
Most common position in a pipeline	As the first component to route a query to different Retrievers , based on its language
Mandatory init variables	"languages": A list of ISO language codes
Mandatory run variables	“text”: A string
Output variables	“unmatched”: A string “language defined during initialization”: A string. For example: "fr": French language string.
API reference	Routers
GitHub link	https://github.com/deepset-ai/haystack/blob/main/haystack/components/routers/text_language_router.py

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?"}})