npm:1.0.20":
-  version: 1.0.15
+  version: 1.0.20
-  resolution: "@ai-sdk/gateway@npm:1.0.15"
+  resolution: "@ai-sdk/gateway@npm:1.0.20"
   dependencies:
     "@ai-sdk/provider": "npm:2.0.0"
-    "@ai-sdk/provider-utils": "npm:3.0.7"
+    "@ai-sdk/provider-utils": "npm:3.0.8"
   peerDependencies:
     zod: ^3.25.76 || ^4
-  checksum: 10c0/cdd09f119d6618f00c363a27f51dc466a8a64f57f01bcdd127030a804825bd143b0fef2dbdb7802530865d474f4b9d55855670fecd7f2e6c615a5d9ac9fd6e3b
+  checksum: 10c0/c25e98aab2513f783b2b552245b027e5a73b209d974e25bbfae0e69b67fd3468bba0bf57085ca3d7259b4dc8881e7f40fca769f698f0b1eb028a849f587ad09c
   languageName: node
   linkType: hard
 
-"@ai-sdk/google-vertex@npm:^3.0.0":
+"@ai-sdk/google-vertex@npm:^3.0.25":
-  version: 3.0.9
+  version: 3.0.25
-  resolution: "@ai-sdk/google-vertex@npm:3.0.9"
+  resolution: "@ai-sdk/google-vertex@npm:3.0.25"
   dependencies:
-    "@ai-sdk/anthropic": "npm:2.0.4"
+    "@ai-sdk/anthropic": "npm:2.0.15"
-    "@ai-sdk/google": "npm:2.0.6"
+    "@ai-sdk/google": "npm:2.0.13"
     "@ai-sdk/provider": "npm:2.0.0"
-    "@ai-sdk/provider-utils": "npm:3.0.3"
+    "@ai-sdk/provider-utils": "npm:3.0.8"
     google-auth-library: "npm:^9.15.0"
   peerDependencies:
     zod: ^3.25.76 || ^4
-  checksum: 10c0/c6584b877f9e20a10dd7d92fc4cb1b4a9838510aa89734cf1ff2faa74ba820b976d3359d4eadcb6035c8911973300efb157931fa0d1105abc8db36f94544cc88
+  checksum: 10c0/ed67a439fc4a446aa7353d258c61497198aecdf0de55500d2abbea86109bbf1ff4570fffdfcf58508db1c887a2095a71322777634f76326a45e259d28ef0b801
   languageName: node
   linkType: hard
 
-"@ai-sdk/google@npm:2.0.6":
+"@ai-sdk/google@npm:2.0.13, @ai-sdk/google@npm:^2.0.13":
-  version: 2.0.6
-  resolution: "@ai-sdk/google@npm:2.0.6"
-  dependencies:
-    "@ai-sdk/provider": "npm:2.0.0"
-    "@ai-sdk/provider-utils": "npm:3.0.3"
-  peerDependencies:
-    zod: ^3.25.76 || ^4
-  checksum: 10c0/ad54dd4168df62851646bec3ac2e5cf9e39f3def3e9017579aef5c8e8ecdf57c150c67a80cad4d092c3df69cd8539bc1792adb6c311ed095f8261673b7812e98
-  languageName: node
-  linkType: hard
-
-"@ai-sdk/google@npm:^2.0.13":
   version: 2.0.13
   resolution: "@ai-sdk/google@npm:2.0.13"
   dependencies:
@@ -267,19 +267,6 @@ __metadata:
   languageName: node
   linkType: hard
 
-"@ai-sdk/provider-utils@npm:3.0.7":
-  version: 3.0.7
-  resolution: "@ai-sdk/provider-utils@npm:3.0.7"
-  dependencies:
-    "@ai-sdk/provider": "npm:2.0.0"
-    "@standard-schema/spec": "npm:^1.0.0"
-    eventsource-parser: "npm:^3.0.5"
-  peerDependencies:
-    zod: ^3.25.76 || ^4
-  checksum: 10c0/7e709289f9e514a6ba56a9b19764eb124ea1bd36d4b3b3e455a1c05353674c152839a4d3cd061af7a4cc36106bd15859a2346e54d4ed0a861feec3b2c4c21513
-  languageName: node
-  linkType: hard
-
 "@ai-sdk/provider-utils@npm:3.0.8":
   version: 3.0.8
   resolution: "@ai-sdk/provider-utils@npm:3.0.8"
@@ -12829,7 +12816,7 @@ __metadata:
     "@agentic/searxng": "npm:^7.3.3"
     "@agentic/tavily": "npm:^7.3.3"
     "@ai-sdk/amazon-bedrock": "npm:^3.0.0"
-    "@ai-sdk/google-vertex": "npm:^3.0.0"
+    "@ai-sdk/google-vertex": "npm:^3.0.25"
     "@ai-sdk/mistral": "npm:^2.0.0"
     "@ant-design/v5-patch-for-react-19": "npm:^1.0.3"
     "@anthropic-ai/sdk": "npm:^0.41.0"
@@ -12944,7 +12931,7 @@ __metadata:
     "@viz-js/lang-dot": "npm:^1.0.5"
     "@viz-js/viz": "npm:^3.14.0"
     "@xyflow/react": "npm:^12.4.4"
-    ai: "npm:^5.0.29"
+    ai: "npm:^5.0.38"
     antd: "patch:antd@npm%3A5.27.0#~/.yarn/patches/antd-npm-5.27.0-aa91c36546.patch"
     archiver: "npm:^7.0.1"
     async-mutex: "npm:^0.5.0"
@@ -13198,17 +13185,17 @@ __metadata:
   languageName: node
   linkType: hard
 
-"ai@npm:^5.0.29":
+"ai@npm:^5.0.38":
-  version: 5.0.29
+  version: 5.0.38
-  resolution: "ai@npm:5.0.29"
+  resolution: "ai@npm:5.0.38"
   dependencies:
-    "@ai-sdk/gateway": "npm:1.0.15"
+    "@ai-sdk/gateway": "npm:1.0.20"
     "@ai-sdk/provider": "npm:2.0.0"
-    "@ai-sdk/provider-utils": "npm:3.0.7"
+    "@ai-sdk/provider-utils": "npm:3.0.8"
     "@opentelemetry/api": "npm:1.9.0"
   peerDependencies:
     zod: ^3.25.76 || ^4
-  checksum: 10c0/526cd2fd59b35b19d902665e3dc1ba5a09f2bb1377295d642fb8a33e13a890874e4dd4b49a787de7f31f4ec6b07257be8514efac08f993081daeb430cf2f60ba
+  checksum: 10c0/9ea7a76ae5609574e9edb2f9541e2fe9cf0e7296547c5e9ae30ec000206c967b4c07fbb03b85f9027493f6877e15f6bfbe454faa793fca860826acf306982fc5
   languageName: node
   linkType: hard