---
title: Bedrock Translator Agent
description: Documentation for the Bedrock Translator Agent in the Multi-Agent Orchestrator System
---

The `BedrockTranslatorAgent` uses Amazon Bedrock's language models to translate text between different languages.

## Key Features

- Utilizes Amazon Bedrock's language models
- Supports translation between multiple languages
- Allows dynamic setting of source and target languages
- Can be used standalone or as part of a [ChainAgent](/multi-agent-orchestrator/agents/built-in/chain-agent)
- Configurable inference parameters for fine-tuned control

## Creating a Bedrock Translator Agent

### Basic Example

To create a new `BedrockTranslatorAgent` with minimal configuration:

import { Tabs, TabItem } from '@astrojs/starlight/components';

<Tabs syncKey="runtime">
  <TabItem label="TypeScript" icon="seti:typescript" color="blue">
    ```typescript
    import { BedrockTranslatorAgent, BedrockTranslatorAgentOptions } from 'multi-agent-orchestrator';

    const agent = new BedrockTranslatorAgent({
      name: 'BasicTranslator',
      description: 'Translates text to English',
      targetLanguage: 'English'
    });
    ```
  </TabItem>
  <TabItem label="Python" icon="seti:python">
    ```python
    from multi_agent_orchestrator.agents import BedrockTranslatorAgent, BedrockTranslatorAgentOptions

    agent = BedrockTranslatorAgent(BedrockTranslatorAgentOptions(
        name='BasicTranslator',
        description='Translates text to English',
        target_language='English'
    ))
    ```
  </TabItem>
</Tabs>

### Advanced Example

For more complex use cases, you can create a BedrockTranslatorAgent with custom settings:

<Tabs syncKey="runtime">
  <TabItem label="TypeScript" icon="seti:typescript" color="blue">
    ```typescript
    import { BedrockTranslatorAgent, BedrockTranslatorAgentOptions, BEDROCK_MODEL_ID_CLAUDE_3_SONNET } from 'multi-agent-orchestrator';

    const options: BedrockTranslatorAgentOptions = {
      name: 'AdvancedTranslator',
      description: 'Advanced translator with custom settings',
      sourceLanguage: 'French',
      targetLanguage: 'German',
      modelId: BEDROCK_MODEL_ID_CLAUDE_3_SONNET,
      region: 'us-west-2',
      inferenceConfig: {
        maxTokens: 2000,
        temperature: 0.1,
        topP: 0.95,
        stopSequences: ['###']
      }
    };

    const agent = new BedrockTranslatorAgent(options);
    ```
  </TabItem>
  <TabItem label="Python" icon="seti:python">
    ```python
    from multi_agent_orchestrator.agents import BedrockTranslatorAgent, BedrockTranslatorAgentOptions
    from multi_agent_orchestrator.types import BEDROCK_MODEL_ID_CLAUDE_3_SONNET

    options = BedrockTranslatorAgentOptions(
        name='AdvancedTranslator',
        description='Advanced translator with custom settings',
        source_language='French',
        target_language='German',
        model_id=BEDROCK_MODEL_ID_CLAUDE_3_SONNET,
        region='us-west-2',
        inference_config={
            'maxTokens': 2000,
            'temperature': 0.1,
            'topP': 0.95,
            'stopSequences': ['###']
        }
    )

    agent = BedrockTranslatorAgent(options)
    ```
  </TabItem>
</Tabs>

## Dynamic Language Setting

To set the language during the invocation:

<Tabs syncKey="runtime">
  <TabItem label="TypeScript" icon="seti:typescript" color="blue">
    ```typescript
    import { MultiAgentOrchestrator, BedrockTranslatorAgent } from 'multi-agent-orchestrator';

    const translator = new BedrockTranslatorAgent({
      name: 'DynamicTranslator',
      description: 'Translator with dynamically set languages'
    });

    const orchestrator = new MultiAgentOrchestrator();
    orchestrator.addAgent(translator);

    async function translateWithDynamicLanguages(text: string, fromLang: string, toLang: string) {
      translator.setSourceLanguage(fromLang);
      translator.setTargetLanguage(toLang);

      const response = await orchestrator.routeRequest(
        text,
        'user123',
        'session456'
      );

      console.log(`Translated from ${fromLang} to ${toLang}:`, response);
    }

    // Usage
    translateWithDynamicLanguages("Hello, world!", "English", "French");
    translateWithDynamicLanguages("Bonjour le monde!", "French", "Spanish");
    ```
  </TabItem>
  <TabItem label="Python" icon="seti:python">
    ```python
    from multi_agent_orchestrator.orchestrator import MultiAgentOrchestrator
    from multi_agent_orchestrator.agents import BedrockTranslatorAgent, BedrockTranslatorAgentOptions

