Update app.py

app.py

@@ -10,9 +10,7 @@ from diffusers import DiffusionPipeline, StableDiffusionXLPipeline, EDMEulerSche
 from huggingface_hub import hf_hub_download, InferenceClient
 
 vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
-pipe = StableDiffusionXLPipeline.from_pretrained("SG161222/RealVisXL_V3.0", torch_dtype=torch.float16, vae=vae)
-pipe.load_lora_weights("KingNish/Better-Image-XL-Lora", weight_name="example-03.safetensors", adapter_name="lora")
-pipe.set_adapters("lora")
+pipe = StableDiffusionXLPipeline.from_pretrained("SG161222/RealVisXL_V4.0", torch_dtype=torch.float16, vae=vae)
 pipe.to("cuda")
 
 refiner = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0", vae=vae, torch_dtype=torch.float16, use_safetensors=True, variant="fp16")
@@ -53,7 +51,7 @@ pipe_edit.to("cuda")
 
 def promptifier(prompt):
     client1 = InferenceClient("mistralai/Mistral-7B-Instruct-v0.2")
-    system_instructions1 = "<s>[SYSTEM] Your task is to modify prompt by USER to more better prompt for Image Generation in Stable Diffusion XL, reply with prompt only, Your task is to reply with final prompt in SDXL image generation format only. [USER]"
+    system_instructions1 = "<s>[SYSTEM] Your task is to modify prompt by USER to more better prompt for Image Generation in Stable Diffusion XL, reply with prompt only, Your task is to reply with final prompt in SDXL image generation format only. Just reply with pure prompt.[USER]"
     formatted_prompt = f"{system_instructions1} {prompt} [FINAL_PROMPT]"
     stream = client1.text_generation(formatted_prompt, max_new_tokens=80, stream=True, details=True, return_full_text=False)
     return "".join([response.token.text for response in stream if response.token.text != "</s>"])
@@ -108,14 +106,13 @@ def king(type ,
             generator = generator, output_type="latent",
             ).images 
         else:
-            guidance_scale2=(guidance_scale/2) 
             if enhance_prompt:
                 print(f"BEFORE: {instruction} ")
                 instruction = promptifier(instruction)
                 print(f"AFTER: {instruction} ")
             image = pipe( prompt = instruction,
             negative_prompt=negative_prompt,
-            guidance_scale = guidance_scale2, 
+            guidance_scale = guidance_scale, 
             num_inference_steps = steps, 
             width = width, height = height,
             generator = generator, output_type="latent",
@@ -198,7 +195,7 @@ with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
         generate_button = gr.Button("Run", scale=0)
     with gr.Row():
         type = gr.Dropdown(["Image Generation","Image Editing"], label="Task", value="Image Generation",interactive=True)
-        enhance_prompt = gr.Checkbox(label="Enhance prompt", value=True, scale=0)
+        enhance_prompt = gr.Checkbox(label="Enhance prompt", value=False, scale=0)
         fast = gr.Checkbox(label="FAST Generation", value=False, scale=0)
         
     with gr.Row():