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import torch
import gradio as gr
from utils import *
from torch import nn
import lightning.pytorch as pl
from torch.nn import functional as F
device = 'cuda' if torch.cuda.is_available() else 'cpu'
HTML_TEMPLATE = """
<style>
#app-header {
text-align: center;
background: rgba(255, 255, 255, 0.3); /* Semi-transparent white */
padding: 20px;
border-radius: 10px;
box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
position: relative; /* To position the artifacts */
}
#app-header h1 {
color: #FF0000;
font-size: 2em;
margin-bottom: 10px;
}
.concept {
position: relative;
transition: transform 0.3s;
}
.concept:hover {
transform: scale(1.1);
}
.concept img {
width: 100px;
border-radius: 10px;
box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
}
.concept-description {
position: absolute;
bottom: -30px;
left: 50%;
transform: translateX(-50%);
background-color: #4CAF50;
color: white;
padding: 5px 10px;
border-radius: 5px;
opacity: 0;
transition: opacity 0.3s;
}
.concept:hover .concept-description {
opacity: 1;
}
/* Artifacts */
</style>
<div id="app-header">
<!-- Artifacts -->
<div class="artifact large"></div>
<div class="artifact large"></div>
<div class="artifact large"></div>
<div class="artifact large"></div>
<!-- Content -->
<h1>GPT NEXT WORD GENERATOR</h1>
<p>Generate dialogue for given some initial prompt for context.</p>
<p>Model: GPT, Dataset: arxiv + book + cc, Parameter Count: 160M</p>
"""
with gr.Blocks(theme=gr.themes.Glass(),css=".gradio-container {background: url('file=https://github.com/santule/ERA/assets/20509836/e78f2bb3-ddd8-4ce9-a941-3d3d7ef7a272')}") as interface:
gr.HTML(value=HTML_TEMPLATE, show_label=False)
gr.Markdown("")
gr.Markdown("")
gr.Markdown("")
gr.Markdown("")
gr.Markdown("")
gr.Markdown("")
gr.Markdown("")
gr.Markdown("")
gr.Markdown("")
gr.Markdown("")
gr.Markdown("")
with gr.Row():
input_text = gr.Textbox(
label="Input Text",
value="Enter your prompt here: This text will set the context for the AI's response."
)
temperature_dropdown = gr.Slider(0, 1, value=0.8, label="Temperature", info="Set the creativity level: Higher values produce more varied results, lower values generate more predictable text.")
top_k_dropdown = gr.Slider(200, 300, value=200, label="Top K", info="Control the randomness: Limits the AI to consider only the top K most likely next words.")
max_new_tokens = gr.Slider(10, 100, value=50, label="Max Tokens", info="Choose the length: This determines the maximum number of words the AI will generate.")
outputs = gr.Textbox(
label="Generated Dialogue"
)
inputs = [input_text, temperature_dropdown, top_k_dropdown, max_new_tokens]
with gr.Column():
button = gr.Button("Generate")
button.click(generate_dialogue, inputs=inputs, outputs=outputs)
# with gr.Row():
# gr.Examples(examples=examples, inputs=inputs, outputs=outputs, fn=generate_dialogue, cache_examples=True,)
interface.launch() |