Update tools/analyze.py

tools/analyze.py

@@ -6,36 +6,82 @@ def analyze_image(image_path: str):
     """
     Analyze an uploaded image.
 
-    Returns a dictionary that can be used by the Image Agent.
+    Returns:
+        {
+            "description": "...",
+            "objects": [],
+            "style": "...",
+            "lighting": "...",
+            "resolution": "...",
+            "filename": "...",
+            "format": "...",
+            "mode": "...",
+            "size_bytes": ...
+        }
     """
 
-    img = Image.open(image_path)
-
-    width, height = img.size
-
-    analysis = {
-        "filename": os.path.basename(image_path),
-        "format": img.format,
-        "mode": img.mode,
-        "width": width,
-        "height": height,
-        "resolution": f"{width} x {height}",
-
-        # Placeholder until Vision LLM is connected
-        "description": "Image uploaded successfully. Vision analysis not yet enabled.",
-
-        "objects": [],
-        "text": "",
-        "style": "",
-        "lighting": "",
-        "colors": [],
-        "suggestions": [
-            "Remove background",
-            "Enhance quality",
-            "Convert to anime",
-            "Generate variations",
-            "Extract text (OCR)"
-        ]
-    }
-
-    return analysis
+    if not image_path:
+        return {
+            "error": "No image path provided."
+        }
+
+    if not os.path.exists(image_path):
+        return {
+            "error": "Image file not found."
+        }
+
+    try:
+
+        img = Image.open(image_path)
+
+        width, height = img.size
+
+        image_format = img.format
+
+        image_mode = img.mode
+
+        file_size = os.path.getsize(image_path)
+
+        # -------------------------------------------------
+        # Placeholder description
+        # Replace this section with an LLM/Vision model later
+        # -------------------------------------------------
+
+        description = (
+            f"This image has a resolution of {width} × {height}. "
+            f"It is a {image_format} image in {image_mode} color mode. "
+            "A vision model can provide a detailed description of the scene."
+        )
+
+        objects = []
+
+        style = "Unknown"
+
+        lighting = "Unknown"
+
+        return {
+
+            "description": description,
+
+            "objects": objects,
+
+            "style": style,
+
+            "lighting": lighting,
+
+            "resolution": f"{width} x {height}",
+
+            "filename": os.path.basename(image_path),
+
+            "format": image_format,
+
+            "mode": image_mode,
+
+            "size_bytes": file_size
+        }
+
+    except Exception as e:
+
+        return {
+            "error": str(e)
+        }