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
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"""Generative AI-Bildbearbeitung via OpenRouter (Gemini/GPT Image-Modelle).
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Stark bei kreativen Edits: Hintergrund tauschen, Retusche, Restauration,
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freie Prompts. NICHT geeignet fuer echtes Freistellen (kein Alpha-Kanal) oder
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pixeltreues Upscaling – dafuer die lokalen Funktionen in enhance.py nutzen.
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"""
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from __future__ import annotations
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import base64
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import io
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import time
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import httpx
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from PIL import Image, ImageOps
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from . import config
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from .enhance import Result
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# Vordefinierte Presets (Prompt-Bausteine)
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PRESETS: dict[str, str] = {
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"studio": (
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"Replace the background with a clean, professional photo-studio backdrop "
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"(soft neutral gradient, subtle vignette). Keep the subject exactly the "
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"same – same pose, face, clothing, colors. Photorealistic, high quality."
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),
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"retouch": (
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"Professionally retouch this photo: even out skin tones, remove blemishes "
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"and sensor noise, balance exposure and color, gentle natural sharpening. "
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"Preserve the person's identity and natural look. Photorealistic."
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),
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"restore": (
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"Restore this old or damaged photo: remove scratches, dust and creases, "
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"fix fading and color casts, recover detail. Keep it faithful and natural, "
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"do not add new elements. Photorealistic."
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),
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}
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PRESET_LABELS = {
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"studio": "Studio-Hintergrund",
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"retouch": "AI-Retusche",
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"restore": "Foto-Restaurierung",
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}
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def _prep_data_uri(image_bytes: bytes) -> str:
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pil = Image.open(io.BytesIO(image_bytes))
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pil = ImageOps.exif_transpose(pil).convert("RGB")
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w, h = pil.size
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longest = max(w, h)
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if longest > config.AI_EDIT_MAX_EDGE:
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s = config.AI_EDIT_MAX_EDGE / longest
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pil = pil.resize((int(w * s), int(h * s)), Image.LANCZOS)
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buf = io.BytesIO()
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pil.save(buf, format="JPEG", quality=92)
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b64 = base64.b64encode(buf.getvalue()).decode()
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return f"data:image/jpeg;base64,{b64}"
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def _extract_image(message: dict) -> bytes | None:
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imgs = message.get("images") or []
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for im in imgs:
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url = (im.get("image_url") or {}).get("url") if isinstance(im, dict) else None
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if url and url.startswith("data:"):
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return base64.b64decode(url.split(",", 1)[1])
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# Manche Modelle liefern Bildteile im content-Array
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content = message.get("content")
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if isinstance(content, list):
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for part in content:
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if isinstance(part, dict):
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url = (part.get("image_url") or {}).get("url", "")
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if url.startswith("data:"):
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return base64.b64decode(url.split(",", 1)[1])
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return None
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def _call(instruction: str, data_uri: str) -> dict:
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body = {
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"model": config.OPENROUTER_MODEL,
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"modalities": ["image", "text"],
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"messages": [{
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"role": "user",
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"content": [
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{"type": "text", "text": instruction},
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{"type": "image_url", "image_url": {"url": data_uri}},
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],
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}],
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}
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headers = {
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"Authorization": f"Bearer {config.OPENROUTER_API_KEY}",
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"Content-Type": "application/json",
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"X-Title": "Klarbildbot",
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}
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with httpx.Client(timeout=config.OPENROUTER_TIMEOUT) as client:
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r = client.post(f"{config.OPENROUTER_BASE}/chat/completions",
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json=body, headers=headers)
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r.raise_for_status()
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return r.json()
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def edit(image_bytes: bytes, instruction: str) -> Result:
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"""Fuehrt einen generativen Edit aus und gibt das Ergebnisbild zurueck."""
