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+---
+layout: integration
+name: Lara
+description: Translate Haystack documents using translated's Lara adaptive translation API
+authors:
+  - name: deepset
+    socials:
+      github: deepset-ai
+      twitter: deepset_ai
+      linkedin: https://www.linkedin.com/company/deepset-ai/
+pypi: https://pypi.org/project/lara-haystack/
+repo: https://github.com/deepset-ai/haystack-core-integrations/tree/main/integrations/lara
+type: Custom Component
+report_issue: https://github.com/deepset-ai/haystack-core-integrations/issues
+logo: /logos/lara.png
+version: Haystack 2.0
+toc: true
+---
+
+### **Table of Contents**
+
+- [Overview](#overview)
+- [Installation](#installation)
+- [Usage](#usage)
+  - [Components](#components)
+  - [API Keys](#api-keys)
+- [Examples](#examples)
+  - [Standalone](#standalone)
+  - [Pipeline](#pipeline)
+- [License](#license)
+
+## Overview
+
+[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.
+
+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](https://developers.laratranslate.com/docs/introduction) and the [Lara support documentation](https://support.laratranslate.com/en).
+
+## Installation
+
+```bash
+pip install lara-haystack
+```
+
+## Usage
+
+### Components
+
+This integration provides one component:
+
+- The [`LaraDocumentTranslator`](https://docs.haystack.deepset.ai/docs/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](https://laratranslate.com/).
+
+Once obtained, export them as environment variables:
+
+```bash
+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](https://docs.haystack.deepset.ai/reference/utils-api#secret) utility.
+
+## Examples
+
+### Standalone
+
+The following example translates a list of Documents from English to German:
+
+```python
+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`:
+
+```python
+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](https://opensource.org/license/apache-2-0) license.
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