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It provides a unified interface to interact with different MT and AI services, allowing you to translate text between multiple languages.\n\nInterface `MTEngine` provides these methods:\n\n```typescript\n    getName(): string;\n    getShortName(): string;\n    getSourceLanguages(): Promise<string[]>;\n    getTargetLanguages(): Promise<string[]>;\n    setSourceLanguage(lang: string): void;\n    getSourceLanguage(): string;\n    setTargetLanguage(lang: string): void;\n    getTargetLanguage(): string;\n    translate(source: string): Promise<string>;\n    getMTMatch(source: string): Promise<MTMatch>;\n    handlesTags(): boolean;\n    fixesMatches(): boolean;\n    fixMatch(originalSource: XMLElement, matchSource: XMLElement, matchTarget: XMLElement): Promise<MTMatch>;\n    fixesTags(): boolean;\n    fixTags(source: XMLElement, target: XMLElement): Promise<XMLElement>;\n```\n\nAll supported engines implement the `MTEngine` interface. Methods `fixMatch()` and `fixTags()` are only implemented by AI-based engines (`QwenTranslator`, `ChatGPTTranslator`, `AnthropicTranslator`, `MistralTranslator` and `GeminiTranslator`), all other engines throw an error when they are called.\n\n`Ollama` engine allows you to work with locally instaled models served by the [Ollama](https://ollama.com/) platform without sending source text to external servers.\n\nWhen creating an instance of `OllamaTranslator`, you must pass the URL where Ollama is running (usually `http://localhost:11434`), the name of the model to use and optionally a `think` boolean parameter that when set to `true` can speed up the translation process.\n\n## Supported Engines\n\n- Alibaba Qwen Models\n- Anthropic Claude\n- DeepL (Free and Pro)\n- Google Cloud Translation\n- Google Gemini\n- Microsoft Azure Translator Text\n- Mistral AI\n- ModernMT\n- Ollama\n- OpenAI ChatGPT\n\n## Installation\n\n```bash\nnpm install mtengines\n```\n\n> **Note**: The library requires Node.js 24 or newer to ensure the built-in `fetch` API is available at runtime.\n\n## Examples\n\n```typescript\nimport { GoogleTranslator } from \"mtengines\";\n\nclass TestGoogle {\n\n    constructor() {\n        let translator: GoogleTranslator = new GoogleTranslator('yourApiKey');\n        translator.setSourceLanguage(\"en\");\n        translator.setTargetLanguage(\"ja\");\n         translator.translate(\"Hello World\").then((result: string) => {\n            console.log(result);\n        }, (error: any) => {\n            console.error(error);\n        });\n    }\n}\n\nnew TestGoogle();\n```\n\n`QwenTranslator`, `ChatGPTTranslator`, `AnthropicTranslator`, `MistralTranslator`, `GeminiTranslator` and `Ollama` need that you either indicate the model to use when creating the instance, or set the model to use by calling the `setModel()` method like in the following example:\n\n```typescript\nimport { ChatGPTTranslator } from \"mtengines\";\nclass TestChatGPT {\n\n    constructor() {\n        let translator: ChatGPTTranslator = new ChatGPTTranslator('yourApiKey');\n        translator.setModel(\"gpt-4\");\n        translator.setSourceLanguage(\"en\");\n        translator.setTargetLanguage(\"fr\");\n         translator.translate(\"Hello World\").then((result: string) => {\n            console.log(result);\n        }, (error: any) => {\n            console.error(error);\n        });\n    }\n}\n\nnew TestChatGPT();\n```\n\nYou can get a list of models supported by `QwenTranslator`, `ChatGPTTranslator`, `AnthropicTranslator`, `MistralTranslator`, `OllamaTranslator` and `GeminiTranslator` by calling the `getAvailableModels()` method:\n\n```typescript\nimport { AnthropicTranslator } from \"mtengines\";\nclass TestModels {   \n\n    constructor() {\n        let claude: AnthropicTranslator = new AnthropicTranslator('yourApiKey');\n        claude.getAvailableModels().then((models: string[][]) => {\n            console.log('Claude available models:');\n            console.log(models);\n        }, (error) => {\n            console.error(error);\n        });\n    }\n}\nnew TestModels();\n```\n\nExpected output:\n\n``` text\nClaude available models:\n[\n  [ 'claude-opus-4-5-20251101', 'Claude Opus 4.5' ],\n  [ 'claude-haiku-4-5-20251001', 'Claude Haiku 4.5' ],\n  [ 'claude-sonnet-4-5-20250929', 'Claude Sonnet 4.5' ],\n  [ 'claude-opus-4-1-20250805', 'Claude Opus 4.1' ],\n  [ 'claude-opus-4-20250514', 'Claude Opus 4' ],\n  [ 'claude-sonnet-4-20250514', 'Claude Sonnet 4' ],\n  [ 'claude-3-7-sonnet-20250219', 'Claude Sonnet 3.7' ],\n  [ 'claude-3-5-haiku-20241022', 'Claude Haiku 3.5' ],\n  [ 'claude-3-haiku-20240307', 'Claude Haiku 3' ],\n  [ 'claude-3-opus-20240229', 'Claude Opus 3' ]\n]\n```\n\n*Note*: Only `QwenTranslator` has a set of preconfigured models that depend on the selected working `region`, for all other AI-based engines the list of available models is retrieved at runtime.\n","readmeFilename":"README.md"}