Prevent sprite generations from becoming texture maps

app.py

@@ -196,10 +196,23 @@ def interpret_style_hint(style_hint: str) -> StylePlan:
 
 def build_asset_prompt(role: str, prompt: str, style_hint: str) -> str:
     plan = interpret_style_hint(style_hint)
+    slug = slugify(role)
+    is_background = any(word in slug for word in ("background", "backdrop", "scene", "map", "level"))
+    if is_background:
+        asset_instruction = (
+            "Create one complete 2D game background scene, not a texture tile, not a material sample, "
+            "not a UV map. Full scene composition for a canvas game."
+        )
+    else:
+        asset_instruction = (
+            "Create one complete standalone 2D sprite of the whole subject, centered, full body or full vehicle, "
+            "single object, transparent or plain background, readable silhouette. Not a texture map, not a tiled "
+            "pattern, not a material swatch, not a UV unwrap, not a 3D model skin."
+        )
     return (
         f"{role} asset: {prompt}. Style interpretation: {plan.medium}; {plan.palette}; "
         f"{plan.texture}; {plan.lighting}; {plan.linework}; {plan.camera}. "
-        "Transparent background for characters and items unless the role is a background. "
+        f"{asset_instruction} "
         "Game asset, readable at small size, no text, no watermark."
     )
 
@@ -1045,8 +1058,14 @@ def free_diffusion_png(spec: AssetSpec, index: int, run_id: int) -> tuple[bytes
         width, height = diffusion_dimensions(spec)
         seed = abs(hash(f"{spec.role}|{spec.prompt}|{index}|{run_id}")) % 2147483647
         generator = torch.Generator(device="cpu").manual_seed(seed)
+        negative_prompt = (
+            "texture map, material texture, seamless texture, tiled pattern, uv map, uv unwrap, "
+            "skin texture, 3d model texture, normal map, roughness map, diffuse map, sprite sheet, "
+            "atlas, multiple objects, cropped subject, close-up surface, fabric swatch, text, watermark"
+        )
         image = FREE_DIFFUSION_PIPE(
             spec.prompt,
+            negative_prompt=negative_prompt,
             width=width,
             height=height,
             num_inference_steps=FREE_IMAGE_STEPS,