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<header>
    <h1>AbhiModels API Documentation</h1>
    <nav>
        <a href="#overview">Overview</a>
        <a href="#text-to-image">Text to Image</a>
        <a href="#image-to-image">Image to Image</a>
        <a href="#inpainting">Inpainting</a>
        <a href="#fetch-image">Fetch Image</a>
    </nav>
</header>

<div class="container">
    <div class="content">
        <h2 id="overview">Realtime API Overview</h2>
        <p>
            The Realtime API provided by <strong>AbhiModels</strong> enables users to generate images quickly and efficiently using various endpoints.
            This API supports both text-based and image-based requests, allowing for flexible image generation tailored to specific needs.
        </p>
        <h3>Image Generation Capabilities</h3>
        <p>
            Images can be generated in seconds, with the ability to specify the number of images produced as well as their dimensions.
            The API currently supports the following image formats:
        </p>
        <ul>
            <li>PNG</li>
            <li>JPG</li>
        </ul>
        <h3>Available Endpoints</h3>
        <ol>
            <li><a href="#text-to-image">Text to Image Endpoint</a></li>
            <li><a href="#image-to-image">Image to Image Endpoint</a></li>
            <li><a href="#inpainting">Inpainting Endpoint</a></li>
            <li><a href="#fetch-image">Fetch Queued Images Endpoint</a></li>
        </ol>
        <h3>Playground</h3>
        <p>
            Users can experiment with available endpoints in the Playground section of <strong>AbhiModels</strong>,
            but registration is required to access this feature.
        </p>

        <hr>

        <h2 id="text-to-image">Text to Image API Documentation</h2>
        <h3>Overview</h3>
        <p>
            The Text to Image API allows users to generate images in real time based on provided text prompts.
            This endpoint is part of the <strong>AbhiModels</strong> API and facilitates the creation of images tailored to specific descriptions.
        </p>
        <h3>Request</h3>
        <p>To utilize the API, send a <code>POST</code> request to the following endpoint:</p>
        <pre><code>POST https://api.abhibhai.com/api/v6/realtime/text2img</code></pre>
        <h4>Body Attributes</h4>
        <p>The request body must include the following parameters:</p>
        <table>
            <thead>
                <tr>
                    <th>Parameter</th>
                    <th>Description</th>
                </tr>
            </thead>
            <tbody>
                <tr>
                    <td><code>key</code></td>
                    <td>Your API Key for request authorization. <a href="#api-key">View your API Key</a>.</td>
                </tr>
                <tr>
                    <td><code>prompt</code></td>
                    <td>A description of the desired image.</td>
                </tr>
                <tr>
                    <td><code>negative_prompt</code></td>
                    <td>Descriptions of elements to avoid in the image (e.g., NSFW content, poor quality).</td>
                </tr>
                <tr>
                    <td><code>width</code></td>
                    <td>Width of the generated image (e.g., 1024).</td>
                </tr>
                <tr>
                    <td><code>height</code></td>
                    <td>Height of the generated image (e.g., 1024).</td>
                </tr>
                <tr>
                    <td><code>samples</code></td>
                    <td>Number of images to return (maximum 4).</td>
                </tr>
                <tr>
                    <td><code>safety_checker</code></td>
                    <td>Ensures inappropriate content is replaced with a blank image (default: <code>true</code>).</td>
                </tr>
                <tr>
                    <td><code>seed</code></td>
                    <td>Used for reproducibility; use <code>null</code> for a random seed.</td>
                </tr>
                <tr>
                    <td><code>instant_response</code></td>
                    <td>Enables immediate response before processing completes (default: <code>false</code>).</td>
                </tr>
                <tr>
                    <td><code>base64</code></td>
                    <td>Returns response as a base64 string (default: <code>false</code>).</td>
                </tr>
                <tr>
                    <td><code>webhook</code></td>
                    <td>URL for receiving a POST call after image generation completes.</td>
                </tr>
                <tr>
                    <td><code>track_id</code></td>
                    <td>ID returned in the webhook response for tracking.</td>
                </tr>
                <tr>
                    <td><code>enhance_prompt</code></td>
                    <td>Enhances prompts for better results (options: <code>true</code>, <code>false</code>).</td>
                </tr>
                <tr>
                    <td><code>enhance_style</code></td>
                    <td>Specifies the style of the image from various available styles.</td>
                </tr>
            </tbody>
        </table>
        <h4>Example Request Body</h4>
        <pre><code class="language-json">{
  "key": "",
  "prompt": "ultra realistic close up portrait ((beautiful pale cyberpunk female with heavy black eyeliner))",
  "negative_prompt": "bad quality",
  "width": "512",
  "height": "512",
  "safety_checker": false,
  "seed": null,
  "samples": 1,
  "base64": false,
  "webhook": null,
  "track_id": null
}</code></pre>
        <h4>Example Code Snippets</h4>
        <h5>JavaScript</h5>
        <pre><code class="language-javascript">var myHeaders = new Headers();
myHeaders.append("Content-Type", "application/json");

