Integration: Lara

Translate Haystack documents using translated's Lara adaptive translation API

Authors

deepset

Table of Contents

• Overview
• Installation
• Usage
  • Components
  • API Keys
• Examples
  • Standalone
  • Pipeline
• License

Overview

Lara is an adaptive translation API by translated that combines the fluency and context handling of LLMs with low hallucination and latency. It adapts to domains at inference time using optional context, instructions, translation memories, and glossaries.

Key features:

• Translation styles: Choose between faithful, fluid, or creative styles to control the balance between accuracy and natural flow.
• Context-aware translation: Provide surrounding text as context to improve translation quality without translating it.
• Instruction-guided translation: Use natural-language instructions to guide translations (e.g. “Be formal”, “Use a professional tone”).
• Translation memories: Adapt translations to the style and terminology of existing translation memories.
• Glossaries: Enforce consistent terminology (e.g. brand names, product terms) across translations.
• Reasoning (Lara Think): Enable multi-step linguistic analysis for higher-quality translations.

For more details, see the Lara SDK documentation and the Lara support documentation.

Installation

pip install lara-haystack

Usage

Components

This integration provides one component:

• The LaraDocumentTranslator: translates the text content of Haystack Document objects using the Lara API.

API Keys

To use the Lara integration, you need a Lara API access key ID and secret. You can obtain them from Lara.

Once obtained, export them as environment variables:

export LARA_ACCESS_KEY_ID="your-access-key-id"
export LARA_ACCESS_KEY_SECRET="your-access-key-secret"

By default, LaraDocumentTranslator reads the API credentials from these environment variables. You can also pass them explicitly using the Haystack Secret utility.

Examples

Standalone

The following example translates a list of Documents from English to German:

from haystack import Document
from haystack_integrations.components.translators.lara import LaraDocumentTranslator

translator = LaraDocumentTranslator(
    source_lang="en-US",
    target_lang="de-DE",
)

documents = [
    Document(content="Hello, world!"),
    Document(content="Goodbye, world!"),
]

result = translator.run(documents=documents)
for doc in result["documents"]:
    print(doc.content)

Pipeline

You can use LaraDocumentTranslator in a Haystack pipeline. The following example converts text files to Documents, translates them, and writes them to an InMemoryDocumentStore:

from haystack import Pipeline
from haystack.components.converters import TextFileToDocument
from haystack.components.writers import DocumentWriter
from haystack.document_stores.in_memory import InMemoryDocumentStore

from haystack_integrations.components.translators.lara import LaraDocumentTranslator

document_store = InMemoryDocumentStore()

pipeline = Pipeline()
pipeline.add_component("converter", TextFileToDocument())
pipeline.add_component(
    "translator",
    LaraDocumentTranslator(source_lang="en-US", target_lang="es-ES"),
)
pipeline.add_component("writer", DocumentWriter(document_store=document_store))

pipeline.connect("converter", "translator")
pipeline.connect("translator", "writer")

pipeline.run({"converter": {"sources": ["filename.txt"]}})
print(document_store.filter_documents())

License

lara-haystack is distributed under the terms of the Apache-2.0 license.