TextLanguageRouter
Use this component in pipelines to route a query based on its language.
Name | TextLanguageRouter |
Folder path | /routers/ |
Most common position in a pipeline | As the first component to route a query to different Retrievers, based on its language |
Mandatory input variables | “text”: A string |
Output variables | “unmatched”: A string “language defined during initialization”: A string. For example: "fr": French language string. |
Overview
TextLanguageRouter
detects the language of an input string and routes it to an output named after the language if it's in the set of languages the component was initialized with. By default, only English is in this set. If the detected language of the input text is not in the component’s languages
, it's routed to an output named unmatched
.
In pipelines, it's used as the first component to route a query based on its language and filter out queries in unsupported languages.
The components parameter languages
must be a list of languages in ISO code, such as en, de, fr, es, it, each corresponding to a different output connection (see langdetect documentation)).
Usage
On its own
Below is an example where using the TextLanguageRouter
to route only French texts to an output connection named fr
. Other texts, such as the English text below, are routed to an output named unmatched
.
from haystack.components.routers import TextLanguageRouter
router = TextLanguageRouter(languages=["fr"])
router.run(text="What's your query?")
In a pipeline
Below is an example of a query pipeline that uses a TextLanguageRouter
to forward only English language queries to the Retriever.
from haystack import Pipeline
from haystack.components.routers import TextLanguageRouter
from haystack.document_stores.in_memory import InMemoryDocumentStore
from haystack.components.retrievers.in_memory import InMemoryBM25Retriever
document_store = InMemoryDocumentStore()
p = Pipeline()
p.add_component(instance=TextLanguageRouter(), name="text_language_router")
p.add_component(instance=InMemoryBM25Retriever(document_store=document_store), name="retriever")
p.connect("text_language_router.en", "retriever.query")
p.run({"text_language_router": {"text": "What's your query?"}})
Updated 5 months ago