var raw = JSON.stringify({
  "key": "",
  "prompt": "ultra realistic close up portrait ((beautiful pale cyberpunk female with heavy black eyeliner))",
  "negative_prompt": "bad quality",
  "width": "512",
  "height": "512",
  "safety_checker": false,
  "seed": null,
  "samples": 1,
  "base64": false,
  "webhook": null,
  "track_id": null
});

var requestOptions = {
  method: 'POST',
  headers: myHeaders,
  body: raw,
};

fetch("https://api.abhibhai.com/api/v6/realtime/text2img", requestOptions)
.then(response => response.text())
.then(result => console.log(result))
.catch(error => console.log('error', error));</code></pre>
        <h5>Python</h5>
        <pre><code class="language-python">import requests
import json

url = "https://api.abhibhai.com/api/v6/realtime/text2img"
payload = json.dumps({
    "key": "",
    "prompt": "ultra realistic close up portrait ((beautiful pale cyberpunk female with heavy black eyeliner))",
    "negative_prompt": "bad quality",
    "width": "512",
    "height": "512",
    "safety_checker": False,
    "seed": None,
    "samples": 1,
    "base64": False,
    "webhook": None,
    "track_id": None
})

headers = {
    'Content-Type': 'application/json'
}

response = requests.post(url, headers=headers, data=payload)
print(response.text)</code></pre>

        <h4>Response Format</h4>
        <p>A successful response includes:</p>
        <pre><code class="language-json">{
  "status": "success",
  "generationTime": 1.06,
  "id": 91753437,
  "output": [
    "&lt;image_url&gt;"
  ],
  ...
}</code></pre>
        <p>This document provides a comprehensive overview of using the Text to Image API, including necessary parameters, example requests, and expected responses.</p>