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t0 = time.time()
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data_uri = _prep_data_uri(image_bytes)
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resp = _call(instruction, data_uri)
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msg = resp["choices"][0]["message"]
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out = _extract_image(msg)
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if out is None:
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# Ein Nachfassen: Modell explizit zur Bildausgabe zwingen
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resp = _call(instruction + "\n\nOutput ONLY the edited image.", data_uri)
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msg = resp["choices"][0]["message"]
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out = _extract_image(msg)
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if out is None:
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text = (msg.get("content") or "")[:200] if isinstance(msg.get("content"), str) else ""
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raise RuntimeError(
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"Das AI-Modell hat kein Bild geliefert" + (f" (Antwort: {text})" if text else "")
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)
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pil = Image.open(io.BytesIO(out))
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w, h = pil.size
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fmt = "jpg" if out[:2] == b"\xff\xd8" else "png"
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return Result(out, fmt, w, h, time.time() - t0,
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f"openrouter/{config.OPENROUTER_MODEL}")
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+95
-53
@@ -23,7 +23,7 @@ from telegram.ext import (
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filters,
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)
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from . import config, enhance, picdrop
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from . import ai_edit, config, enhance, picdrop
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logging.basicConfig(
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format="%(asctime)s %(levelname)s %(name)s | %(message)s",
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@@ -63,13 +63,21 @@ async def cmd_start(update: Update, ctx: ContextTypes.DEFAULT_TYPE) -> None:
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uid = update.effective_user.id if update.effective_user else "?"
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if not _allowed(update):
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return await _deny(update)
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ai_block = ""
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if config.AI_EDIT_ENABLED:
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ai_block = (
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"• 🎨 *Studio-Hintergrund* / 🪄 *AI-Retusche* / 🖼 *Restaurierung*\n"
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"• 💬 *Eigener AI-Prompt*: Bild mit Bildunterschrift senden "
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"(z. B. 'Hintergrund zu Strand', 'mach es schwarz-weiß')\n"
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)
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await update.effective_message.reply_text(
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"👋 *Klarbildbot* – AI-Bildaufbereitung\n\n"
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"Schick mir ein Bild, dann kannst du wählen:\n"
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"• 🔍 *Klarbild ×2 / ×4* – AI-Upscaling + Schärfen\n"
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"• ✂️ *Freistellen* – Hintergrund per AI entfernen (PNG)\n"
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"• ✨ *Freistellen + Klarbild* – beides\n\n"
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"💡 Für beste Qualität das Bild als *Datei* senden "
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"• 🔍 *Klarbild ×2 / ×4* – Upscaling + Schärfen (lokal, originaltreu)\n"
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"• ✂️ *Freistellen* – Hintergrund entfernen, echtes transparentes PNG (lokal)\n"
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"• ✨ *Freistellen + Klarbild* – beides\n"
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+ ai_block +
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"\n💡 Für beste Qualität das Bild als *Datei* senden "
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"(Büroklammer → Datei), nicht als komprimiertes Foto.\n\n"
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f"Deine Telegram-ID: `{uid}`",
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parse_mode="Markdown",
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@@ -97,12 +105,81 @@ async def cmd_help(update: Update, ctx: ContextTypes.DEFAULT_TYPE) -> None:
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# Bild empfangen -> Aktionsmenue
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# ---------------------------------------------------------------------------
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def _menu() -> InlineKeyboardMarkup:
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return InlineKeyboardMarkup([
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rows = [
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[InlineKeyboardButton("🔍 Klarbild ×2", callback_data="up:2"),
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InlineKeyboardButton("🔍 Klarbild ×4", callback_data="up:4")],
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[InlineKeyboardButton("✂️ Freistellen", callback_data="cut:0")],
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[InlineKeyboardButton("✨ Freistellen + Klarbild ×2", callback_data="cutup:2")],
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])
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]
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if config.AI_EDIT_ENABLED:
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rows += [
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[InlineKeyboardButton("🎨 Studio-Hintergrund", callback_data="ai:studio"),
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InlineKeyboardButton("🪄 AI-Retusche", callback_data="ai:retouch")],
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[InlineKeyboardButton("🖼 Foto-Restaurierung", callback_data="ai:restore")],
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]
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return InlineKeyboardMarkup(rows)
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def _label(action: str, scale: int = 0, prompt: str = "") -> str:
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return {
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"up": f"Klarbild ×{scale}",
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"cut": "Freistellen",
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"cutup": f"Freistellen + Klarbild ×{scale}",
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"ai": ai_edit.PRESET_LABELS.get(prompt, prompt),
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"aiprompt": f"AI-Edit: {prompt[:40]}",
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}.get(action, action)
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def _do_job(action: str, scale: int, prompt: str, image_bytes: bytes) -> enhance.Result:
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if action == "up":
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return enhance.upscale(image_bytes, scale)
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if action == "cut":
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return enhance.cutout(image_bytes)
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if action == "cutup":
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return enhance.cutout_then_upscale(image_bytes, scale)
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if action == "ai":
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return ai_edit.edit(image_bytes, ai_edit.PRESETS[prompt])
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if action == "aiprompt":
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return ai_edit.edit(image_bytes, prompt)
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raise ValueError(action)
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async def _process(ctx: ContextTypes.DEFAULT_TYPE, chat_id: int, status,
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file_id: str, action: str, scale: int, prompt: str) -> None:
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"""Bild laden, Job im Executor ausfuehren, Ergebnis als Dokument senden.