    translator = BedrockTranslatorAgent(BedrockTranslatorAgentOptions(
        name='DynamicTranslator',
        description='Translator with dynamically set languages'
    ))

    orchestrator = MultiAgentOrchestrator()
    orchestrator.add_agent(translator)

    async def translate_with_dynamic_languages(text: str, from_lang: str, to_lang: str):
        translator.set_source_language(from_lang)
        translator.set_target_language(to_lang)

        response = await orchestrator.route_request(
            text,
            'user123',
            'session456'
        )

        print(f"Translated from {from_lang} to {to_lang}:", response)

    # Usage
    import asyncio

    asyncio.run(translate_with_dynamic_languages("Hello, world!", "English", "French"))
    asyncio.run(translate_with_dynamic_languages("Bonjour le monde!", "French", "Spanish"))
    ```
  </TabItem>
</Tabs>

## Usage with ChainAgent

The `BedrockTranslatorAgent` can be effectively used within a `ChainAgent` for complex multilingual processing workflows. Here's an example that demonstrates translating user input and processing it:

<Tabs syncKey="runtime">
  <TabItem label="TypeScript" icon="seti:typescript" color="blue">
    ```typescript
    import { MultiAgentOrchestrator, ChainAgent, BedrockTranslatorAgent, BedrockLLMAgent } from 'multi-agent-orchestrator';

    // Create translator agents
    const translatorToEnglish = new BedrockTranslatorAgent({
      name: 'TranslatorToEnglish',
      description: 'Translates input to English',
      targetLanguage: 'English'
    });

    // Create a processing agent (e.g., a BedrockLLMAgent)
    const processor = new BedrockLLMAgent({
      name: 'EnglishProcessor',
      description: 'Processes text in English'
    });

    // Create a ChainAgent
    const chainAgent = new ChainAgent({
      name: 'TranslateProcessTranslate',
      description: 'Translates, processes, and translates back',
      agents: [translatorToEnglish, processor]
    });

    const orchestrator = new MultiAgentOrchestrator();
    orchestrator.addAgent(chainAgent);

    // Function to handle user input
    async function handleMultilingualInput(input: string, sourceLanguage: string) {
      translatorToEnglish.setSourceLanguage(sourceLanguage);

      const response = await orchestrator.routeRequest(
        input,
        'user123',
        'session456'
      );

      console.log('Response:', response);
    }

    // Usage
    handleMultilingualInput("Hola, ¿cómo estás?", "Spanish");
    ```
  </TabItem>
  <TabItem label="Python" icon="seti:python">
    ```python
    from multi_agent_orchestrator.orchestrator import MultiAgentOrchestrator
    from multi_agent_orchestrator.agents import ChainAgent, BedrockTranslatorAgent, BedrockLLMAgent
    from multi_agent_orchestrator.agents import ChainAgentOptions, BedrockTranslatorAgentOptions, BedrockLLMAgentOptions

    # Create translator agents
    translator_to_english = BedrockTranslatorAgent(BedrockTranslatorAgentOptions(
        name='TranslatorToEnglish',
        description='Translates input to English',
        target_language='English'
    ))

    # Create a processing agent (e.g., a BedrockLLMAgent)
    processor = BedrockLLMAgent(BedrockLLMAgentOptions(
        name='EnglishProcessor',
        description='Processes text in English'
    ))

    # Create a ChainAgent
    chain_agent = ChainAgent(ChainAgentOptions(
        name='TranslateProcessTranslate',
        description='Translates, processes, and translates back',
        agents=[translator_to_english, processor]
    ))

    orchestrator = MultiAgentOrchestrator()
    orchestrator.add_agent(chain_agent)

    # Function to handle user input
    async def handle_multilingual_input(input_text: str, source_language: str):
        translator_to_english.set_source_language(source_language)

        response = await orchestrator.route_request(
            input_text,
            'user123',
            'session456'
        )

        print('Response:', response)

    # Usage
    import asyncio

    asyncio.run(handle_multilingual_input("Hola, ¿cómo estás?", "Spanish"))
    ```
  </TabItem>
</Tabs>

In this example:
1. The first translator agent converts the input to English.
2. The processor agent (e.g., a `BedrockLLMAgent`) processes the English text.

This setup allows for seamless multilingual processing, where the core logic can be implemented in English while supporting input and output in various languages.

---

By leveraging the `BedrockTranslatorAgent`, you can create sophisticated multilingual applications and workflows, enabling seamless communication and processing across language barriers in your Multi-Agent Orchestrator system.