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import gradio as gr | |
from huggingface_hub import InferenceClient | |
client = InferenceClient( | |
"meta-llama/Llama-3.2-1B-Instruct" #"HuggingFaceH4/zephyr-7b-beta" | |
) | |
# Background effect from CodePen | |
background_html = """ | |
<p class="codepen" data-height="300" data-theme-id="dark" data-default-tab="html,result" data-slug-hash="LYwLqVv" data-pen-title="WebGL Eye Pattern" data-user="bxck75" style="height: 300px; box-sizing: border-box; display: flex; align-items: center; justify-content: center; border: 2px solid; margin: 1em 0; padding: 1em;"> | |
<span>See the Pen <a href="https://codepen.io/bxck75/pen/LYwLqVv"> | |
WebGL Eye Pattern</a> by boudewijn (<a href="https://codepen.io/bxck75">@bxck75</a>) | |
on <a href="https://codepen.io">CodePen</a>.</span> | |
</p> | |
<script async src="https://cpwebassets.codepen.io/assets/embed/ei.js"></script> | |
""" | |
title_html=""" | |
<center> | |
<div id="title-container"> | |
<h1 id="title-text">ChatBot</h1> | |
</div> | |
</center> | |
""" | |
css = """ | |
.gradio-container { | |
background: url(https://huggingface.co/spaces/K00B404/FLUX.1-Dev-Serverless-darn-enhanced-prompt/resolve/main/edge.png); | |
background-size: 1800px 1000px; | |
background-repeat: no-repeat; | |
background-position: center; | |
background-attachment: fixed; | |
color:#111; | |
} | |
.dark\:bg-gray-950:is(.dark *) { | |
--tw-bg-opacity: 1; | |
background-color: rgb(157, 17, 142); | |
} | |
.gradio-container-4-41-0 .prose :last-child { | |
margin-top: 8px !important; | |
} | |
.gradio-container-4-41-0 .prose :last-child { | |
margin-bottom: -7px !important; | |
} | |
.dark { | |
--button-primary-background-fill: #09e60d70; | |
--button-primary-background-fill-hover: #00000070; | |
--background-fill-primary: #000; | |
--background-fill-secondary: #000; | |
} | |
.hide-container { | |
margin-top;-2px; | |
} | |
#app-container3 { | |
background-color: rgba(255, 255, 255, 0.001); /* Corrected to make semi-transparent */ | |
max-width: 600px; | |
margin-left: auto; | |
margin-right: auto; | |
margin-bottom: 10px; | |
border-radius: 125px; | |
box-shadow: 0 0 10px rgba(0,0,0,0.1); /* Adjusted shadow opacity */ | |
} | |
#app-container { | |
background-color: rgba(255, 255, 255, 0.001); /* Semi-transparent background */ | |
max-width: 600px; | |
margin: 0 auto; /* Center horizontally */ | |
padding-bottom: 10px; | |
border-radius: 25px; | |
box-shadow: 0 0 10px rgba(0, 0, 0, 0.1); /* Adjusted shadow opacity */ | |
} | |
.panel-container { | |
background-image: url('your-neon-border-image.png'); | |
background-size: 100% 100%; /* Adjust the size to cover the container */ | |
background-repeat: no-repeat; | |
background-position: center; | |
} | |
#title-container { | |
display: flex; | |
align-items: center | |
margin-bottom:10px; | |
justify-content: center; | |
} | |
#title-icon { | |
width: 32px; | |
height: auto; | |
margin-right: 10px; | |
} | |
#title-text { | |
font-size: 30px; | |
font-weight: bold; | |
color: #111; | |
} | |
:root { | |
--panel-size: 300px; | |
--border-width: 4px; | |
--glow-blur: 15px; | |
} | |
body { | |
background-color: #000; | |
display: flex; | |
justify-content: center; | |
align-items: center; | |
min-height: 100vh; | |
margin: 0; | |
} | |
.neon-panel { | |
width: var(--panel-size); | |
height: var(--panel-size); | |
background-color: #000; | |
position: relative; | |
border-radius: 20px; | |
overflow: hidden; | |
} | |
.neon-panel::before, | |
.neon-panel::after { | |
content: ''; | |
position: absolute; | |
left: -2px; | |
top: -2px; | |
background: linear-gradient( | |
124deg, | |
#ff2400, #e81d1d, #e8b71d, #e3e81d, #1de840, | |
#1ddde8, #2b1de8, #dd00f3, #dd00f3 | |
); | |
background-size: 300% 300%; | |
width: calc(100% + 4px); | |
height: calc(100% + 4px); | |
z-index: -1; | |
animation: moveGradient 10s ease infinite; | |
} | |
.neon-panel::after { | |
filter: blur(var(--glow-blur)); | |
} | |
.neon-panel-content { | |
position: absolute; | |
top: var(--border-width); | |
left: var(--border-width); | |
right: var(--border-width); | |
bottom: var(--border-width); | |
background-color: #000; | |
border-radius: 16px; | |
z-index: 1; | |
} | |
@keyframes moveGradient { | |
0% { background-position: 0% 50%; } | |
50% { background-position: 100% 50%; } | |
100% { background-position: 0% 50%; } | |
} | |
@media (max-width: 768px) { | |
:root { | |
--panel-size: 250px; | |
--glow-blur: 10px; | |
} | |
} | |
@media (prefers-reduced-motion: reduce) { | |
.neon-panel::before, | |
.neon-panel::after { | |
animation: none; | |
} | |
} | |
""" | |
def respond( | |
message, | |
history: list[tuple[str, str]], | |
system_message, | |
max_tokens, | |
temperature, | |
top_p, | |
): | |
messages = [{"role": "system", "content": system_message}] | |
for val in history: | |
if val[0]: | |
messages.append({"role": "user", "content": val[0]}) | |
if val[1]: | |
messages.append({"role": "assistant", "content": val[1]}) | |
messages.append({"role": "user", "content": message}) | |
response = "" | |
for message in client.chat_completion( | |
messages, | |
max_tokens=max_tokens, | |
stream=True, | |
temperature=temperature, | |
top_p=top_p, | |
): | |
token = message.choices[0].delta.content | |
response += token | |
yield response | |
with gr.Blocks(css=css) as demo: | |
gr.HTML(title_html) # Insert the background effect | |
gr.ChatInterface( | |
respond, | |
additional_inputs=[ | |
gr.Textbox(value="You are a friendly Chatbot.", label="System message"), | |
gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"), | |
gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"), | |
gr.Slider( | |
minimum=0.1, | |
maximum=1.0, | |
value=0.95, | |
step=0.05, | |
label="Top-p (nucleus sampling)", | |
), | |
], | |
) | |
if __name__ == "__main__": | |
demo.launch() | |