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@@ -69,41 +69,32 @@ AUTH_SERVICE_URL = os.getenv("AUTH_SERVICE_URL", "http://daarion-auth:7020")
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MATRIX_GATEWAY_URL = os.getenv("MATRIX_GATEWAY_URL", "http://daarion-matrix-gateway:7025")
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# Helper for image processing
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def process_image(image_bytes: bytes, target_size: tuple = (256, 256)) -> tuple[bytes, bytes]:
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def process_image(image_bytes: bytes, max_size: int = 1024, force_square: bool = False) -> tuple[bytes, bytes]:
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"""
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Process image:
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1. Convert to PNG
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2. Resize/Crop to target_size (default 256x256)
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3. Generate thumbnail 128x128
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1. Convert to PNG (any format accepted)
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2. Resize to fit within max_size (preserving aspect ratio)
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3. Optionally force square crop for avatars/logos
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4. Generate thumbnail 128x128
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Returns (processed_bytes, thumb_bytes)
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"""
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with Image.open(io.BytesIO(image_bytes)) as img:
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# Convert to RGBA/RGB
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if img.mode in ('P', 'CMYK'):
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if img.mode in ('P', 'CMYK', 'LA'):
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img = img.convert('RGBA')
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elif img.mode != 'RGBA':
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img = img.convert('RGB')
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# Resize/Crop to target_size
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img_ratio = img.width / img.height
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target_ratio = target_size[0] / target_size[1]
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if img_ratio > target_ratio:
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# Wider than target
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new_height = target_size[1]
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new_width = int(new_height * img_ratio)
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else:
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# Taller than target
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new_width = target_size[0]
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new_height = int(new_width / img_ratio)
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# Force square crop if needed (for avatars/logos)
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if force_square:
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min_dim = min(img.width, img.height)
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left = (img.width - min_dim) / 2
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top = (img.height - min_dim) / 2
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img = img.crop((left, top, left + min_dim, top + min_dim))
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img = img.resize((new_width, new_height), Image.Resampling.LANCZOS)
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# Center crop
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left = (new_width - target_size[0]) / 2
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top = (new_height - target_size[1]) / 2
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right = (new_width + target_size[0]) / 2
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bottom = (new_height + target_size[1]) / 2
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img = img.crop((left, top, right, bottom))
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# Resize to fit within max_size (preserve aspect ratio)
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if img.width > max_size or img.height > max_size:
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img.thumbnail((max_size, max_size), Image.Resampling.LANCZOS)
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# Save processed
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processed_io = io.BytesIO()
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@@ -318,25 +309,31 @@ async def update_agent_visibility_endpoint(
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@router.post("/assets/upload")
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async def upload_asset(
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file: UploadFile = File(...),
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type: str = Form(...) # microdao_logo, microdao_banner, room_logo, room_banner
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type: str = Form(...) # microdao_logo, microdao_banner, room_logo, room_banner, agent_avatar
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):
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"""Upload asset (logo/banner) with auto-processing"""
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"""Upload asset (logo/banner/avatar) with auto-processing. Accepts any image format."""
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try:
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# Validate type
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if type not in ['microdao_logo', 'microdao_banner', 'room_logo', 'room_banner']:
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raise HTTPException(status_code=400, detail="Invalid asset type")
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valid_types = ['microdao_logo', 'microdao_banner', 'room_logo', 'room_banner', 'agent_avatar']
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if type not in valid_types:
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raise HTTPException(status_code=400, detail=f"Invalid asset type. Valid: {valid_types}")
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# Validate file size (5MB limit) - done by reading content
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# Validate file size (20MB limit)
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content = await file.read()
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if len(content) > 5 * 1024 * 1024:
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raise HTTPException(status_code=400, detail="File too large (max 5MB)")
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if len(content) > 20 * 1024 * 1024:
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raise HTTPException(status_code=400, detail="File too large (max 20MB)")
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# Process image
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target_size = (256, 256)
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# Process image based on type
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# Logos and avatars: square, max 512px
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# Banners: max 1920px width, preserve aspect ratio
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if 'banner' in type:
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target_size = (1200, 400) # Standard banner size
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max_size = 1920
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force_square = False
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else:
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max_size = 512
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force_square = True # Square crop for logos/avatars
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processed_bytes, thumb_bytes = process_image(content, target_size=target_size)
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processed_bytes, thumb_bytes = process_image(content, max_size=max_size, force_square=force_square)
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# Save to disk
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filename = f"{uuid.uuid4()}.png"
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@@ -4078,9 +4075,10 @@ async def get_node_swapper_detail(node_id: str):
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models = [
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SwapperModel(
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name=m.get("name", "unknown"),
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loaded=m.get("loaded", False),
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# Swapper uses "status": "loaded" not "loaded": true
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loaded=m.get("status") == "loaded" or m.get("loaded", False),
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type=m.get("type"),
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vram_gb=m.get("vram_gb")
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vram_gb=m.get("size_gb") or m.get("vram_gb")
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)
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for m in models_data
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]
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Apple