AI-Edit-Ebene via OpenRouter (Gemini Image): Studio-Hintergrund, Retusche, Restaurierung + freier Prompt

- app/ai_edit.py: OpenRouter chat/completions (image in/out), Presets + Prompt, Retry - bot: AI-Preset-Buttons + Bildunterschrift = freier AI-Prompt; _process refaktoriert - Freistellen/Upscaling bleiben lokal (originaltreu); AI-Edit fuer generative Edits - httpx pin, config OPENROUTER_* Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01XNQ8ghPfzAfsyVYd6HgFb6
2026-07-23 10:46:38 +00:00
parent 7c23c3f4c7
commit cfe5d36c70
4 changed files with 232 additions and 53 deletions
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+"""Generative AI-Bildbearbeitung via OpenRouter (Gemini/GPT Image-Modelle).
+
+Stark bei kreativen Edits: Hintergrund tauschen, Retusche, Restauration,
+freie Prompts. NICHT geeignet fuer echtes Freistellen (kein Alpha-Kanal) oder
+pixeltreues Upscaling – dafuer die lokalen Funktionen in enhance.py nutzen.
+"""
+from __future__ import annotations
+
+import base64
+import io
+import time
+
+import httpx
+from PIL import Image, ImageOps
+
+from . import config
+from .enhance import Result
+
+# Vordefinierte Presets (Prompt-Bausteine)
+PRESETS: dict[str, str] = {
+    "studio": (
+        "Replace the background with a clean, professional photo-studio backdrop "
+        "(soft neutral gradient, subtle vignette). Keep the subject exactly the "
+        "same – same pose, face, clothing, colors. Photorealistic, high quality."
+    ),
+    "retouch": (
+        "Professionally retouch this photo: even out skin tones, remove blemishes "
+        "and sensor noise, balance exposure and color, gentle natural sharpening. "
+        "Preserve the person's identity and natural look. Photorealistic."
+    ),
+    "restore": (
+        "Restore this old or damaged photo: remove scratches, dust and creases, "
+        "fix fading and color casts, recover detail. Keep it faithful and natural, "
+        "do not add new elements. Photorealistic."
+    ),
+}
+
+PRESET_LABELS = {
+    "studio": "Studio-Hintergrund",
+    "retouch": "AI-Retusche",
+    "restore": "Foto-Restaurierung",
+}
+
+
+def _prep_data_uri(image_bytes: bytes) -> str:
+    pil = Image.open(io.BytesIO(image_bytes))
+    pil = ImageOps.exif_transpose(pil).convert("RGB")
+    w, h = pil.size
+    longest = max(w, h)
+    if longest > config.AI_EDIT_MAX_EDGE:
+        s = config.AI_EDIT_MAX_EDGE / longest
+        pil = pil.resize((int(w * s), int(h * s)), Image.LANCZOS)
+    buf = io.BytesIO()
+    pil.save(buf, format="JPEG", quality=92)
+    b64 = base64.b64encode(buf.getvalue()).decode()
+    return f"data:image/jpeg;base64,{b64}"
+
+
+def _extract_image(message: dict) -> bytes | None:
+    imgs = message.get("images") or []
+    for im in imgs:
+        url = (im.get("image_url") or {}).get("url") if isinstance(im, dict) else None
+        if url and url.startswith("data:"):
+            return base64.b64decode(url.split(",", 1)[1])
+    # Manche Modelle liefern Bildteile im content-Array
+    content = message.get("content")
+    if isinstance(content, list):
+        for part in content:
+            if isinstance(part, dict):
+                url = (part.get("image_url") or {}).get("url", "")
+                if url.startswith("data:"):
+                    return base64.b64decode(url.split(",", 1)[1])
+    return None
+
+
+def _call(instruction: str, data_uri: str) -> dict:
+    body = {
+        "model": config.OPENROUTER_MODEL,
+        "modalities": ["image", "text"],
+        "messages": [{
+            "role": "user",
+            "content": [
+                {"type": "text", "text": instruction},
+                {"type": "image_url", "image_url": {"url": data_uri}},
+            ],
+        }],
+    }
+    headers = {
+        "Authorization": f"Bearer {config.OPENROUTER_API_KEY}",
+        "Content-Type": "application/json",
+        "X-Title": "Klarbildbot",
+    }
+    with httpx.Client(timeout=config.OPENROUTER_TIMEOUT) as client:
+        r = client.post(f"{config.OPENROUTER_BASE}/chat/completions",
+                        json=body, headers=headers)
+        r.raise_for_status()
+        return r.json()
+
+
+def edit(image_bytes: bytes, instruction: str) -> Result:
+    """Fuehrt einen generativen Edit aus und gibt das Ergebnisbild zurueck."""
+    t0 = time.time()
+    data_uri = _prep_data_uri(image_bytes)
+
+    resp = _call(instruction, data_uri)
+    msg = resp["choices"][0]["message"]
+    out = _extract_image(msg)
+
+    if out is None:
+        # Ein Nachfassen: Modell explizit zur Bildausgabe zwingen
+        resp = _call(instruction + "\n\nOutput ONLY the edited image.", data_uri)
+        msg = resp["choices"][0]["message"]
+        out = _extract_image(msg)
+
+    if out is None:
+        text = (msg.get("content") or "")[:200] if isinstance(msg.get("content"), str) else ""
+        raise RuntimeError(
+            "Das AI-Modell hat kein Bild geliefert" + (f" (Antwort: {text})" if text else "")
+        )
+
+    pil = Image.open(io.BytesIO(out))
+    w, h = pil.size
+    fmt = "jpg" if out[:2] == b"\xff\xd8" else "png"
+    return Result(out, fmt, w, h, time.time() - t0,
+                  f"openrouter/{config.OPENROUTER_MODEL}")