Update app.py

app.py

@@ -103,10 +103,10 @@ def image_to_base64(image_path):
         return base64.b64encode(img_file.read()).decode()
     
 
-@st.cache_resource
-def load_model():
-    pipeline_ = AutoPipelineForInpainting.from_pretrained("kandinsky-community/kandinsky-2-2-decoder-inpaint", torch_dtype=torch.float16).to("cuda")
-    return pipeline_
+# @st.cache_resource
+# def load_model():
+#     pipeline_ = AutoPipelineForInpainting.from_pretrained("kandinsky-community/kandinsky-2-2-decoder-inpaint", torch_dtype=torch.float16).to("cuda")
+#     return pipeline_
 
 @st.cache_resource
 def prompt_improvment(pre_prompt):
@@ -140,15 +140,15 @@ def numpy_to_list(array):
 
 
 
-@st.cache_resource
-def llm_text_response():
-    llm = Ollama(model="llama3:latest",num_ctx=1000)
-    return llm.stream
+# @st.cache_resource
+# def llm_text_response():
+#     llm = Ollama(model="llama3:latest",num_ctx=1000)
+#     return llm.stream
 
-def model_single_out(prompt):
-    pipe=load_model()
-    image = pipe(prompt).images[0]
-    return image
+# def model_single_out(prompt):
+#     pipe=load_model()
+#     image = pipe(prompt).images[0]
+#     return image
 
 def model_out_put(init_image,mask_image,prompt,negative_prompt):
     API_URL = "https://8417-201-238-124-65.ngrok-free.app/api/llm-response"
@@ -170,16 +170,16 @@ def model_out_put(init_image,mask_image,prompt,negative_prompt):
     # output_image.show()
     return output_image
 
-def model_out_put(init_image, mask_image, prompt, negative_prompt):
-    # Run the inpainting pipeline
-    pipeline_ = load_model()
-    image = pipeline_(
-        prompt=prompt, 
-        negative_prompt=negative_prompt, 
-        image=init_image, 
-        mask_image=mask_image
-    ).images[0]
-    return image
+# def model_out_put(init_image, mask_image, prompt, negative_prompt):
+#     # Run the inpainting pipeline
+#     pipeline_ = load_model()
+#     image = pipeline_(
+#         prompt=prompt, 
+#         negative_prompt=negative_prompt, 
+#         image=init_image, 
+#         mask_image=mask_image
+#     ).images[0]
+#     return image
 
 @st.cache_resource
 def multimodel():