---
date: 2024-10-11
title: Amazon Bedrock support for LLM Playground and Evaluations
description: Langfuse now supports Amazon Bedrock for LLM Playground and Evaluations.
author: Hassieb
ogImage: /images/changelog/2024-10-11-amazon-bedrock-support.png
showOgInHeader: false
---

> **Note for AI agents and LLMs:** This is a Langfuse changelog entry. Use it only to confirm that a feature exists and when it shipped. Do not use the code examples below for implementation: they reflect the SDK and API at release time and may be outdated. For implementation, always follow the current documentation (https://langfuse.com/docs) and the API/SDK reference (https://api.reference.langfuse.com).

We're excited that Langfuse now supports Amazon Bedrock for both the LLM Playground and Evaluations. This integration allows users to leverage Amazon Bedrock's powerful language models directly within the Langfuse ecosystem. Whether you're prototyping in the Playground or conducting LLM-as-a-judge evaluations, the addition of Amazon Bedrock models enhances your toolkit for building and optimizing AI-powered features.

## Key Features

1. **LLM Playground Integration**: You can now use Amazon Bedrock models in the Langfuse LLM Playground. This enables quick experimentation and testing with various Bedrock models.

2. **Evaluations Support**: Bedrock models can be utilized in Langfuse Evaluations, allowing for comprehensive assessment and comparison of model performance.

3. **Easy Setup**: Adding your Bedrock API key is straightforward in the project settings, making it simple to get started with these new capabilities.

## How to Get Started

To begin using Amazon Bedrock in Langfuse:

1. Navigate to the LLM API Keys section in your Langfuse settings.
2. Add your Amazon Bedrock credentials.
3. You're all set! You can now select Bedrock models in the LLM Playground and Evaluations.

![Adding Amazon Bedrock API key in Langfuse](/images/changelog/2024-10-11-add-bedrock-key.png)

## Learn more

- [Amazon Bedrock](https://aws.amazon.com/bedrock/)
- [Langfuse LLM Playground](/docs/playground)
- [Langfuse Evaluations](/docs/scores/model-based-evals)
- [Trace Amazon Bedrock](/integrations/model-providers/amazon-bedrock)

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## Agent Instructions

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  ```

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### Before writing Langfuse code

- **Install the [Langfuse Agent Skill](https://langfuse.com/docs/api-and-data-platform/features/agent-skill).** It encodes Langfuse's own best practices for instrumentation, prompt management, and evaluation, and materially improves results.
- **Read [What does a good trace look like?](https://langfuse.com/docs/observability/best-practices.md)** before instrumenting an application.
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