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Add Lara integration (#403)
* Add Lara integration page * Update Lara integration to include a link to the `LaraDocumentTranslator` documenation page
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integrations/lara.md

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---
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layout: integration
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name: Lara
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description: Translate Haystack documents using translated's Lara adaptive translation API
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authors:
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- name: deepset
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socials:
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github: deepset-ai
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twitter: deepset_ai
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linkedin: https://www.linkedin.com/company/deepset-ai/
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pypi: https://pypi.org/project/lara-haystack/
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repo: https://github.com/deepset-ai/haystack-core-integrations/tree/main/integrations/lara
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type: Custom Component
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report_issue: https://github.com/deepset-ai/haystack-core-integrations/issues
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logo: /logos/lara.png
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version: Haystack 2.0
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toc: true
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---
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### **Table of Contents**
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- [Overview](#overview)
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- [Installation](#installation)
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- [Usage](#usage)
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- [Components](#components)
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- [API Keys](#api-keys)
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- [Examples](#examples)
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- [Standalone](#standalone)
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- [Pipeline](#pipeline)
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- [License](#license)
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## Overview
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[Lara](https://laratranslate.com/) is an adaptive translation API by [translated](https://translated.com/) 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.
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Key features:
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- **Translation styles**: Choose between `faithful`, `fluid`, or `creative` styles to control the balance between accuracy and natural flow.
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- **Context-aware translation**: Provide surrounding text as context to improve translation quality without translating it.
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- **Instruction-guided translation**: Use natural-language instructions to guide translations (e.g. "Be formal", "Use a professional tone").
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- **Translation memories**: Adapt translations to the style and terminology of existing translation memories.
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- **Glossaries**: Enforce consistent terminology (e.g. brand names, product terms) across translations.
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- **Reasoning (Lara Think)**: Enable multi-step linguistic analysis for higher-quality translations.
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For more details, see the [Lara SDK documentation](https://developers.laratranslate.com/docs/introduction) and the [Lara support documentation](https://support.laratranslate.com/en).
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## Installation
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```bash
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pip install lara-haystack
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```
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## Usage
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### Components
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This integration provides one component:
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- The [`LaraDocumentTranslator`](https://docs.haystack.deepset.ai/docs/laradocumenttranslator): translates the text content of Haystack `Document` objects using the Lara API.
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### API Keys
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To use the Lara integration, you need a Lara API access key ID and secret. You can obtain them from [Lara](https://laratranslate.com/).
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Once obtained, export them as environment variables:
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```bash
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export LARA_ACCESS_KEY_ID="your-access-key-id"
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export LARA_ACCESS_KEY_SECRET="your-access-key-secret"
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```
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By default, `LaraDocumentTranslator` reads the API credentials from these environment variables. You can also pass them explicitly using the Haystack [Secret](https://docs.haystack.deepset.ai/reference/utils-api#secret) utility.
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## Examples
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### Standalone
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The following example translates a list of Documents from English to German:
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```python
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from haystack import Document
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from haystack_integrations.components.translators.lara import LaraDocumentTranslator
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translator = LaraDocumentTranslator(
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source_lang="en-US",
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target_lang="de-DE",
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)
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documents = [
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Document(content="Hello, world!"),
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Document(content="Goodbye, world!"),
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]
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result = translator.run(documents=documents)
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for doc in result["documents"]:
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print(doc.content)
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```
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### Pipeline
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You can use `LaraDocumentTranslator` in a Haystack pipeline. The following example converts text files to Documents, translates them, and writes them to an `InMemoryDocumentStore`:
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```python
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from haystack import Pipeline
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from haystack.components.converters import TextFileToDocument
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from haystack.components.writers import DocumentWriter
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from haystack.document_stores.in_memory import InMemoryDocumentStore
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from haystack_integrations.components.translators.lara import LaraDocumentTranslator
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document_store = InMemoryDocumentStore()
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pipeline = Pipeline()
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pipeline.add_component("converter", TextFileToDocument())
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pipeline.add_component(
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"translator",
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LaraDocumentTranslator(source_lang="en-US", target_lang="es-ES"),
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)
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pipeline.add_component("writer", DocumentWriter(document_store=document_store))
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pipeline.connect("converter", "translator")
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pipeline.connect("translator", "writer")
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pipeline.run({"converter": {"sources": ["filename.txt"]}})
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print(document_store.filter_documents())
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```
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### License
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`lara-haystack` is distributed under the terms of the
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[Apache-2.0](https://opensource.org/license/apache-2-0) license.

logos/lara.png

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