The Translator does what it says on the tin: it translates text from one language into another. Have a look at examples of how to use the Translator in your search app.
Some translation models are language-specific while others are multilingual. See the Hugging Face Model Hub for a list of available models.
You can use the Translator component directly to translate your query or documents:
from haystack import Document from haystack.nodes import TransformersTranslator DOCS = [ Document( content="""Heinz von Foerster was an Austrian American scientist combining physics and philosophy, and widely attributed as the originator of Second-order cybernetics.""" ) ] translator = TransformersTranslator(model_name_or_path="Helsinki-NLP/opus-mt-en-fr") res = translator.translate(documents=DOCS, query=None)
Using the TranslationWrapperPipeline
Let's imagine you have an English corpus of technical docs, but the mother tongue of many of your users is French. You can use a
Translator node in your pipeline to:
- Translate the incoming query from French to English.
- Search in your English corpus for the right document or answer.
- Translate the results back from English to French.
from haystack.pipelines import TranslationWrapperPipeline, DocumentSearchPipeline from haystack.nodes import TransformersTranslator pipeline = DocumentSearchPipeline(retriever=my_dpr_retriever) in_translator = TransformersTranslator(model_name_or_path="Helsinki-NLP/opus-mt-fr-en") out_translator = TransformersTranslator(model_name_or_path="Helsinki-NLP/opus-mt-en-fr") pipeline_with_translation = TranslationWrapperPipeline(input_translator=in_translator, output_translator=out_translator, pipeline=pipeline)
Updated 8 months ago