# Debugging LLM Applications

> Helicone provides an efficient platform for identifying and rectifying errors in your LLM applications, offering insights into their occurrence.

# Identifying Errors

Helicone's request page allows you to filter results by status code, a unique identifier that corresponds to various states of web requests. This feature enables you to pinpoint errors, providing essential information about their timing and location.

<Frame>
  ![Filter web request results by status code on Helicone's request
  page.](/images/use-cases/status-filter.png)
</Frame>

We are currently developing dedicated error filters to further enhance your debugging experience. If you are interested in this feature, please support us by upvoting the feature request [here](https://www.helicone.ai/roadmap).

# Debugging Prompts with Playground

<Info>Currently, only ChatGPT is supported</Info>

Helicone's 'Playground' feature offers a platform for debugging your 'prompt'. This tool enables you to test your prompt and swiftly observe the model's output for minor adjustments within the Helicone environment. Here's a step-by-step guide on how to use it:

1. Open a request.

<Frame>
  ![View detailed logging details on Helicone's Requests
  page.](/images/use-cases/view-request.png)
</Frame>

2. Click on the 'Playground' button.

<Frame>
  ![Access the Playground feature for prompt debugging in
  Helicone](/images/use-cases/playground-button.png)
</Frame>

3. Input and execute your prompt to view the results.

<Frame>
  ![Use Helicone's Playground to test prompts in a sandbox
  environment](/images/use-cases/playground.png)
</Frame>

Please note, the Playground tool is a sandbox environment, so feel free to experiment with different prompts and settings to optimize results for your project.