mirror of
https://github.com/CherryHQ/cherry-studio.git
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280 lines
10 KiB
TypeScript
280 lines
10 KiB
TypeScript
/**
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* 参数构建模块
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* 构建AI SDK的流式和非流式参数
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*/
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import { anthropic } from '@ai-sdk/anthropic'
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import { azure } from '@ai-sdk/azure'
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import { google } from '@ai-sdk/google'
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import { vertexAnthropic } from '@ai-sdk/google-vertex/anthropic/edge'
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import { vertex } from '@ai-sdk/google-vertex/edge'
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import { combineHeaders } from '@ai-sdk/provider-utils'
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import type { AnthropicSearchConfig, WebSearchPluginConfig } from '@cherrystudio/ai-core/built-in/plugins'
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import { isBaseProvider } from '@cherrystudio/ai-core/core/providers/schemas'
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import type { BaseProviderId } from '@cherrystudio/ai-core/provider'
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import { loggerService } from '@logger'
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import {
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isAnthropicModel,
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isFixedReasoningModel,
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isGeminiModel,
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isGenerateImageModel,
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isGrokModel,
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isOpenAIModel,
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isOpenRouterBuiltInWebSearchModel,
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isPureGenerateImageModel,
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isSupportedReasoningEffortModel,
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isSupportedThinkingTokenModel,
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isWebSearchModel
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} from '@renderer/config/models'
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import { getHubModeSystemPrompt } from '@renderer/config/prompts-code-mode'
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import { fetchAllActiveServerTools } from '@renderer/services/ApiService'
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import { getDefaultModel } from '@renderer/services/AssistantService'
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import store from '@renderer/store'
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import type { CherryWebSearchConfig } from '@renderer/store/websearch'
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import type { Model } from '@renderer/types'
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import { type Assistant, getEffectiveMcpMode, type MCPTool, type Provider, SystemProviderIds } from '@renderer/types'
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import type { StreamTextParams } from '@renderer/types/aiCoreTypes'
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import { mapRegexToPatterns } from '@renderer/utils/blacklistMatchPattern'
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import { replacePromptVariables } from '@renderer/utils/prompt'
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import { isAIGatewayProvider, isAwsBedrockProvider, isSupportUrlContextProvider } from '@renderer/utils/provider'
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import type { ModelMessage, Tool } from 'ai'
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import { stepCountIs } from 'ai'
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import { getAiSdkProviderId } from '../provider/factory'
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import { setupToolsConfig } from '../utils/mcp'
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import { buildProviderOptions } from '../utils/options'
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import { buildProviderBuiltinWebSearchConfig } from '../utils/websearch'
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import { addAnthropicHeaders } from './header'
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import { getMaxTokens, getTemperature, getTopP } from './modelParameters'
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const logger = loggerService.withContext('parameterBuilder')
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type ProviderDefinedTool = Extract<Tool<any, any>, { type: 'provider' }>
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function mapVertexAIGatewayModelToProviderId(model: Model): BaseProviderId | undefined {
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if (isAnthropicModel(model)) {
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return 'anthropic'
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}
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if (isGeminiModel(model)) {
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return 'google'
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}
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if (isGrokModel(model)) {
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return 'xai'
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}
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if (isOpenAIModel(model)) {
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return 'openai'
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}
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logger.warn(`Unknown model type for AI Gateway: ${model.id}. Web search will not be enabled.`)
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return undefined
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}
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/**
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* 构建 AI SDK 流式参数
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* 这是主要的参数构建函数，整合所有转换逻辑
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*/
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export async function buildStreamTextParams(
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sdkMessages: StreamTextParams['messages'] = [],
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assistant: Assistant,
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provider: Provider,
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options: {
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mcpTools?: MCPTool[]
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webSearchProviderId?: string
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webSearchConfig?: CherryWebSearchConfig
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requestOptions?: {
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signal?: AbortSignal
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timeout?: number
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headers?: Record<string, string>
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}
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}
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): Promise<{
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params: StreamTextParams
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modelId: string
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capabilities: {
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enableReasoning: boolean
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enableWebSearch: boolean
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enableGenerateImage: boolean
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enableUrlContext: boolean
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}
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webSearchPluginConfig?: WebSearchPluginConfig
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}> {
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const { mcpTools } = options
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const model = assistant.model || getDefaultModel()
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const aiSdkProviderId = getAiSdkProviderId(provider)
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// 这三个变量透传出来，交给下面启用插件/中间件
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// 也可以在外部构建好再传入buildStreamTextParams
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// FIXME: qwen3即使关闭思考仍然会导致enableReasoning的结果为true
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const enableReasoning =
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((isSupportedThinkingTokenModel(model) || isSupportedReasoningEffortModel(model)) &&
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assistant.settings?.reasoning_effort !== undefined) ||
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isFixedReasoningModel(model)
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// 判断是否使用内置搜索
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// 条件：没有外部搜索提供商 && (用户开启了内置搜索 || 模型强制使用内置搜索)
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const hasExternalSearch = !!options.webSearchProviderId
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const enableWebSearch =
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!hasExternalSearch &&
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((assistant.enableWebSearch && isWebSearchModel(model)) ||
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isOpenRouterBuiltInWebSearchModel(model) ||
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model.id.includes('sonar'))
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// Validate provider and model support to prevent stale state from triggering urlContext
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const enableUrlContext = !!(
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assistant.enableUrlContext &&
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isSupportUrlContextProvider(provider) &&
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!isPureGenerateImageModel(model) &&
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(isGeminiModel(model) || isAnthropicModel(model))
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)
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const enableGenerateImage = !!(isGenerateImageModel(model) && assistant.enableGenerateImage)
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let tools = setupToolsConfig(mcpTools)
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// 构建真正的 providerOptions
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const webSearchConfig: CherryWebSearchConfig = {
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maxResults: store.getState().websearch.maxResults,
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excludeDomains: store.getState().websearch.excludeDomains,
