AI-generated image provenance metadata (EU AI Act deepfake disclosure)

## Context

Diffusers generates images that get saved and distributed. Under EU AI Act Article 50 (August 2, 2026), AI-generated images disclosed publicly must carry transparency metadata. Deepfake disclosure becomes mandatory.

Currently, when you run:

```python
pipe = StableDiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0")
image = pipe("a sunset over mountains").images[0]
image.save("output.png")
```

The saved PNG has no metadata indicating it's AI-generated. A recipient has no way to know its origin.

## The Gap

Photos from cameras carry EXIF (camera model, GPS, timestamp). AI-generated images carry nothing. There's no standard EXIF/XMP field for:

- `AIGenerated: True`
- `AIModel: stable-diffusion-xl-base-1.0`
- `AIPrompt: "a sunset over mountains"` (optional)
- `GeneratedAt: 2026-03-28T12:00:00Z`

## Possible Approach

Diffusers could optionally embed provenance into saved images:

```python
image.save("output.png",
pnginfo=PngInfo() # already supported
)
# Could include AI provenance in PNG tEXt chunks or EXIF
```

This could be:
1. **Opt-in flag** — `pipe(..., embed_provenance=True)`
2. **Default on, opt-out** — more aggressive but helps compliance
3. **Separate utility** — `diffusers.utils.embed_provenance(image, model_name=...)`

## Why Diffusers Specifically

- Diffusers is the most popular image generation library
- Images are the primary target of EU AI Act deepfake provisions
- Pillow (which diffusers uses) already supports custom EXIF/XMP writing
- C2PA exists but requires Certificate Authority infrastructure — a lightweight EXIF-based approach would have much broader adoption

## Existing Formats

- [C2PA](https://c2pa.org/) — media provenance with PKI (heavy)
- [AKF](https://akf.dev) — lightweight JSON provenance for 20+ formats including images
- Custom EXIF/XMP — simplest, most compatible

Not advocating for any specific format — the important thing is that diffusers outputs carry *some* provenance. What does the team think?

Beginnen Sie mit der im Issue gezeigten Pipeline-Ausgabe und dem Pfad Pillow's image.save/PngInfo; keine Repository-Datei oder kein Test ist genannt. Vergleichen Sie die vorgeschlagenen Opt-in-, Standard- und Utility-Ansätze mit C2PA und benutzerdefinierten Metadatenformaten. Für den Abschluss sind ein vereinbartes Provenienzformat und API-Verhalten sowie eine Abdeckung für gespeicherte PNG-Metadaten erforderlich.

Vom Indexierungsmodell aus dem Issue-Text verfasst.