refactor(translate): 重构语言检测功能，使用通用聊天接口替代专用接口

- 移除专用的语言检测接口 fetchLanguageDetection
- 使用现有的 fetchChatCompletion 接口实现语言检测功能
- 处理 QwenMT 模型的特殊逻辑
- 优化语言检测的提示词和参数处理

src/renderer/src/services/ApiService.ts

@@ -7,8 +7,7 @@ import { CompletionsParams } from '@renderer/aiCore/legacy/middleware/schemas'
 import { AiSdkMiddlewareConfig } from '@renderer/aiCore/middleware/AiSdkMiddlewareBuilder'
 import { buildStreamTextParams } from '@renderer/aiCore/transformParameters'
 import type { StreamTextParams } from '@renderer/aiCore/types'
-import { isDedicatedImageGenerationModel, isEmbeddingModel, isQwenMTModel } from '@renderer/config/models'
+import { isDedicatedImageGenerationModel, isEmbeddingModel } from '@renderer/config/models'
-import { LANG_DETECT_PROMPT } from '@renderer/config/prompts'
 import { getStoreSetting } from '@renderer/hooks/useSettings'
 import i18n from '@renderer/i18n'
 import store from '@renderer/store'
@@ -20,7 +19,6 @@ import { removeSpecialCharactersForTopicName } from '@renderer/utils'
 import { isPromptToolUse, isSupportedToolUse } from '@renderer/utils/mcp-tools'
 import { findFileBlocks, getMainTextContent } from '@renderer/utils/messageUtils/find'
 import { containsSupportedVariables, replacePromptVariables } from '@renderer/utils/prompt'
-import { getTranslateOptions } from '@renderer/utils/translate'
 import { isEmpty, takeRight } from 'lodash'
 
 import AiProviderNew from '../aiCore/index_new'
@@ -172,74 +170,6 @@ export async function fetchChatCompletion({
   })
 }
 
-interface FetchLanguageDetectionProps {
-  text: string
-  onResponse?: (text: string, isComplete: boolean) => void
-}
-
-/**
- * 检测文本语言
- * @param params - 参数对象
- * @param {string} params.text - 需要检测语言的文本内容
- * @param {function} [params.onResponse] - 流式响应回调函数,用于实时获取检测结果
- * @returns {Promise<string>} 返回检测到的语言代码,如果检测失败会抛出错误
- * @throws {Error}
- */
-export async function fetchLanguageDetection({ text, onResponse }: FetchLanguageDetectionProps) {
-  const translateLanguageOptions = await getTranslateOptions()
-  const listLang = translateLanguageOptions.map((item) => item.langCode)
-  const listLangText = JSON.stringify(listLang)
-
-  const model = getQuickModel() || getDefaultModel()
-  if (!model) {
-    throw new Error(i18n.t('error.model.not_exists'))
-  }
-
-  if (isQwenMTModel(model)) {
-    logger.info('QwenMT cannot be used for language detection.')
-    if (isQwenMTModel(model)) {
-      throw new Error(i18n.t('translate.error.detect.qwen_mt'))
-    }
-  }
-
-  const provider = getProviderByModel(model)
-
-  if (!hasApiKey(provider)) {
-    throw new Error(i18n.t('error.no_api_key'))
-  }
-
-  const assistant: Assistant = getDefaultAssistant()
-
-  assistant.model = model
-  assistant.settings = {
-    temperature: 0.7
-  }
-  assistant.prompt = LANG_DETECT_PROMPT.replace('{{list_lang}}', listLangText).replace('{{input}}', text)
-
-  const isSupportedStreamOutput = () => {
-    if (!onResponse) {
-      return false
-    }
-    return true
-  }
-
-  const stream = isSupportedStreamOutput()
-
-  const params: CompletionsParams = {
-    callType: 'translate-lang-detect',
-    messages: 'follow system prompt',
-    assistant,
-    streamOutput: stream,
-    enableReasoning: false,
-    shouldThrow: true,
-    onResponse
-  }
-
-  const AI = new AiProvider(provider)
-
-  return (await AI.completions(params)).getText()
-}
-
 export async function fetchMessagesSummary({ messages, assistant }: { messages: Message[]; assistant: Assistant }) {
   let prompt = (getStoreSetting('topicNamingPrompt') as string) || i18n.t('prompts.title')
   const model = getQuickModel() || assistant.model || getDefaultModel()

src/renderer/src/utils/translate.ts

@@ -1,10 +1,15 @@
 import { loggerService } from '@logger'
+import { isQwenMTModel } from '@renderer/config/models'
+import { LANG_DETECT_PROMPT } from '@renderer/config/prompts'
 import { builtinLanguages as builtinLanguages, LanguagesEnum, UNKNOWN } from '@renderer/config/translate'
 import db from '@renderer/databases'
-import { fetchLanguageDetection } from '@renderer/services/ApiService'
+import i18n from '@renderer/i18n'
+import { fetchChatCompletion } from '@renderer/services/ApiService'
+import { getDefaultAssistant, getDefaultModel, getQuickModel } from '@renderer/services/AssistantService'
 import { estimateTextTokens } from '@renderer/services/TokenService'
 import { getAllCustomLanguages } from '@renderer/services/TranslateService'
-import { TranslateLanguage, TranslateLanguageCode } from '@renderer/types'
+import { Assistant, TranslateLanguage, TranslateLanguageCode } from '@renderer/types'
+import { Chunk, ChunkType } from '@renderer/types/chunk'
 import { franc } from 'franc-min'
 import React, { RefObject } from 'react'
 import { sliceByTokens } from 'tokenx'
@@ -55,13 +60,41 @@ export const detectLanguage = async (inputText: string): Promise<TranslateLangua
 const detectLanguageByLLM = async (inputText: string): Promise<TranslateLanguageCode> => {
   logger.info('Detect language by llm')
   let detectedLang = ''
-  await fetchLanguageDetection({
+  const text = sliceByTokens(inputText, 0, 100)
-    text: sliceByTokens(inputText, 0, 100),
+
-    onResponse: (text) => {
+  const translateLanguageOptions = await getTranslateOptions()
-      detectedLang = text.replace(/^\s*\n+/g, '')
+  const listLang = translateLanguageOptions.map((item) => item.langCode)
+  const listLangText = JSON.stringify(listLang)
+
+  const model = getQuickModel() || getDefaultModel()
+  if (!model) {
+    throw new Error(i18n.t('error.model.not_exists'))
+  }
+
+  if (isQwenMTModel(model)) {
+    logger.info('QwenMT cannot be used for language detection.')
+    if (isQwenMTModel(model)) {
+      throw new Error(i18n.t('translate.error.detect.qwen_mt'))
     }
-  })
+  }
-  return detectedLang
+
+  const assistant: Assistant = getDefaultAssistant()
+
+  assistant.model = model
+  assistant.settings = {
+    temperature: 0.7
+  }
+  assistant.prompt = LANG_DETECT_PROMPT.replace('{{list_lang}}', listLangText).replace('{{input}}', text)
+
+  const onChunk: (chunk: Chunk) => void = (chunk: Chunk) => {
+    // 你的意思是，虽然写的是delta类型，但其实是完整拼接后的结果？
+    if (chunk.type === ChunkType.TEXT_DELTA) {
+      detectedLang = chunk.text
+    }
+  }
+
+  await fetchChatCompletion({ prompt: 'follow system prompt', assistant, onChunkReceived: onChunk })
+  return detectedLang.trim()
 }
 
 const detectLanguageByFranc = (inputText: string): TranslateLanguageCode => {