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searchWithTime: store.getState().websearch.searchWithTime
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}
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const { providerOptions, standardParams } = buildProviderOptions(assistant, model, provider, {
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enableReasoning,
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enableWebSearch,
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enableGenerateImage
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})
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let webSearchPluginConfig: WebSearchPluginConfig | undefined = undefined
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if (enableWebSearch) {
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if (isBaseProvider(aiSdkProviderId)) {
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webSearchPluginConfig = buildProviderBuiltinWebSearchConfig(aiSdkProviderId, webSearchConfig, model)
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} else if (isAIGatewayProvider(provider) || SystemProviderIds.gateway === provider.id) {
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const aiSdkProviderId = mapVertexAIGatewayModelToProviderId(model)
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if (aiSdkProviderId) {
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webSearchPluginConfig = buildProviderBuiltinWebSearchConfig(aiSdkProviderId, webSearchConfig, model)
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}
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}
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if (!tools) {
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tools = {}
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}
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if (aiSdkProviderId === 'google-vertex') {
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tools.google_search = vertex.tools.googleSearch({}) as ProviderDefinedTool
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} else if (aiSdkProviderId === 'google-vertex-anthropic') {
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const blockedDomains = mapRegexToPatterns(webSearchConfig.excludeDomains)
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tools.web_search = vertexAnthropic.tools.webSearch_20250305({
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maxUses: webSearchConfig.maxResults,
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blockedDomains: blockedDomains.length > 0 ? blockedDomains : undefined
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}) as ProviderDefinedTool
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} else if (aiSdkProviderId === 'azure-responses') {
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tools.web_search_preview = azure.tools.webSearchPreview({
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searchContextSize: webSearchPluginConfig?.openai!.searchContextSize
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}) as ProviderDefinedTool
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} else if (aiSdkProviderId === 'azure-anthropic') {
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const blockedDomains = mapRegexToPatterns(webSearchConfig.excludeDomains)
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const anthropicSearchOptions: AnthropicSearchConfig = {
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maxUses: webSearchConfig.maxResults,
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blockedDomains: blockedDomains.length > 0 ? blockedDomains : undefined
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}
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tools.web_search = anthropic.tools.webSearch_20250305(anthropicSearchOptions) as ProviderDefinedTool
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}
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}
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if (enableUrlContext) {
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if (!tools) {
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tools = {}
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}
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const blockedDomains = mapRegexToPatterns(webSearchConfig.excludeDomains)
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switch (aiSdkProviderId) {
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case 'google-vertex':
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tools.url_context = vertex.tools.urlContext({}) as ProviderDefinedTool
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break
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case 'google':
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tools.url_context = google.tools.urlContext({}) as ProviderDefinedTool
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break
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case 'anthropic':
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case 'azure-anthropic':
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case 'google-vertex-anthropic':
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if (['anthropic', 'azure-anthropic'].includes(aiSdkProviderId)) {
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tools.web_fetch = anthropic.tools.webFetch_20250910({
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maxUses: webSearchConfig.maxResults,
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blockedDomains: blockedDomains.length > 0 ? blockedDomains : undefined
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}) as ProviderDefinedTool
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}
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break
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}
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}
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let headers: Record<string, string | undefined> = options.requestOptions?.headers ?? {}
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if (isAnthropicModel(model) && !isAwsBedrockProvider(provider)) {
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const betaHeaders = addAnthropicHeaders(assistant, model)
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// Only add the anthropic-beta header if there are actual beta headers to include
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if (betaHeaders.length > 0) {
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const newBetaHeaders = { 'anthropic-beta': betaHeaders.join(',') }
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headers = combineHeaders(headers, newBetaHeaders)
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}
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}
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// 构建基础参数
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// Note: standardParams (topK, frequencyPenalty, presencePenalty, stopSequences, seed)
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// are extracted from custom parameters and passed directly to streamText()
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// instead of being placed in providerOptions
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const params: StreamTextParams = {
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messages: sdkMessages,
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maxOutputTokens: getMaxTokens(assistant, model),
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temperature: getTemperature(assistant, model),
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topP: getTopP(assistant, model),
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// Include AI SDK standard params extracted from custom parameters
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...standardParams,
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abortSignal: options.requestOptions?.signal,
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headers,
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providerOptions,
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stopWhen: stepCountIs(20),
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maxRetries: 0
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}
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if (tools) {
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params.tools = tools
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}
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let systemPrompt = assistant.prompt ? await replacePromptVariables(assistant.prompt, model.name) : ''
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if (getEffectiveMcpMode(assistant) === 'auto') {
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const allActiveTools = await fetchAllActiveServerTools()
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const autoModePrompt = getHubModeSystemPrompt(allActiveTools)
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if (autoModePrompt) {
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systemPrompt = systemPrompt ? `${systemPrompt}\n\n${autoModePrompt}` : autoModePrompt
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}
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}
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if (systemPrompt) {
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params.system = systemPrompt
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}
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logger.debug('params', params)
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return {
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params,
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modelId: model.id,
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capabilities: { enableReasoning, enableWebSearch, enableGenerateImage, enableUrlContext },
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webSearchPluginConfig
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}
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}
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/**
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* 构建非流式的 generateText 参数
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*/
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export async function buildGenerateTextParams(
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messages: ModelMessage[],
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assistant: Assistant,
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provider: Provider,
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options: {
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mcpTools?: MCPTool[]
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enableTools?: boolean
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} = {}
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): Promise<any> {
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// 复用流式参数的构建逻辑
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return await buildStreamTextParams(messages, assistant, provider, options)
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}
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