Update

app.py

@@ -1,26 +1,127 @@
 import gradio as gr
+import torch
 import requests
 import json
+# from diffusers import StableDiffusionLDM3DPipeline
+import gradio as gr
+import torch 
+from PIL import Image
+import base64
+from io import BytesIO
+from tempfile import NamedTemporaryFile
+from pathlib import Path
+
+from gradio_client import Client
 
-def text_gen(url, prompt):
-    headers = {'Content-Type': 'application/json'}
-    payload = {'inputs': prompt, 'parameters': {'max_new_tokens': 32}}
-    resp = requests.post(url, data=json.dumps(payload), headers=headers)
-    return resp.text
-
-URL = "198.175.88.247"
-myport = "80"
-g2url = f"http://{URL}:{myport}/generate"
-
-url_input = gr.Textbox(label="URL", value=g2url, visible=True)
-prompt_input = gr.Textbox(label="Prompt", value="Why is the sky purple?", visible=True)
-outputs = gr.Textbox(label="Generated Text")
-
-demo = gr.Interface(
-    fn=text_gen,
-    inputs=[url_input, prompt_input],
-    outputs=[outputs],
-    title="Text Generation Demo"
+theme = gr.themes.Base(
+    primary_hue=gr.themes.Color(
+        c100="#dbeafe", c200="#bfdbfe", c300="#93c5fd", c400="#60a5fa", c50="#eff6ff", c500="#0054ae", c600="#00377c", c700="#00377c", c800="#1e40af", c900="#1e3a8a", c950="#0a0c2b"),
+    secondary_hue=gr.themes.Color(
+        c100="#dbeafe", c200="#bfdbfe", c300="#93c5fd", c400="#60a5fa", c50="#eff6ff", c500="#0054ae", c600="#0054ae", c700="#0054ae", c800="#1e40af", c900="#1e3a8a", c950="#1d3660"),
+).set(
+    body_background_fill_dark='*primary_950',
+    body_text_color_dark='#FFFFFF',
+    body_text_color='#000000',
+    border_color_accent='*primary_700',
+    border_color_accent_dark='*neutral_800',
+    block_background_fill_dark='*primary_950',
+    block_border_width='2px',
+    block_border_width_dark='2px',
+    button_primary_background_fill_dark='*primary_500',
+    button_primary_border_color_dark='*primary_500'
 )
 
-demo.launch()
+css='''
+    @font-face {
+        font-family: IntelOne;
+        src: url("file/assets/intelone-bodytext-font-family-regular.ttf");
+    }
+'''
+
+html_title = '''
+<table>
+<tr style="height:150px">
+    <td style="border-bottom:0"><img src="file/assets/intel-labs.png" height="100" width="100"></td>
+    <td style="border-bottom:0; vertical-align:middle">
+    <p style="font-size:xx-large;font-family:IntelOne, Georgia, sans-serif;color: var(--body-text-color);">
+     Cognitive AI:
+     <br>
+     LDM3D: Latent Diffusion Model for 3D
+    </p>
+    </td>
+    <td style="border-bottom:0;"><img src="file/assets/gaudi.png" width="100" height="100"></td>
+    <td style="border-bottom:0;"><img src="file/assets/xeon.png" width="100" height="100"></td>
+</tr>
+</table>
+
+'''
+
+client = Client("http://198.175.88.247:17810/")
+
+def generate(
+    prompt: str,
+    negative_prompt: str,
+    guidance_scale: float = 5.0,
+    seed: int = 0,
+    randomize_seed: bool = True,
+):
+
+    result = client.predict(
+		prompt,	# str  in 'Prompt' Textbox component
+		negative_prompt,	# str  in 'Negative Prompt' Textbox component
+		guidance_scale,	# int | float (numeric value between 0 and 10) in 'Guidance Scale' Slider component
+		seed,	# int | float (numeric value between 0 and 18446744073709551615) in 'Seed' Slider component
+		randomize_seed,	# bool  in 'Randomize Seed' Checkbox component
+		False,	# bool  in 'Upscale' Checkbox component
+		fn_index=1
+    )
+
+    return result
+
+with gr.Blocks(theme=theme, css=css) as demo:
+    gr.HTML(value=html_title)
+    gr.Markdown(
+        """
+[Model card](https://huggingface.co/Intel/ldm3d-pano<br>)
+[Diffusers docs](https://huggingface.co/docs/diffusers/main/en/api/pipelines/stable_diffusion/ldm3d_diffusion)
+For better results, specify "360 view of" or "panoramic view of" in the prompt
+
+"""
+    )
+    with gr.Row():
+        with gr.Column(scale=1):
+            prompt = gr.Textbox(label="Prompt")
+            negative_prompt = gr.Textbox(label="Negative Prompt")
+            guidance_scale = gr.Slider(
+                label="Guidance Scale", minimum=0, maximum=10, step=0.1, value=5.0
+            )
+            randomize_seed = gr.Checkbox(label="Randomize Seed", value=True)
+            seed = gr.Slider(label="Seed", minimum=0,
+                             maximum=2**64 - 1, step=1)
+            generated_seed = gr.Number(label="Generated Seed")
+            markdown = gr.Markdown(label="Output Box")
+            with gr.Row():
+                new_btn = gr.Button("New Image")
+        with gr.Column(scale=2):
+            html = gr.HTML()
+            with gr.Row():
+                rgb = gr.Image(label="RGB Image", type="filepath")
+                depth = gr.Image(label="Depth Image", type="filepath")
+
+    gr.Examples(
+        examples=[
+            ["360 view of a large bedroom", "", 7.0, 42, False]],
+        inputs=[prompt, negative_prompt, guidance_scale, seed, randomize_seed],
+        outputs=[rgb, depth, generated_seed, html],
+        fn=generate,
+        cache_examples=False)
+
+    new_btn.click(
+        fn=generate,
+        inputs=[prompt, negative_prompt, guidance_scale, seed, randomize_seed],
+        outputs=[rgb, depth, generated_seed, html],
+    )
+  
+    demo.launch(
+        allowed_paths=["assets/", "static/"]
+    )

requirements.txt

@@ -1,7 +1,7 @@
-git+https://https://github.com/huggingface/optimum-habana.git@v1.11.1
-gradio==3.40.1
+gradio==4.36.1
+diffusers
 transformers
 accelerate
 Pillow
 numpy
-torch
+torch