return optimized image from read_resource tool - tweaks

src/basic_memory/mcp/tools/resource.py

@@ -12,14 +12,18 @@ from PIL import Image as PILImage
 
 def resize_image(img, max_size):
     """Resize image maintaining aspect ratio"""
+    original_dimensions = {"width": img.width, "height": img.height}
+    
     if img.width > max_size or img.height > max_size:
         ratio = min(max_size / img.width, max_size / img.height)
         new_size = (int(img.width * ratio), int(img.height * ratio))
-        logger.debug("Resizing image", original={
-            "width": img.width, 
-            "height": img.height
-        }, target=new_size)
+        logger.debug("Resizing image", 
+                    original=original_dimensions, 
+                    target=new_size,
+                    ratio=ratio)
         return img.resize(new_size, PILImage.Resampling.LANCZOS)
+    
+    logger.debug("No resize needed", dimensions=original_dimensions)
     return img
 
 def optimize_image(img, max_output_bytes=500000):  # 500KB limit
@@ -29,16 +33,22 @@ def optimize_image(img, max_output_bytes=500000):  # 500KB limit
                 mode=img.mode,
                 max_bytes=max_output_bytes)
     
-    # Convert to RGB if needed
-    if img.mode in ('RGBA', 'LA') or (img.mode == 'P' and 'transparency' in img.info):
-        img = img.convert('RGB')
-        logger.debug("Converted image to RGB")
+    # Start with higher quality for better color preservation
+    quality = 60
     
-    quality = 30
-    size = 400
+    # Make initial size relative to input dimensions
+    initial_size = min(800, max(img.width, img.height))
+    size = initial_size
+    
+    original_mode = img.mode
+    if img.mode in ('RGBA', 'LA') or (img.mode == 'P' and 'transparency' in img.info):
+        # Keep original mode info for logging
+        img = img.convert('RGB')
+        logger.debug("Converted color mode", 
+                    from_mode=original_mode,
+                    to_mode='RGB')
     
     while True:
-        # Try current settings
         buf = io.BytesIO()
         resized = resize_image(img, size)
         
@@ -49,23 +59,35 @@ def optimize_image(img, max_output_bytes=500000):  # 500KB limit
                     subsampling='4:2:0')
         
         output_size = buf.getbuffer().nbytes
-        logger.debug("Optimization attempt", quality=quality, size=size, output_bytes=output_size)
+        logger.debug("Optimization attempt", 
+                    quality=quality, 
+                    size=size, 
+                    output_bytes=output_size,
+                    target_bytes=max_output_bytes)
         
         if output_size < max_output_bytes:
+            compression_ratio = output_size / max_output_bytes
             logger.info("Image optimization complete", 
-                      final_size=output_size,
-                      quality=quality,
-                      dimensions={"width": resized.width, "height": resized.height})
+                       final_size=output_size,
+                       quality=quality,
+                       dimensions={"width": resized.width, "height": resized.height},
+                       compression_ratio=compression_ratio)
             return buf.getvalue()
             
-        # Try lower quality first
-        if quality > 10:
-            quality -= 10
-            logger.debug("Reducing quality", new_quality=quality)
-        # Then reduce size if quality is already minimum
-        elif size > 200:
-            size -= 50
-            logger.debug("Reducing size", new_size=size)
+        # More gradual quality reduction for better color preservation
+        if quality > 30:
+            quality_step = 5 if quality > 50 else 10
+            quality -= quality_step
+            logger.debug("Reducing quality", 
+                        new_quality=quality,
+                        step=quality_step)
+        # Smaller size reduction steps
+        elif size > 300:
+            size_step = 25 if size > 600 else 50
+            size -= size_step
+            logger.debug("Reducing size", 
+                        new_size=size,
+                        step=size_step)
         else:
             logger.warning("Reached minimum optimization parameters", 
                          final_size=output_size,