add gradio app

app.py

@@ -0,0 +1,114 @@
+PATH = 'harpomaxx/deeplili' #stable diffusion 1.5
+from PIL import Image
+import torch
+from transformers import CLIPTextModel, CLIPTokenizer
+from diffusers import AutoencoderKL, UNet2DConditionModel, PNDMScheduler
+from diffusers import UniPCMultistepScheduler
+from diffusers import StableDiffusionPipeline
+from PIL import Image
+from tqdm.auto import tqdm
+import random
+import gradio as gr
+
+guidance_scale = 8.5  # Scale for classifier-free guidance
+
+
+pipe = StableDiffusionPipeline.from_pretrained(PATH,local_files_only=False ).to("cpu")
+guidance_scale = 8.5
+
+def generate_images(prompt, guidance_scale, n_samples, num_inference_steps):
+    seeds = [random.randint(1, 10000) for _ in range(n_samples)]
+    images = [] 
+    for seed in tqdm(seeds):
+        torch.manual_seed(seed)
+        image = pipe(prompt, num_inference_steps=num_inference_steps,guidance_scale=guidance_scale).images[0]   
+        images.append(image)
+    return images
+
+def gr_generate_images(prompt: str, num_images: int, num_inference: int):
+    prompt = prompt + "sks style"
+    images = generate_images(prompt, tokenizer, text_encoder, unet, vae, scheduler, guidance_scale, num_images, num_inference)
+    return images
+
+with gr.Blocks() as demo:
+    examples = [
+    [
+        'A black and white cute character on top of a hill',
+        1,
+	30
+    ],
+    [
+        'Bubbles and mountains in the sky',
+        1,
+	20
+    ],
+    [
+        'A tree with multiple eyes and a small flower muted colors',
+        1,
+	20
+    ],
+    [
+        "3d character on top of a hill",
+        1,
+	20
+    ],
+    [
+        "a poster of a large forest with black and white characters",
+        1,
+	20
+    ],
+    ]
+    gr.Markdown(
+    """
+    <img src="https://github.com/harpomaxx/DeepLili/raw/main/images/lilifiallo/660.png" width="150" height="150">
+
+    # #DeepLili v0.45b
+
+    ## Enter your prompt and generate a work of art in the style of Lili's Toy Art paintings.
+    """
+    )
+
+    with gr.Column(variant="panel"):
+        with gr.Row(variant="compact"):
+            text = gr.Textbox(
+                label="Enter your prompt",
+                show_label=False,
+                max_lines=2,
+                placeholder="a white and black drawing of  a cute character on top of a house with a little animal"
+            ).style(
+                container=False,
+            )
+          
+        with gr.Row(variant="compact"):
+            num_images_slider = gr.Slider(
+                minimum=1,
+                maximum=10,
+                step=1,
+                value=1,
+                label="Number of Images",
+            )
+   
+            num_inference_steps_slider = gr.Slider(
+                minimum=1,
+                maximum=25,
+                step=1,
+                value=20,
+                label="Number of Inference Steps",
+            )
+
+            btn = gr.Button("Generate image").style(full_width=False)
+      
+        gallery = gr.Gallery(
+            label="Generated images", show_label=False, elem_id="gallery"
+        ).style(columns=[5], rows=[1], object_fit="contain", height="250px", width="250px")
+
+    btn.click(gr_generate_images, [text, num_images_slider,num_inference_steps_slider], gallery)
+    gr.Examples(examples, inputs=[text])
+    gr.HTML(
+    """
+    <h6><a href="https://harpomaxx.github.io/"> harpomaxx </a></h6>
+    """
+    )
+
+if __name__ == "__main__":
+    demo.queue().launch(share=True)