Update app.py

app.py

@@ -168,80 +168,105 @@ def _extract_mask_array(mask_value: Union[np.ndarray, Dict[str, Any], None]) ->
 
 
 def edit_image(
-    api_key: str,
-    image_numpy: Optional[np.ndarray],
-    mask_dict: Optional[Dict[str, Any]],
-    prompt: str,
-    n: int,
-    size: str,
-    quality: str,
-    out_fmt: str,
-    compression: int,
-    transparent_bg: bool,
-):
-    if image_numpy is None:
-        raise gr.Error("Please upload an image.")
-    if not prompt:
-        raise gr.Error("Please enter an edit prompt.")
+        api_key: str,
+        image_numpy: Optional[np.ndarray],
+        mask_dict: Optional[Dict[str, Any]],
+        prompt: str,
+        n: int,
+        size: str,
+        quality: str,
+        out_fmt: str,
+        compression: int,
+        transparent_bg: bool,
+    ):
+        if image_numpy is None:
+            raise gr.Error("Please upload an image.")
+        if not prompt:
+            raise gr.Error("Please enter an edit prompt.")
+
+        img_bytes = _bytes_from_numpy(image_numpy)
+        mask_bytes: Optional[bytes] = None
+        mask_numpy = _extract_mask_array(mask_dict)
+
+        # (Mask handling code unchanged - Note: the current code doesn't actually
+        # convert mask_numpy to mask_bytes. If you implement this, you'll need
+        # to apply the tuple format to the mask as well.)
+        if mask_numpy is not None:
+            # Assuming you implement mask conversion similar to image:
+            # mask_bytes = _bytes_from_numpy(mask_numpy) # Example implementation needed here
+            pass # Placeholder - current code doesn't set mask_bytes
 
-    img_bytes = _bytes_from_numpy(image_numpy)
-    mask_bytes: Optional[bytes] = None
-    mask_numpy = _extract_mask_array(mask_dict)
+        try:
+            client = _client(api_key)
+            common_args = _common_kwargs(prompt, n, size, quality, out_fmt, compression, transparent_bg)
 
-    # (Mask handling code unchanged)
-    if mask_numpy is not None:
-        # existing mask-to-bytes logic...
-        pass
+            # --- FIX: Provide image data as a tuple ---
+            image_tuple = ("image.png", img_bytes, "image/png")
+            api_kwargs = {"image": image_tuple, **common_args}
+            # ------------------------------------------
+
+            if mask_bytes is not None:
+                # --- FIX: Provide mask data as a tuple if used ---
+                mask_tuple = ("mask.png", mask_bytes, "image/png")
+                api_kwargs["mask"] = mask_tuple
+                # -------------------------------------------------
+
+            resp = client.images.edit(**api_kwargs) # This line caused the error
+            imgs = _img_list(resp)
+            if out_fmt in {"jpeg", "webp"}:
+                imgs = [convert_to_format(img, out_fmt, compression) for img in imgs]
+            return imgs
+        except (openai.APIError, openai.OpenAIError) as e:
+            raise gr.Error(_format_openai_error(e))
+        except Exception as e:
+            print(f"Unexpected error during edit: {type(e).__name__}: {e}")
+            raise gr.Error("An unexpected application error occurred. Please check logs.")
 
-    try:
-        client = _client(api_key)
-        common_args = _common_kwargs(prompt, n, size, quality, out_fmt, compression, transparent_bg)
-        api_kwargs = {"image": img_bytes, **common_args}
-        if mask_bytes is not None:
-            api_kwargs["mask"] = mask_bytes
-        resp = client.images.edit(**api_kwargs)
-        imgs = _img_list(resp)
-        if out_fmt in {"jpeg", "webp"}:
-            imgs = [convert_to_format(img, out_fmt, compression) for img in imgs]
-        return imgs
-    except (openai.APIError, openai.OpenAIError) as e:
-        raise gr.Error(_format_openai_error(e))
-    except Exception as e:
-        print(f"Unexpected error during edit: {type(e).__name__}: {e}")
-        raise gr.Error("An unexpected application error occurred. Please check logs.")
 
 
 # ---------- Variations ---------- #
 def variation_image(
-    api_key: str,
-    image_numpy: Optional[np.ndarray],
-    n: int,
-    size: str,
-    quality: str,
-    out_fmt: str,
-    compression: int,
-    transparent_bg: bool,
-):
-    gr.Warning("Note: Image Variations are officially supported for DALL·E 2/3, not gpt-image-1. This may fail.")
-    if image_numpy is None:
-        raise gr.Error("Please upload an image.")
+        api_key: str,
+        image_numpy: Optional[np.ndarray],
+        n: int,
+        size: str,
+        quality: str,
+        out_fmt: str,
+        compression: int,
+        transparent_bg: bool, # Note: transparent_bg is passed but not used by variations API
+    ):
+        gr.Warning("Note: Image Variations are officially supported for DALL·E 2/3, not gpt-image-1. This may fail.")
+        if image_numpy is None:
+            raise gr.Error("Please upload an image.")
+
+        img_bytes = _bytes_from_numpy(image_numpy)
+        try:
+            client = _client(api_key)
+            var_args: Dict[str, Any] = {"model": MODEL, "n": n}
+            if size != "auto":
+                var_args["size"] = size
+
+            # --- FIX: Provide image data as a tuple ---
+            image_tuple = ("image.png", img_bytes, "image/png")
+            # ------------------------------------------
+
+            # Pass the tuple to the image parameter
+            resp = client.images.create_variation(image=image_tuple, **var_args) # This line would have the same error
+
+            imgs = _img_list(resp)
+            if out_fmt in {"jpeg", "webp"}:
+                imgs = [convert_to_format(img, out_fmt, compression) for img in imgs]
+            return imgs
+        except (openai.APIError, openai.OpenAIError) as e:
+            # Add specific check for variation incompatibility
+            err_msg = _format_openai_error(e)
+            if isinstance(e, openai.BadRequestError) and "model does not support variations" in err_msg.lower():
+                 raise gr.Error("As warned, the selected model (gpt-image-1) does not support the variations endpoint.")
+            raise gr.Error(err_msg)
+        except Exception as e:
+            print(f"Unexpected error during variation: {type(e).__name__}: {e}")
+            raise gr.Error("An unexpected application error occurred. Please check logs.")
 
-    img_bytes = _bytes_from_numpy(image_numpy)
-    try:
-        client = _client(api_key)
-        var_args: Dict[str, Any] = {"model": MODEL, "n": n}
-        if size != "auto":
-            var_args["size"] = size
-        resp = client.images.create_variation(image=img_bytes, **var_args)
-        imgs = _img_list(resp)
-        if out_fmt in {"jpeg", "webp"}:
-            imgs = [convert_to_format(img, out_fmt, compression) for img in imgs]
-        return imgs
-    except (openai.APIError, openai.OpenAIError) as e:
-        raise gr.Error(_format_openai_error(e))
-    except Exception as e:
-        print(f"Unexpected error during variation: {type(e).__name__}: {e}")
-        raise gr.Error("An unexpected application error occurred. Please check logs.")
 
 
 # ---------- UI ---------- #
@@ -294,3 +319,4 @@ def build_ui():
 if __name__ == "__main__":
     app = build_ui()
     app.launch(share=os.getenv("GRADIO_SHARE") == "true", debug=os.getenv("GRADIO_DEBUG") == "true")
+