app updated

app.py

@@ -3,64 +3,16 @@ import sys
 # sys.path.append("LaVi-Bridge/test")
 # from llama2_unet_diffusion_lens import call_diffusion_lens
 from diffusion_lens import get_images
-
+import gradio as gr
 import os
 import subprocess
 
-def prepare_images(images):
-    return images
-
-
-# def call_diffusion_lens(prompt):
-#     # os.chdir('LaVi-Bridge/test')
-#     command = f"python -u llama2_unet.py --ckpt_dir 'LaVi-Bridge/llama2_unet' --output_dir 'output' --llama2_dir 'meta-llama/Llama-2-7b-hf' --prompt '{prompt}'"
-#     subprocess.run(command, shell=True)
-#     return 'output'
-
-
 def get_prompt(prompt):
     print('prompt:', prompt)
     print('calling diffusion lens')
-
-    # parser.add_argument("--ckpt_dir", type=str, default="")
-    # parser.add_argument("--output_dir", type=str, default="")
-    # parser.add_argument("--llama2_dir", type=str, default="")
-    # parser.add_argument("--prompts_path", type=str, default="inputs/in.txt")
-    # parser.add_argument("--use_chat", action="store_true")
-    # parser.add_argument("--generate_text", action="store_true")
-    # parser.add_argument("--dont_use_lora", action="store_true")
-    # parser.add_argument("--is_gradio", action="store_true")
-
-    # args = {
-    #     'ckpt_dir': 'LaVi-Bridge/LaVi-Bridge/llama2_unet',
-    #     'output_dir': 'output',
-    #     'llama2_dir': 'meta-llama/Llama-2-7b-hf',
-    #     'prompt': prompt,
-    #     'use_chat': False,
-    #     'generate_text': False,
-    #     'dont_use_lora': False,
-    #     'is_gradio': True,
-    #     'prompts_path': None
-    # }
-    # images = call_diffusion_lens(args, prompt)
-    # print('done calling diffusion lens')
-    # print('number of images:', len(images))
-    # images = prepare_images(images)
-    # print('done preparing images')
     image = get_images(prompt, skip_layers=0)
     return image
 
-if __name__ == '__main__':
-    print('starting')
-    get_prompt("A photo of a cat")
-    print('done')
-
-
-# iface = gr.Interface(fn=get_prompt, inputs="text", outputs="image", title="Diffusion Lens")
-# iface.launch()
-
-import gradio as gr
-
 def display_images(images):
     # Prepare images for display
     return [gr.Image(image) for image in images]