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`status` ist eine Telegram-Message, deren Text als Fortschritt editiert wird."""
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label = _label(action, scale, prompt)
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await status.edit_text(f"⏳ {label} läuft … (kann bei großen Bildern dauern)")
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try:
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tg_file = await ctx.bot.get_file(file_id)
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image_bytes = bytes(await tg_file.download_as_bytearray())
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except Exception as exc:
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log.exception("Download fehlgeschlagen")
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return await status.edit_text(
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f"❌ Konnte das Bild nicht laden: {exc}\n"
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"(Telegram-Bots können Dateien bis 20 MB laden.)")
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await ctx.bot.send_chat_action(chat_id, ChatAction.UPLOAD_DOCUMENT)
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loop = asyncio.get_running_loop()
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try:
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result = await loop.run_in_executor(
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EXECUTOR, _do_job, action, scale, prompt, image_bytes)
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except Exception as exc:
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log.exception("Verarbeitung fehlgeschlagen")
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return await status.edit_text(f"❌ Fehler bei der Verarbeitung: {exc}")
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caption = (f"✅ {label}\n{result.width}×{result.height}px · {result.seconds:.1f}s"
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+ (f"\n{result.note}" if result.note else ""))
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try:
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await ctx.bot.send_document(
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chat_id=chat_id,
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document=InputFile(result.data, filename=f"klarbild.{result.fmt}"),
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caption=caption,
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)
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await status.edit_text(f"✅ Fertig: {label}")
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except Exception as exc:
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log.exception("Senden fehlgeschlagen")
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await status.edit_text(f"❌ Konnte Ergebnis nicht senden: {exc}")
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async def on_image(update: Update, ctx: ContextTypes.DEFAULT_TYPE) -> None:
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@@ -119,8 +196,16 @@ async def on_image(update: Update, ctx: ContextTypes.DEFAULT_TYPE) -> None:
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else:
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return await msg.reply_text("Bitte ein Bild senden.")
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# Bild mit Bildunterschrift + AI aktiv => Unterschrift als freier AI-Prompt
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caption = (msg.caption or "").strip()
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if caption and config.AI_EDIT_ENABLED:
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status = await msg.reply_text("🪄 AI-Edit vorbereiten …")
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return await _process(ctx, msg.chat_id, status, file_id, "aiprompt", 0, caption)
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PENDING[update.effective_user.id] = {"file_id": file_id, "source": source}
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hint = "" if source == "document" else "\n_(Tipp: als Datei senden = volle Auflösung)_"
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if config.AI_EDIT_ENABLED:
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hint += "\n💬 _Oder Bild mit Bildunterschrift senden = eigener AI-Prompt._"
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await msg.reply_text(
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"Was soll ich damit machen?" + hint,
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reply_markup=_menu(),
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@@ -145,54 +230,11 @@ async def on_action(update: Update, ctx: ContextTypes.DEFAULT_TYPE) -> None:
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action, _, arg = query.data.partition(":")
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scale = int(arg) if arg.isdigit() else 0
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labels = {"up": f"Klarbild ×{scale}", "cut": "Freistellen",
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"cutup": f"Freistellen + Klarbild ×{scale}"}
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await query.edit_message_text(f"⏳ {labels.get(action, action)} läuft … "
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"(kann bei großen Bildern etwas dauern)")
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# Original holen (volle Aufloesung)
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try:
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tg_file = await ctx.bot.get_file(pend["file_id"])
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image_bytes = bytes(await tg_file.download_as_bytearray())
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except Exception as exc:
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log.exception("Download fehlgeschlagen")
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return await query.edit_message_text(
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f"❌ Konnte das Bild nicht laden: {exc}\n"
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"(Telegram-Bots können Dateien bis 20 MB laden.)")