        <hr>

        <h2 id="image-to-image">Image to Image API Documentation</h2>
        <h3>Overview</h3>
        <p>
            The Image to Image API allows users to generate new images based on existing images.
            By providing an initial image URL along with descriptive prompts, users can create modified versions of the original image, enhancing creativity and customization.
        </p>
        <h3>Endpoint</h3>
        <p>To use the Image to Image API, send a <code>POST</code> request to the following endpoint:</p>
        <pre><code>POST https://api.abhibhai.com/api/v6/realtime/img2img</code></pre>
        <h3>Request Parameters</h3>
        <p>The request body must include the following parameters:</p>
        <table>
            <thead>
                <tr>
                    <th>Parameter</th>
                    <th>Description</th>
                </tr>
            </thead>
            <tbody>
                <tr>
                    <td><code>key</code></td>
                    <td>Your API Key used for request authorization.</td>
                </tr>
                <tr>
                    <td><code>prompt</code></td>
                    <td>Text prompt describing the desired modifications to the image.</td>
                </tr>
                <tr>
                    <td><code>negative_prompt</code></td>
                    <td>Items or features that should not be included in the generated image.</td>
                </tr>
                <tr>
                    <td><code>init_image</code></td>
                    <td>URL of the initial image from which to generate the new image.</td>
                </tr>
                <tr>
                    <td><code>width</code></td>
                    <td>Width of the generated image (maximum: 1024).</td>
                </tr>
                <tr>
                    <td><code>height</code></td>
                    <td>Height of the generated image (maximum: 1024).</td>
                </tr>
                <tr>
                    <td><code>samples</code></td>
                    <td>Number of images to return (maximum: 4).</td>
                </tr>
                <tr>
                    <td><code>safety_checker</code></td>
                    <td>A feature that replaces NSFW images with a blank image if detected (default: <code>false</code>).</td>
                </tr>
                <tr>
                    <td><code>base64</code></td>
                    <td>Return response as a base64 string (default: <code>false</code>).</td>
                </tr>
                <tr>
                    <td><code>strength</code></td>
                    <td>Determines how much influence the initial image has on the output; a value of 1.0 means full destruction of information in the initial image.</td>
                </tr>
                <tr>
                    <td><code>instant_response</code></td>
                    <td>If set to true, returns an instant response before processing is complete (default: <code>false</code>).</td>
                </tr>
                <tr>
                    <td><code>seed</code></td>
                    <td>Seed for reproducibility; using the same seed will yield the same output. Use <code>null</code> for a random seed.</td>
                </tr>
                <tr>
                    <td><code>enhance_prompt</code></td>
                    <td>Option to enhance prompts for better results (options: <code>true</code>/<code>false</code>).</td>
                </tr>
                <tr>
                    <td><code>enhance_style</code></td>
                    <td>Specifies the style of the generated image from various available styles (e.g., surrealism, watercolor).</td>
                </tr>
                <tr>
                    <td><code>webhook</code></td>
                    <td>Set a URL to receive a POST call once image generation is complete.</td>
                </tr>
                <tr>
                    <td><code>track_id</code></td>
                    <td>ID returned in the webhook response for tracking purposes.</td>
                </tr>
            </tbody>
        </table>
        <h4>Example Request Body</h4>
        <pre><code class="language-json">{
  "key": "",
  "prompt": "a cat sitting on a bench",
  "negative_prompt": "bad quality",
  "init_image": "https://raw.githubusercontent.com/CompVis/stable-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png",
  "width": "512",
  "height": "512",
  "samples": "1",
  "safety_checker": false,
  "strength": 0.7,
  "seed": null,
  "webhook": null,
  "track_id": null
}</code></pre>
        <h4>Example Code Snippets</h4>
        <h5>JavaScript</h5>
        <pre><code class="language-javascript">var myHeaders = new Headers();
myHeaders.append("Content-Type", "application/json");

var raw = JSON.stringify({
    "key": "",
    "prompt": "a cat sitting on a bench",
    "negative_prompt": "bad quality",
    "init_image": "https://raw.githubusercontent.com/CompVis/stable-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png",
    "width": "512",
    "height": "512",
    "samples": "1",
    "safety_checker": false,
    "strength": 0.7,
    "seed": null,
    "webhook": null,
    "track_id": null
});

var requestOptions = {
    method: 'POST',
    headers: myHeaders,
    body: raw,
};

fetch("https://api.abhibhai.com/api/v6/realtime/img2img", requestOptions)
.then(response => response.text())
.then(result => console.log(result))
.catch(error => console.log('error', error));</code></pre>
        <h5>Python</h5>
        <pre><code class="language-python">import requests
import json

url = "https://api.abhibhai.com/api/v6/realtime/img2img"
payload = json.dumps({
    "key": "",
    "prompt": "a cat sitting on a bench",
    "negative_prompt": "bad quality",
    "init_image": "https://raw.githubusercontent.com/CompVis/stable-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png",
    "width": "512",
    "height": "512",
    "samples": 1,
    "safety_checker": False,
    "strength": 0.7,
    "seed": None,
    "webhook": None,
    "track_id": None
})

headers = {
    'Content-Type': 'application/json'
}
response = requests.post(url, headers=headers, data=payload)
print(response.text)</code></pre>

        <h4>Response Format</h4>
        <p>A successful response will include:</p>
        <pre><code class="language-json">{
  "status": "success",
  "generationTime": 2.92,
  "id": 302455,
  "output": [
      "&lt;image_url&gt;"
  ],
  ...
}</code></pre>
        <p>This document provides a detailed overview of the Image to Image API, outlining its capabilities and usage for effective image generation based on existing images.</p>

