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The Phota API provides four core capabilities. Each one can optionally leverage trained profiles to preserve the identity of specific people in the output.

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Edit — transform existing photos

The /edit endpoint takes one or more input images and a text prompt, then produces a transformed version. When you reference a profile, the person’s identity is preserved even through dramatic transformations.
Input photoBefore
Edited outputAfter
”Make [[abc123]] look at the camera and create a portrait shot.”
Input photoBefore
Edited outputAfter
”Combine [[abc123]] from the first image and [[def456]] from the second image in one group shot.”
Input photoBefore
Edited outputAfter
”Convert to a solo portrait of [[abc123]].”
When to use it: adding or removing people from group shots, adjusting camera angle or lighting, restyling scenes and backgrounds, creating seasonal or themed variations - anything where the edit needs to look like the real person. How profiles help: pass the user’s profile IDs in profile_ids so the API knows which identities to preserve. The API matches the people in the input photo to the provided profiles automatically. You can also use [[profile_id]] in the prompt to reference a specific person explicitly, e.g. "Make [[abc123]] smile wider". Example request body: 
{
  "prompt": "Make [[abc123]] smile wider",
  "images": ["https://example.com/photo.jpg"],
  "profile_ids": ["abc123"], # Optional, since profile_ids is mentioned in the prompt
  "base_model": "nb2", # Optional, defaults to "nb2" (Nano Banana 2)
  "aspect_ratio": "1:1",
  "resolution": "4K",
  "num_output_images": 2,
  "output_format": "jpg"
}
You can control the output aspect ratio (e.g. "9:16") and resolution (up to "4K") on every request. See Best practices.
Switch the underlying image model per request with base_model. See Base model selection for the supported values.

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Generate — create new images from scratch

The /generate endpoint creates images from a text prompt alone — no input image is needed. When you reference a profile, the generated person looks exactly like the actual person (or pet).
Generated imagePhota
”Artistic Noir Studio Headshot of [[abc123]], chest up. Introspective expression, gaze directed slightly off-camera, subtle three-quarter head tilt.”
Generated imagePhota
”Playful, photorealistic portrait of [[abc123]] and [[def456]], emerging through torn festive paper. Their hands emerge through the torn paper, holding the edges as if the subjects are emerging from the paper.”
Generated imagePhota
”Professional corporate headshot of [[abc123]]. Off-center to the right, smiling at camera, confident expression.”
When to use it: professional headshots, holiday cards and family portraits, profile pictures in any setting or style, couple and group photos where everyone doesn’t need to be in the same room — any scenario where you need a photo-realistic image of specific people. How profiles help: the generated person matches the trained profile’s appearance — face shape, features, hair, and skin tone are all preserved. Reference profiles directly in the prompt with [[profile_id]] syntax. Example request body: 
{
  "prompt": "A professional headshot of [[abc123]] in a modern office",
  "base_model": "nb2", # Optional, defaults to "nb2" (Nano Banana 2)
  "num_output_images": 4,
  "output_format": "jpg"
}
Generation is non-deterministic — set num_output_images to 2–4 and let the user pick the best result.
The /generate endpoint does not accept images or profile_ids. Reference profiles in the prompt with [[profile_id]] syntax instead. If you need to transform an existing photo, use /edit.

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Enhance — automatic quality improvement

The /enhance endpoint improves a photo automatically — no text prompt, no parameters to tune. Unlike most AI image services, Phota infers all enhancement parameters on its own: lighting, sharpness, color balance, and overall quality.
Original photoBefore
Enhanced photoAfter
Original photoBefore
Enhanced photoAfter
Original photoBefore
Enhanced photoAfter
When to use it: photos taken in poor lighting, blurry or noisy images, photos with compression artifacts — any photo where quality fell short. How profiles help: when profile IDs are provided, enhancement preserves and can improve the rendering of known faces in the photo. Example request body: 
{
  "image": "https://example.com/photo.jpg",
  "profile_ids": ["abc123"],
  "num_output_images": 2,
  "output_format": "jpg"
}

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Remix — restyle with a reference image

The /remix endpoint takes an input image (the content) and a reference image (the style), and produces your photo rendered in the reference’s look — lighting, palette, mood, and artistic treatment. No prompt needed, though an optional prompt can steer the result (second slide).
Input photoInput
+
Style referenceReference
=
Remixed outputOutput
No prompt — pure style transfer
Remixed output steered by a promptOutput
Prompt: “no sunglasses; let her wear an argentina jersey instead, same pose as in reference”
When to use it: applying a brand’s visual style to user photos, themed photo features (film looks, editorial styles, seasonal treatments), matching new shots to an existing campaign’s aesthetic. How profiles help: pass profile IDs in profile_ids and recognized people keep their real likeness through the restyle. Example request body: 
{
  "input_image": "https://example.com/photo.jpg",
  "reference_image": "https://example.com/reference.jpg",
  "profile_ids": ["abc123"],
  "num_output_images": 2,
  "output_format": "jpg",
  "response_mode": "urls"
}
See the Remix guide for the full walkthrough.

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Next steps

Profiles guide

Learn how to create and manage profiles for identity preservation.

Quickstart

Walk through the full workflow with code examples.

API reference

Explore the full endpoint documentation.