> ## Documentation Index
> Fetch the complete documentation index at: https://docs.qualifire.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Prompt Management

> An introduction to the Qualifire Prompt Management

The Prompt Management is a powerful tool that allows you to create, edit, and manage your prompts.
It provides a user-friendly interface for managing your prompts, including creating, editing, and deleting prompts, as well as viewing the results of your prompts.

## Creating a Prompt

To create a new prompt, follow these steps:

<Steps>
  <Step title="Navigate to the Prompts page in the Qualifire platform.">
    Navigate to the Prompts page in the Qualifire platform.
  </Step>

  <Step title="Click on the &#x22;Create New Prompt&#x22; button.">
    Click on the "Create New Prompt" button.
  </Step>

  <Step title="Select the type of prompt you want to create (e.g., &#x22;Safety and Security&#x22; or &#x22;Content Analysis&#x22;).">
    Select the evaluation you want to create or use, and link to an experiment
    if you want to evaluate the prompt against it.
  </Step>

  <Step title="Configure the prompt settings, such as the severity level, the content to be checked, and the checks to be applied.">
    Configure the prompt settings, such as the severity level, the content to be
    checked, and the checks to be applied.
  </Step>

  <Step title="Save the prompt and start observing your content.">
    Save the prompt and start observing your content.
  </Step>

  <Step title="Use the prompt in your application">
    Once you have created a prompt, you can use it in your application. You can
    use the prompt to generate content, evaluate it against an evaluation, or
    create a new evaluation.

    <CodeGroup>
      ```javascript javascript theme={null}
      import OpenAI from "openai";

        const openai = new OpenAI({
            apiKey: process.env.OPENAI_API_KEY,
            baseURL: "https://proxy.qualifire.ai/api/providers/openai/",
            defaultHeaders: {
            "X-Qualifire-Api-Key": `${process.env.QUALIFIRE_API_KEY}`,
            },
        });

        const THEME = "cats";

        openai.chat.completions.create({
            model: "gpt-4o",
            messages: [
                {
                    role: "user",
                    content: `$JOKES|[theme=${THEME}]`,
                },
            ],
        });
      ```

      ```python python theme={null}
      from openai import OpenAI

      client = OpenAI(
          api_key=os.environ["OPENAI_API_KEY"],
          base_url="https://proxy.qualifire.ai/api/providers/openai/",
          default_headers={
              "X-Qualifire-Api-Key": f"{os.environ['QUALIFIRE_API_KEY']}",
          },
      )

      THEME = "cats"

      client.chat.completions.create(
          model="gpt-4o",
          messages=[
              {
                  "role": "user",
                  "content": f"$JOKES|[theme={THEME}]",
              },
          ],
      )

      ```
    </CodeGroup>
  </Step>
</Steps>

## Advanced Features

<AccordionGroup>
  <Accordion title="Revisions and Releases" icon="code-branch">
    You can create revisions of your prompts to track changes and improvements over time. Revisions allow you to compare different versions of your prompts and track the evolution of your content. You can also decide which version of your prompt to use in your application.
  </Accordion>

  <Accordion title="Managing Prompts" icon="list-check">
    Once you have created a prompt, you can manage it through the Prompts page. You can edit, duplicate, or delete prompts as needed.
  </Accordion>

  <Accordion title="Observability" icon="chart-line">
    Qualifire provides a detailed view of the prompt's application to your content. You can see the results of the prompt's checks, the severity level, and any issues or failed checks that were identified.
  </Accordion>
</AccordionGroup>

<Tip>
  Use revisions to A/B test different prompt versions. Create a revision, link it to an experiment, and compare results before promoting to production.
</Tip>