        <hr>

        <h2 id="inpainting">Inpainting API Documentation</h2>
        <h3>Overview</h3>
        <p>
            The Inpainting API allows users to generate and modify images by utilizing an initial image and a corresponding mask.
            By providing these elements along with descriptive prompts, users can create tailored images that reflect specific modifications or enhancements.
        </p>
        <h3>Endpoint</h3>
        <p>To use the Inpainting API, send a <code>POST</code> request to the following endpoint:</p>
        <pre><code>POST https://api.abhibhai.com/api/v6/realtime/inpaint</code></pre>
        <h3>Request Parameters</h3>
        <p>The request body must include the following parameters:</p>
        <table>
            <thead>
                <tr>
                    <th>Parameter</th>
                    <th>Description</th>
                </tr>
            </thead>
            <tbody>
                <tr>
                    <td><code>key</code></td>
                    <td>Your API Key used for request authorization.</td>
                </tr>
                <tr>
                    <td><code>prompt</code></td>
                    <td>Text prompt describing the desired modifications to the image.</td>
                </tr>
                <tr>
                    <td><code>negative_prompt</code></td>
                    <td>Items or features that should not be included in the generated image.</td>
                </tr>
                <tr>
                    <td><code>init_image</code></td>
                    <td>URL of the initial image from which to generate the new image.</td>
                </tr>
                <tr>
                    <td><code>mask_image</code></td>
                    <td>URL of the mask image that specifies areas to be modified in the initial image.</td>
                </tr>
                <tr>
                    <td><code>width</code></td>
                    <td>Width of the generated image (maximum: 1024).</td>
                </tr>
                <tr>
                    <td><code>height</code></td>
                    <td>Height of the generated image (maximum: 1024).</td>
                </tr>
                <tr>
                    <td><code>samples</code></td>
                    <td>Number of images to return in response (maximum: 4).</td>
                </tr>
                <tr>
                    <td><code>safety_checker</code></td>
                    <td>A feature that replaces NSFW images with a blank image if detected (default: <code>false</code>).</td>
                </tr>
                <tr>
                    <td><code>strength</code></td>
                    <td>Determines how much influence the initial image has on the output; a value of 1.0 means full destruction of information in the initial image.</td>
                </tr>
                <tr>
                    <td><code>instant_response</code></td>
                    <td>If set to true, returns an instant response before processing is complete (default: <code>false</code>).</td>
                </tr>
                <tr>
                    <td><code>base64</code></td>
                    <td>Return response as a base64 string (default: <code>false</code>).</td>
                </tr>
                <tr>
                    <td><code>seed</code></td>
                    <td>Seed for reproducibility; using the same seed will yield the same output. Use <code>null</code> for a random seed.</td>
                </tr>
                <tr>
                    <td><code>enhance_prompt</code></td>
                    <td>Option to enhance prompts for better results (options: <code>true</code>/<code>false</code>).</td>
                </tr>
                <tr>
                    <td><code>enhance_style</code></td>
                    <td>Specifies the style of the generated image from various available styles.</td>
                </tr>
                <tr>
                    <td><code>webhook</code></td>
                    <td>Set a URL to receive a POST call once image generation is complete.</td>
                </tr>
                <tr>
                    <td><code>track_id</code></td>
                    <td>ID returned in the webhook response for tracking purposes.</td>
                </tr>
            </tbody>
        </table>
        <h4>Example Request Body</h4>
        <pre><code class="language-json">{
  "key": "",
  "prompt": "a cat sitting on a bench",
  "negative_prompt": "bad quality",
  "init_image": "https://raw.githubusercontent.com/CompVis/stable-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png",
  "mask_image": "https://raw.githubusercontent.com/CompVis/stable-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo_mask.png",
  "width": "512",
  "height": "512",
  "samples": 1,
  "safety_checker": false,
  "strength": 0.7,
  "base64": false,
  "seed": null,
  "webhook": null,
  "track_id": null
}</code></pre>
        <h4>Example Code Snippets</h4>
        <h5>JavaScript</h5>
        <pre><code class="language-javascript">var myHeaders = new Headers();
myHeaders.append("Content-Type", "application/json");

var raw = JSON.stringify({
    "key": "",
    "prompt": "a cat sitting on a bench",
    "negative_prompt": "bad quality",
    "init_image": "https://raw.githubusercontent.com/CompVis/stable-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png",
    "mask_image": "https://raw.githubusercontent.com/CompVis/stable-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo_mask.png",
    "width": "512",
    "height": "512",
    "samples": 1,
    "safety_checker": false,
    "strength": 0.7,
    "base64": false,
    "seed": null,
    "webhook": null,
    "track_id": null
});