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await ctx.bot.send_chat_action(update.effective_chat.id, ChatAction.UPLOAD_DOCUMENT)
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loop = asyncio.get_running_loop()
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def work() -> enhance.Result:
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if action == "up":
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return enhance.upscale(image_bytes, scale)
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if action == "cut":
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return enhance.cutout(image_bytes)
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if action == "cutup":
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return enhance.cutout_then_upscale(image_bytes, scale)
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raise ValueError(action)
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prompt = arg if action == "ai" else "" # bei AI-Presets ist arg der Preset-Key
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try:
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result = await loop.run_in_executor(EXECUTOR, work)
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except Exception as exc:
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log.exception("Verarbeitung fehlgeschlagen")
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return await query.edit_message_text(f"❌ Fehler bei der Verarbeitung: {exc}")
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fname = f"klarbild.{result.fmt}"
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caption = (f"✅ {labels.get(action, action)}\n"
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f"{result.width}×{result.height}px · {result.seconds:.1f}s"
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+ (f"\n{result.note}" if result.note else ""))
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try:
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await ctx.bot.send_document(
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chat_id=update.effective_chat.id,
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document=InputFile(result.data, filename=fname),
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caption=caption,
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)
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await query.edit_message_text(f"✅ Fertig: {labels.get(action, action)}")
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except Exception as exc:
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log.exception("Senden fehlgeschlagen")
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await query.edit_message_text(f"❌ Konnte Ergebnis nicht senden: {exc}")
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await _process(ctx, update.effective_chat.id, query.message,
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pend["file_id"], action, scale, prompt)
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finally:
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PENDING.pop(uid, None)
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@@ -63,6 +63,17 @@ POST_SHARPEN: bool = _get_bool("POST_SHARPEN", True)
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# JPEG-Qualitaet fuer zurueckgesendete Fotos (Freistellen liefert immer PNG).
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JPEG_QUALITY: int = _get_int("JPEG_QUALITY", 95)
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# --- OpenRouter (generative AI-Edits: Hintergrund, Retusche, freier Prompt) --
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# Achtung: US-gehostet (Google/OpenAI via OpenRouter). Bewusst gesetzt.
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OPENROUTER_API_KEY: str = os.getenv("OPENROUTER_API_KEY", "").strip()
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OPENROUTER_BASE: str = os.getenv("OPENROUTER_BASE", "https://openrouter.ai/api/v1")
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OPENROUTER_MODEL: str = os.getenv("OPENROUTER_MODEL", "google/gemini-3.1-flash-image")
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OPENROUTER_TIMEOUT: int = _get_int("OPENROUTER_TIMEOUT", 120)
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# Laengste Kante, auf die Eingangsbilder vor dem Senden verkleinert werden
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# (Kosten/Tempo). Das Modell gibt ohnehin ~1024px-Ausgaben zurueck.
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AI_EDIT_MAX_EDGE: int = _get_int("AI_EDIT_MAX_EDGE", 1536)
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AI_EDIT_ENABLED: bool = bool(OPENROUTER_API_KEY)
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# --- Health-Server ----------------------------------------------------------
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HEALTH_PORT: int = _get_int("PORT", 8080)
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@@ -5,6 +5,7 @@ opencv-contrib-python-headless==4.10.0.84
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numpy==1.26.4
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pillow==10.4.0
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aiohttp==3.10.10
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httpx==0.27.2
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paramiko==3.5.0
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pymatting==1.1.12
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scipy==1.13.1
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