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

# Generate or edit an image with FLUX.1 Kontext

💡 Note that this API is async and will return the **request\_id** instead of the image. Call the [get\_result](/api-reference/get-generated-image-from-flux-kontex) API to obtain the generated image.

<Tabs>
  <Tab title="FLUX.1 Kontext Pro">
    FLUX Kontext Pro is a specialized model for generating contextually-aware images from text descriptions. Designed for professional use cases requiring high-quality, consistent image generation.

    Use our [Playground](https://app.fireworks.ai/playground?model=accounts/fireworks/models/flux-kontext-pro) to quickly try it out in your browser.
  </Tab>

  <Tab title="FLUX.1 Kontext Max">
    FLUX Kontext Max is the most advanced model in the Kontext series, offering maximum quality and context understanding. Ideal for enterprise applications requiring the highest level of image generation performance.

    Use our [Playground](https://app.fireworks.ai/playground?model=accounts/fireworks/models/flux-kontext-max) to quickly try it out in your browser.
  </Tab>
</Tabs>

## Path

<ParamField path="model" type="string" required initialValue="flux-kontext-pro" placeholder="flux-kontext-pro">
  The model to use for image generation. Use **flux-kontext-pro** or  **flux-kontext-max** as the model name in the API.
</ParamField>

## Headers

<ParamField header="Content-Type" type="string" initialValue="application/json" placeholder="application/json">
  The media type of the request body.
</ParamField>

<ParamField header="Authorization" type="string" required>
  Your Fireworks API key.
</ParamField>

## Request Body

<ParamField body="prompt" type="string" required initialValue="A photo of a cat" placeholder="A photo of a cat">
  Prompt to use for the image generation process.
</ParamField>

<ParamField body="input_image" type="string | null" optional>
  Base64 encoded image or URL to use with Kontext.
</ParamField>

<ParamField body="seed" type="integer | null" optional initialValue="42" placeholder="42">
  Optional seed for reproducibility.
</ParamField>

<ParamField body="aspect_ratio" type="string | null" optional>
  Aspect ratio of the image between 21:9 and 9:21.
</ParamField>

<ParamField body="output_format" type="string" optional initialValue="png" placeholder="png">
  Output format for the generated image. Can be 'jpeg' or 'png'.

  **Options:** `jpeg`, `png`
</ParamField>

<ParamField body="webhook_url" type="string | null" optional>
  URL to receive webhook notifications.

  **Length:** 1-2083 characters
</ParamField>

<ParamField body="webhook_secret" type="string | null" optional>
  Optional secret for webhook signature verification.
</ParamField>

<ParamField body="prompt_upsampling" type="boolean" optional initialValue="false" placeholder="false">
  Whether to perform upsampling on the prompt. If active, automatically modifies the prompt for more creative generation.
</ParamField>

<ParamField body="safety_tolerance" type="integer" optional initialValue="2" placeholder="2">
  Tolerance level for input and output moderation. Between 0 and 6, 0 being most strict, 6 being least strict. Limit of 2 for Image to Image.

  **Range:** 0-6
</ParamField>

<RequestExample>
  ```python Python theme={null}
  import requests

  url = "https://api.fireworks.ai/inference/v1/workflows/accounts/fireworks/models/{model}"
  headers = {
      "Content-Type": "application/json",
      "Authorization": "Bearer $API_KEY",
  }
  data = {
      "prompt": "A beautiful sunset over the ocean",
      "input_image": "<string>",
      "seed": 42,
      "aspect_ratio": "<string>",
      "output_format": "jpeg",
      "webhook_url": "<string>",
      "webhook_secret": "<string>",
      "prompt_upsampling": False,
      "safety_tolerance": 2
  }

  response = requests.post(url, headers=headers, json=data)
  ```

  ```typescript TypeScript theme={null}
  import fs from "fs";
  import fetch from "node-fetch";

  (async () => {
      const response = await fetch("https://api.fireworks.ai/inference/v1/workflows/accounts/fireworks/models/{model}", {
        method: "POST",
        headers: {
          "Content-Type": "application/json",
          "Authorization": "Bearer $API_KEY"
        },
        body: JSON.stringify({
          prompt: "A beautiful sunset over the ocean"
        }),
      });
  })().catch(console.error);
  ```

  ```shell curl theme={null}
  curl --request POST \
  -S --fail-with-body \
  --url https://api.fireworks.ai/inference/v1/workflows/accounts/fireworks/models/{model} \
  -H 'Content-Type: application/json' \
  -H "Authorization: Bearer $API_KEY" \
  --data '
  {
    "prompt": "A beautiful sunset over the ocean"
  }'
  ```
</RequestExample>

## Response

<Tabs>
  <Tab title="200">
    Successful Response

    <ParamField body="request_id" type="string">
      request id
    </ParamField>
  </Tab>

  <Tab title="400">
    Unsuccessful Response

    <ParamField body="error_message" type="string">
      error message
    </ParamField>
  </Tab>
</Tabs>