var requestOptions = {
    method: 'POST',
    headers: myHeaders,
    body: raw,
};

fetch("https://api.abhibhai.com/api/v6/realtime/inpaint", requestOptions)
.then(response => response.text())
.then(result => console.log(result))
.catch(error => console.log('error', error));</code></pre>
        <h5>Python</h5>
        <pre><code class="language-python">import requests
import json

url = "https://api.abhibhai.com/api/v6/realtime/inpaint"
payload = json.dumps({
    "key": "",
    "prompt": "a cat sitting on a bench",
    "negative_prompt": "bad quality",
    "init_image": "https://raw.githubusercontent.com/CompVis/stable-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png",
    "mask_image": "https://raw.githubusercontent.com/CompVis/stable-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo_mask.png",
    "width": "512",
    "height": "512",
    "samples": 1,
    "safety_checker": False,
    "strength": 0.7,
    "base64": False,
    "seed": None,
    "webhook": None,
    "track_id": None
})

headers = {
    'Content-Type': 'application/json'
}

response = requests.post(url, headers=headers, data=payload)
print(response.text)</code></pre>

        <h4>Response Format</h4>
        <p>A successful response will include:</p>
        <pre><code class="language-json">{
  "status": "success",
  "generationTime": 1.9110066890716553,
  "id": 12384052,
  "output": [
      "&lt;image_url&gt;"
  ],
  ...
}</code></pre>
        <p>This document provides a detailed overview of the Inpainting API, outlining its capabilities and usage for effective image generation and modification based on an initial image and mask.</p>

        <hr>

        <h2 id="fetch-image">Fetch Image API Documentation</h2>
        <h3>Overview</h3>
        <p>
            The Fetch Image API allows users to retrieve images that have already been generated through the <strong>AbhiModels</strong> platform.
            By using the unique ID assigned to each generated image, users can easily access the output without needing to regenerate it.
        </p>
        <h3>Endpoint</h3>
        <p>To use the Fetch Image API, send a <code>POST</code> request to the following endpoint:</p>
        <pre><code>POST https://api.abhibhai.com/api/v6/realtime/fetchimage</code></pre>
        <h3>Request Parameters</h3>
        <p>The request body must include the following parameter:</p>
        <table>
            <thead>
                <tr>
                    <th>Parameter</th>
                    <th>Description</th>
                </tr>
            </thead>
            <tbody>
                <tr>
                    <td><code>key</code></td>
                    <td>Your API Key used for request authorization.</td>
                </tr>
                <tr>
                    <td><code>id</code></td>
                    <td>The unique ID of the generated image that you wish to retrieve.</td>
                </tr>
            </tbody>
        </table>
        <h4>Example Request Body</h4>
        <pre><code class="language-json">{
  "key": "",
  "id": "12345678"
}</code></pre>
        <h4>Example Code Snippets</h4>
        <h5>JavaScript</h5>
        <pre><code class="language-javascript">var myHeaders = new Headers();
myHeaders.append("Content-Type", "application/json");

var raw = JSON.stringify({
    "key": "",
    "id": "12345678"
});

var requestOptions = {
    method: 'POST',
    headers: myHeaders,
    body: raw,
};

fetch("https://api.abhibhai.com/api/v6/realtime/fetchimage", requestOptions)
.then(response => response.json())
.then(result => console.log(result))
.catch(error => console.log('error', error));</code></pre>
        <h5>Python</h5>
        <pre><code class="language-python">import requests
import json

url = "https://api.abhibhai.com/api/v6/realtime/fetchimage"
payload = json.dumps({
    "key": "",
    "id": "12345678"
})

headers = {
    'Content-Type': 'application/json'
}

response = requests.post(url, headers=headers, data=payload)
print(response.text)</code></pre>

        <h4>Response Format</h4>
        <p>A successful response will include:</p>
        <pre><code class="language-json">{
  "status": "success",
  "id": "12345678",
  "output": "&lt;image_url&gt;"
}</code></pre>
        <p>This document provides a detailed overview of the Fetch Image API, outlining its capabilities and usage for retrieving previously generated images efficiently.</p>

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