remove database saving or retrieving in prompt generator

damo/services/llm/vision.py

@@ -13,52 +13,52 @@ client = OpenAI(api_key=os.getenv('OPENAI_API_KEY'))
 
 def generate_prompt_from_image(image_url, prompt, clothing_type, image_id=None, temperature=0.6):
     material_obj = None
-    with Session(engine) as session:
-        if image_id:
-            material_obj = session.scalar(select(Material).where(Material.name.__eq__(image_id)))
-        if not material_obj:
-            fabric_analysis = client.chat.completions.create(
-                model="gpt-4-turbo",
-                response_format={"type": "json_object"},
-                messages=[
-                    {
-                        "role": "system",
-                        "content": [
-                            {"type": "text",
-                             "text": "As a professional fabric analyst, analyze the material in the picture and fill in "
-                                     "the parameters in the user-provided template. Parameters are indicated as "
-                                     "<example_parameter>. Ensure the material description, and texture are precise. "
-                                     "Maintain the integrity of the prompt template, returning the response as a JSON "
-                                     "object with each parameter's value as a string. Do not alter the template values. "
-                                     "Your tone should be highly detailed and professional with short and concise "
-                                     "phrases without making sentences. "
+    # with Session(engine) as session:
+        # if image_id:
+        #     material_obj = session.scalar(select(Material).where(Material.name.__eq__(image_id)))
+    if not material_obj:
+        fabric_analysis = client.chat.completions.create(
+            model="gpt-4-turbo",
+            response_format={"type": "json_object"},
+            messages=[
+                {
+                    "role": "system",
+                    "content": [
+                        {"type": "text",
+                         "text": "As a professional fabric analyst, analyze the material in the picture and fill in "
+                                 "the parameters in the user-provided template. Parameters are indicated as "
+                                 "<example_parameter>. Ensure the material description, and texture are precise. "
+                                 "Maintain the integrity of the prompt template, returning the response as a JSON "
+                                 "object with each parameter's value as a string. Do not alter the template values. "
+                                 "Your tone should be highly detailed and professional with short and concise "
+                                 "phrases without making sentences. "
 
-                             }
-                        ]
-                    },
-                    {
-                        "role": "user",
-                        "content": [
-                            {"type": "text",
-                             "text": prompt
+                         }
+                    ]
+                },
+                {
+                    "role": "user",
+                    "content": [
+                        {"type": "text",
+                         "text": prompt
 
-                             }
-                        ]
-                    },
-                    {
-                        "role": "user",
-                        "content": [
-                            {"type": "image_url", "image_url": {"url": image_url}},
-                            {"type": "text",
-                             "text": f"Clothing type is: {clothing_type}, and other clothing attributes are: {clothing_type.to_prompt()}"}
-                        ]
-                    }
-                ],
-                temperature=temperature
-            )
-            dalle_prompt = fabric_analysis.choices[0].message.content
-            print(dalle_prompt)
-            material_obj = json.loads(dalle_prompt)
+                         }
+                    ]
+                },
+                {
+                    "role": "user",
+                    "content": [
+                        {"type": "image_url", "image_url": {"url": image_url}},
+                        {"type": "text",
+                         "text": f"Clothing type is: {clothing_type}, and other clothing attributes are: {clothing_type.to_prompt()}"}
+                    ]
+                }
+            ],
+            temperature=temperature
+        )
+        dalle_prompt = fabric_analysis.choices[0].message.content
+        print(dalle_prompt)
+        material_obj = json.loads(dalle_prompt)
             # new_material = Material(**{
             #     "name": image_id,
             #     "texture": material_obj["fabric_texture"],
@@ -74,6 +74,6 @@ def generate_prompt_from_image(image_url, prompt, clothing_type, image_id=None,
             .replace("<other_clothing_attributes>", clothing_type.to_prompt()) \
             .replace("<cloth_type>", clothing_type.name)
         # .replace("<detailed_coloring_and_schema_description>", material_obj["color_and_scheme"]) \
-        session.commit()
-        session.close()
+        # session.commit()
+        # session.close()
         return prompt