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TranslatorMistralCloud Class Documentation

The TranslatorMistralCloud class is fully compatible with both TranslatorOpenSourceLLM and TranslatorOpenAI classes. It contains all their methods and uses models hosted on the Mistral cloud for translation, language detection, and other tasks, providing the same functionality with cloud-based execution.

How to Use

Initialization

To use the TranslatorMistralCloud class, initialize it with your Mistral API key. Optionally, you can specify a model, with MISTRAL_LARGE as the default.

from llmtranslate import TranslatorMistralCloud, ModelForTranslator

translator = TranslatorMistralCloud(
    api_key="your_api_key_here", 
    model="open-mistral-nemo"
)

Choose Mistral model

The TranslatorMistralCloud class allows you to choose a translation model when initializing. By default, it uses MISTRAL_LARGE, but you can specify other models using the ModelForTranslator enum or as a string.

Example using Enum: 

from llmtranslate import TranslatorMistralCloud, ModelForTranslator

translator = TranslatorMistralCloud(
    api_key="your_api_key_here", 
    model=ModelForTranslator.MISTRAL_NEMO
)

Example using String 

from llmtranslate import TranslatorMistralCloud, ModelForTranslator

translator = TranslatorMistralCloud(
    api_key="your_api_key_here", 
    model="open-mistral-nemo"
)

Translate

Translates the provided text into the specified language using the ISO 639-1 code.

  • Parameters:
  • text: The text to translate.
  • to_language: Target language (default is English: "eng").
from llmtranslate import TranslatorMistralCloud
translator = TranslatorMistralCloud(
    api_key="your_api_key_here", 
    model="open-mistral-nemo"
)
translated_text = translator.translate("Bonjour", "en")
print(translated_text)  # Output: Hello

Detect language

Detects the language of the given text and returns its ISO 639-1 code.

from llmtranslate import TranslatorMistralCloud
translator = TranslatorMistralCloud(
    api_key="your_api_key_here", 
    model="open-mistral-nemo"
)
detected_language = translator.get_text_language("jak ty się nazywasz")
if detected_language is not None:
    print(detected_language.ISO_639_1_code)  # Output: 'pl'
    print(detected_language.ISO_639_2_code)  # Output: 'pol'
    print(detected_language.ISO_639_3_code)  # Output: 'pol'
    print(detected_language.language_name)  # Output 'Polish'

Warning

If the translator does not detect any language, it will return None.
Before using results of translator detection you should check if it returned correct result or None

Example Usage

from llmtranslate import TranslatorMistralCloud
translator = TranslatorMistralCloud(
    api_key="your_api_key_here", 
    model="open-mistral-nemo"
)

# Translate text to English
translated_text = translator.translate("こんにちは", "en")
print(translated_text)  # Output: Hello

# Detect language
detected_language = translator.get_text_language("jak ty się nazywasz")
if detected_language is not None:
    print(detected_language.ISO_639_1_code)  # Output: 'pl'
    print(detected_language.ISO_639_2_code)  # Output: 'pol'
    print(detected_language.ISO_639_3_code)  # Output: 'pol'
    print(detected_language.language_name)  # Output 'Polish'