Add Camb AI as a transcription and translation provider

.env.example

@@ -0,0 +1,11 @@
+BAIDU_KEY=
+BAIDU_SECRET=
+VOLC_KEY=
+VOLC_SECRET=
+
+OLLAMA_API_URL=http://localhost:11434
+OLLAMA_MODEL_NAME=llama3
+OLLAMA_PROMPT=Please translate the following content from ${sourceLanguage} to ${targetLanguage}, only return the translation result can be. \n ${content}
+
+# Camb AI — used for both transcription and translation when selected in config.js
+CAMB_API_KEY=

.env.local

@@ -5,4 +5,6 @@ VOLC_SECRET=
 
 OLLAMA_API_URL=http://localhost:11434
 OLLAMA_MODEL_NAME=llama3
-OLLAMA_PROMPT=Please translate the following content from ${sourceLanguage} to ${targetLanguage}, only return the translation result can be. \n ${content}
+OLLAMA_PROMPT=Please translate the following content from ${sourceLanguage} to ${targetLanguage}, only return the translation result can be. \n ${content}
+
+CAMB_API_KEY=

README.md

@@ -37,6 +37,7 @@
 - 支持百度翻译
 - 支持 deeplx 翻译 （批量翻译容易存在被限流的情况）
 - 支持 ollama 翻译
+- 支持 Camb AI （转录 + 翻译）
 - 自定义字幕文件名，方便兼容不同的播放器挂载字幕识别
 - 自定义翻译后的字幕文件内容，纯翻译结果，原字幕+翻译结果
 - 项目集成 `whisper.cpp`， 它对 apple silicon 进行了优化，有较快的生成速度
@@ -238,6 +239,34 @@ export const contentTemplateRule = contentTemplateRuleMap.onlyTranslate;
 
 5️⃣ 配置好该文件之后，执行 `yarn start` 或者 `npm start`, 首次执行会下载 `whisper.cpp` 和配置的对应的模型文件，会比较慢一些。下次执行将会跳过该流程
 
+## Camb AI (transcription + translation)
+
+This project integrates [Camb AI](https://docs.camb.ai) via the official `@camb-ai/sdk` package. Camb AI can be used as a transcription provider (replacing the local `whisper.cpp` run) and/or as a translation provider.
+
+1. Install the SDK:
+
+   ```bash
+   npm install @camb-ai/sdk
+   ```
+
+2. Add your key to `.env.local` (or copy `.env.example`):
+
+   ```
+   CAMB_API_KEY=your_key_here
+   ```
+
+3. Select Camb AI in `config.js`:
+
+   ```js
+   // transcription (optional — defaults to local whisper.cpp)
+   export const transcriptionServiceProvider = supportedTranscriptionService.camb;
+
+   // translation
+   export const translateServiceProvider = supportedService.camb;
+   ```
+
+The provider implementation lives at `providers/camb.js` and exposes `transcribe(audioPath, opts)` and `translate(text, targetLang, opts)`. The translation path is also wired through `service/camb.js` to match the dynamic-import pattern used by the other providers.
+
 如果在使用过程中遇到啥问题，可以提 Issue 或者通过 Discussions 进行讨论
 
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config.js

@@ -30,11 +30,23 @@ export const supportedService = {
   volc: Symbol.for('volc'),
   deeplx: Symbol.for('deeplx'),
   ollama: Symbol.for('ollama'),
+  camb: Symbol.for('camb'),
 };
 
 // 当前使用的翻译服务商，如果不配置，则不执行翻译流程
 export const translateServiceProvider = supportedService.ollama;
 
+// 支持的转录（语音转文字）服务商
+// whisper: 使用本地 whisper.cpp（默认）
+// camb:    使用 Camb AI 云端转录
+export const supportedTranscriptionService = {
+  whisper: Symbol.for('whisper'),
+  camb: Symbol.for('camb'),
+};
+
+// 当前使用的转录服务商
+export const transcriptionServiceProvider = supportedTranscriptionService.whisper;
+
 // 翻译结果字幕文件内容配置
 export const contentTemplateRuleMap = {
   onlyTranslate: Symbol.for('onlyTranslate'), // 只输出翻译内容

index.js

@@ -3,7 +3,15 @@ import path from 'path';
 import { execSync } from 'child_process';
 import { config } from 'dotenv';
 import app from './translate.js';
-import { sourceSrtSaveName, translateServiceProvider, videoDir, translateConfig ,whisperModel } from './config.js';
+import {
+  sourceSrtSaveName,
+  translateServiceProvider,
+  videoDir,
+  translateConfig,
+  whisperModel,
+  transcriptionServiceProvider,
+  supportedTranscriptionService,
+} from './config.js';
 import { extractAudio, renderFilePath, installWhisper, isDarwin, isWin32 } from './utils.js';
 
 config();
@@ -12,7 +20,9 @@ const { log, error } = console;
 
 const SUPPORTED_VIDEO_FORMATS = ["mp4", "avi", "mov", "mkv", "flv", "wmv", "webm", "m4a"];
 
-await installWhisper();
+if (transcriptionServiceProvider !== supportedTranscriptionService.camb) {
+  await installWhisper();
+}
 fs.readdir(videoDir, async (err, files) => {
   if (err) {
     error(err);
@@ -30,13 +40,22 @@ fs.readdir(videoDir, async (err, files) => {
         await extractAudio(`${videoDir}/${file}`, `${wavFile}`);
         //execSync(`ffmpeg -v quiet -stats -i "${videoDir}/${file}" -ar 16000 -ac 1 -c:a pcm_s16le -y "${wavFile}"`);
         log('完成音频文件提取， 准备生成字幕文件');
-        let mainPath = path.join('./', 'whisper.cpp/main');
-        if(isWin32()){
-          mainPath = path.join('./', 'whisper-bin-x64/main.exe');
+        if (transcriptionServiceProvider === supportedTranscriptionService.camb) {
+          const { transcribe } = await import('./providers/camb.js');
+          const srt = await transcribe(wavFile, {
+            sourceLanguage: translateConfig.sourceLanguage,
+            format: 'srt',
+          });
+          fs.writeFileSync(`${srtFile}.srt`, srt);
+        } else {
+          let mainPath = path.join('./', 'whisper.cpp/main');
+          if(isWin32()){
+            mainPath = path.join('./', 'whisper-bin-x64/main.exe');
+          }
+          execSync(
+            `${mainPath} -m ./whisper.cpp/models/ggml-${whisperModel}.bin -f "${wavFile}" -osrt -of "${srtFile}" -l ${translateConfig.sourceLanguage}`
+          )
         }
-        execSync(
-          `${mainPath} -m ./whisper.cpp/models/ggml-${whisperModel}.bin -f "${wavFile}" -osrt -of "${srtFile}" -l ${translateConfig.sourceLanguage}`
-        )
         log('完成字幕文件生成， 准备开始翻译');
         if (translateServiceProvider) {
           await app(videoDir, fileName, `${srtFile}.srt`);