Translate

You can get machine translation and translation quality scores from the /translate REST API endpoint or any of the official SDKs (Python, Go, Rust, JS, or cURL).

Under the hood, the /translate endpoint simultaneously leverages multiple state-of-the-art LLM and machine translation models to perform translations. The translations from these models are scored and ranked using reference-free quality estimation models. This allows us to select the highest quality machine translation for the given source and target languages.

The /translate endpoint will return a JSON object response with two fields:

• Best translation - The translated text.
• Score - A score from -1.0 to 1.0 representing the translation quality. Higher the score better the quality.

Additionally, you can opt to use third-party translation engines such as OpenAI, DeepL, and Google. By default, the use of these commercial engines is set to false.

Our translation API supports a wide range of languages, including but not limited to English, Hindi, French, Spanish, German, and more.

Generate a Translation

To generate a translation, you can use the following code examples. Depending on your preference or requirements, select the appropriate method for your application.

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import os
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import json
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from predictionguard import PredictionGuard
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# Set your Prediction Guard token as an environmental variable.
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os.environ["PREDICTIONGUARD_API_KEY"] = "<api key>"
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client = PredictionGuard()
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# Translate the text.
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result = client.translate.create(
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    		text="The sky is blue",
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            source_lang="eng",
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            target_lang="fra",
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            use_third_party_engine=True
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    )
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print(json.dumps(
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    result,
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    sort_keys=True,
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    indent=4,
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    separators=(',', ': ')
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))

The output will look something like:

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{
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    "translations": [
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        {
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            "score": 0.8694148659706116,
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            "translation": "Le ciel est bleu",
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            "model": "hermes_2_pro_llama_3_8b",
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            "status": "success"
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        },
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        {
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            "score": 0.8694148659706116,
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            "translation": "Le ciel est bleu",
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            "model": "hermes_2_pro_mistral_7b",
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            "status": "success"
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        },
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        {
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            "score": 0.8694148659706116,
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            "translation": "Le ciel est bleu",
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            "model": "openai",
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            "status": "success"
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        },
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        {
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            "score": 0.8694148659706116,
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            "translation": "Le ciel est bleu",
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            "model": "deepl",
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            "status": "success"
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        },
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        {
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            "score": 0.8694148659706116,
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            "translation": "Le ciel est bleu",
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            "model": "google",
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            "status": "success"
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        }
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    ],
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    "best_translation": "Le ciel est bleu",
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    "best_score": 0.8694148659706116,
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    "best_translation_model": "hermes_2_pro_llama_3_8b",
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    "created": 1721136682,
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    "id": "translation-52929bae5c2c44c9b5177921958cb5f7",
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    "object": "translation"
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}

This approach presents a straightforward way for readers to choose and apply the code example that best suits their needs for generating text completions using either Python, Go, Rust, JS, or cURL.