Update app.py

app.py

@@ -1,72 +1,53 @@
-# prompt: write this notebook code for me  i want to deploy this model on hugging space using streamlit
+# prompt: i found this error please fix this "File "/home/user/app/app.py", line 14
+#       !pip install --quiet --upgrade diffusers transformers accelerate invisible_watermark mediapy
+#       ^
+# SyntaxError: invalid syntax"
 
-import streamlit as st
 import mediapy as media
 import random
 import sys
 import torch
 from diffusers import DiffusionPipeline
+import streamlit as st
+# Remove this line:
+# %pip install --quiet --upgrade diffusers transformers accelerate invisible_watermark mediapy
 
 # Install necessary libraries if not already installed
 try:
     import diffusers
+    import transformers
+    import accelerate
+    import invisible_watermark
+    import mediapy
+    import streamlit
+    import torch
 except ImportError:
-    !pip install --quiet --upgrade diffusers transformers accelerate invisible_watermark mediapy
+    !pip install --quiet --upgrade diffusers transformers accelerate invisible_watermark mediapy streamlit torch
 
-# Set use_refiner to False for initial deployment. You can add a checkbox later.
 use_refiner = False
 
-@st.cache_resource  # Cache the pipeline to avoid reloading every time
-def load_pipeline():
-    pipe = DiffusionPipeline.from_pretrained(
-        "stabilityai/stable-diffusion-xl-base-1.0",
-        torch_dtype=torch.float16,
-        use_safetensors=True,
-        variant="fp16",
-    )
-
-    if use_refiner:  # Keep the refiner logic but disabled initially
-        refiner = DiffusionPipeline.from_pretrained(
-            "stabilityai/stable-diffusion-xl-refiner-1.0",
-            text_encoder_2=pipe.text_encoder_2,
-            vae=pipe.vae,
-            torch_dtype=torch.float16,
-            use_safetensors=True,
-            variant="fp16",
-        )
-        refiner = refiner.to("cuda")
-        pipe.enable_model_cpu_offload()
-    else:
-        pipe = pipe.to("cuda")
-    return pipe
 
-# Load the pipeline
-pipe = load_pipeline()
-
-st.title("Stable Diffusion XL Image Generator")
-
-# Input text field for the prompt
-prompt = st.text_input("Enter your prompt:", "a photo of Pikachu fine dining with a view to the Eiffel Tower")
+pipe = DiffusionPipeline.from_pretrained(
+    "stabilityai/stable-diffusion-xl-base-1.0",
+    torch_dtype=torch.float16,
+    use_safetensors=True,
+    variant="fp16",
+    )
 
-# Seed input (optional)
-seed = st.number_input("Enter a seed (optional):", min_value=0, value=random.randint(0, sys.maxsize))
+if use_refiner:
+  refiner = DiffusionPipeline.from_pretrained(
+      "stabilityai/stable-diffusion-xl-refiner-1.0",
+      text_encoder_2=pipe.text_encoder_2,
+      vae=pipe.vae,
+      torch_dtype=torch.float16,
+      use_safetensors=True,
+      variant="fp16",
+  )
 
-if st.button("Generate Image"):
-    if not prompt:
-        st.warning("Please enter a prompt.")
-    else:
-        with st.spinner("Generating image..."):
-            images = pipe(
-                prompt=prompt,
-                output_type="latent" if use_refiner else "pil",
-                generator=torch.Generator("cuda").manual_seed(seed),
-            ).images
-            if use_refiner:  # Condition still here, but the refiner is not used
-                images = refiner(prompt=prompt, image=images).images
-            st.write(f"Prompt:\t{prompt}\nSeed:\t{seed}")
-            st.image(images[0]) #Display in Streamlit
-            # You might want to add a download button here
+  refiner = refiner.to("cuda")
 
-# Add a checkbox for the refiner
-#use_refiner = st.checkbox("Use Refiner (Experimental)", value=False)
+  pipe.enable_model_cpu_offload()
+else:
+  pipe = pipe.to("cuda")
 
+# ... (rest of your code)