update

embodied_gen/utils/gpt_clients.py

@@ -185,9 +185,8 @@ if __name__ == "__main__":
             text_prompt="What is the content in each image?",
             image_base64=combine_images_to_base64(
                 [
-                    "outputs/text2image/demo_objects/bed/sample_0.jpg",
-                    "outputs/imageto3d/v2/cups/sample_69/URDF_sample_69/qa_renders/image_color/003.png",  # noqa
-                    "outputs/text2image/demo_objects/cardboard/sample_1.jpg",
+                    "apps/assets/example_image/sample_02.jpg",
+                    "apps/assets/example_image/sample_03.jpg",
                 ]
             ),  # input raw image_path if only one image
         )
@@ -196,10 +195,8 @@ if __name__ == "__main__":
         response = GPT_CLIENT.query(
             text_prompt="What is the content in the images?",
             image_base64=[
-                Image.open("outputs/text2image/demo_objects/bed/sample_0.jpg"),
-                Image.open(
-                    "outputs/imageto3d/v2/cups/sample_69/URDF_sample_69/qa_renders/image_color/003.png"  # noqa
-                ),
+                Image.open("apps/assets/example_image/sample_02.jpg"),
+                Image.open("apps/assets/example_image/sample_03.jpg"),
             ],
         )
         print(response)

embodied_gen/utils/gpt_config.yaml

@@ -9,6 +9,6 @@ gpt-4o:
 
 qwen2.5-vl:
   endpoint: https://openrouter.ai/api/v1
-  api_key: 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
+  api_key: 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
   api_version: null
   model_name: qwen/qwen2.5-vl-72b-instruct:free

embodied_gen/validators/urdf_convertor.py

@@ -139,9 +139,7 @@ class URDFGenerator(object):
 
     def parse_response(self, response: str) -> dict[str, any]:
         lines = response.split("\n")
-        print("1", lines)
         lines = [line.strip() for line in lines if line]
-        print("2", lines)
         category = lines[0].split(": ")[1]
         description = lines[1].split(": ")[1]
         min_height, max_height = map(