Upload index.html with huggingface_hub
Browse files- index.html +374 -19
index.html
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| 1 |
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<html lang="en">
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| 2 |
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<head>
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| 3 |
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<meta charset="UTF-8">
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| 4 |
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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| 5 |
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<title>AI Chat Assistant - Gradio Lite</title>
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| 6 |
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<script type="module" crossorigin src="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.js"></script>
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| 7 |
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<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.css" />
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| 8 |
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<style>
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| 9 |
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* {
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| 10 |
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margin: 0;
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| 11 |
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padding: 0;
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| 12 |
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box-sizing: border-box;
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| 13 |
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}
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| 14 |
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| 15 |
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body {
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| 16 |
+
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, 'Helvetica Neue', Arial, sans-serif;
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| 17 |
+
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
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| 18 |
+
min-height: 100vh;
|
| 19 |
+
display: flex;
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| 20 |
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flex-direction: column;
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| 21 |
+
align-items: center;
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| 22 |
+
padding: 20px;
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| 23 |
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}
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| 24 |
+
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| 25 |
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.container {
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| 26 |
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width: 100%;
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| 27 |
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max-width: 1200px;
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| 28 |
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background: white;
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| 29 |
+
border-radius: 20px;
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| 30 |
+
box-shadow: 0 20px 60px rgba(0, 0, 0, 0.3);
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| 31 |
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overflow: hidden;
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| 32 |
+
animation: slideIn 0.5s ease-out;
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| 33 |
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}
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| 34 |
+
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| 35 |
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@keyframes slideIn {
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| 36 |
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from {
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| 37 |
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opacity: 0;
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| 38 |
+
transform: translateY(30px);
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| 39 |
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}
|
| 40 |
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to {
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| 41 |
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opacity: 1;
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| 42 |
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transform: translateY(0);
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| 43 |
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}
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| 44 |
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}
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| 45 |
+
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| 46 |
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.header {
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| 47 |
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background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
|
| 48 |
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color: white;
|
| 49 |
+
padding: 30px;
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| 50 |
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text-align: center;
|
| 51 |
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}
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| 52 |
+
|
| 53 |
+
.header h1 {
|
| 54 |
+
font-size: 2.5rem;
|
| 55 |
+
margin-bottom: 10px;
|
| 56 |
+
font-weight: 700;
|
| 57 |
+
text-shadow: 2px 2px 4px rgba(0, 0, 0, 0.2);
|
| 58 |
+
}
|
| 59 |
+
|
| 60 |
+
.header p {
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| 61 |
+
font-size: 1.1rem;
|
| 62 |
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opacity: 0.95;
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| 63 |
+
margin-bottom: 20px;
|
| 64 |
+
}
|
| 65 |
+
|
| 66 |
+
.features {
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| 67 |
+
display: flex;
|
| 68 |
+
justify-content: center;
|
| 69 |
+
gap: 30px;
|
| 70 |
+
margin-top: 20px;
|
| 71 |
+
flex-wrap: wrap;
|
| 72 |
+
}
|
| 73 |
+
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| 74 |
+
.feature {
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| 75 |
+
display: flex;
|
| 76 |
+
align-items: center;
|
| 77 |
+
gap: 8px;
|
| 78 |
+
background: rgba(255, 255, 255, 0.2);
|
| 79 |
+
padding: 8px 16px;
|
| 80 |
+
border-radius: 20px;
|
| 81 |
+
backdrop-filter: blur(10px);
|
| 82 |
+
}
|
| 83 |
+
|
| 84 |
+
.feature-icon {
|
| 85 |
+
font-size: 1.2rem;
|
| 86 |
+
}
|
| 87 |
+
|
| 88 |
+
.app-container {
|
| 89 |
+
padding: 40px;
|
| 90 |
+
background: #f8f9fa;
|
| 91 |
+
min-height: 600px;
|
| 92 |
+
}
|
| 93 |
+
|
| 94 |
+
.loading-message {
|
| 95 |
+
text-align: center;
|
| 96 |
+
padding: 40px;
|
| 97 |
+
color: #666;
|
| 98 |
+
}
|
| 99 |
+
|
| 100 |
+
.loading-spinner {
|
| 101 |
+
display: inline-block;
|
| 102 |
+
width: 50px;
|
| 103 |
+
height: 50px;
|
| 104 |
+
border: 3px solid rgba(0, 0, 0, 0.1);
|
| 105 |
+
border-radius: 50%;
|
| 106 |
+
border-top-color: #667eea;
|
| 107 |
+
animation: spin 1s ease-in-out infinite;
|
| 108 |
+
margin-bottom: 20px;
|
| 109 |
+
}
|
| 110 |
+
|
| 111 |
+
@keyframes spin {
|
| 112 |
+
to { transform: rotate(360deg); }
|
| 113 |
+
}
|
| 114 |
+
|
| 115 |
+
.info-cards {
|
| 116 |
+
display: grid;
|
| 117 |
+
grid-template-columns: repeat(auto-fit, minmax(300px, 1fr));
|
| 118 |
+
gap: 20px;
|
| 119 |
+
padding: 20px;
|
| 120 |
+
margin-bottom: 30px;
|
| 121 |
+
}
|
| 122 |
+
|
| 123 |
+
.info-card {
|
| 124 |
+
background: white;
|
| 125 |
+
border-radius: 12px;
|
| 126 |
+
padding: 20px;
|
| 127 |
+
box-shadow: 0 2px 10px rgba(0, 0, 0, 0.08);
|
| 128 |
+
transition: transform 0.3s ease, box-shadow 0.3s ease;
|
| 129 |
+
}
|
| 130 |
+
|
| 131 |
+
.info-card:hover {
|
| 132 |
+
transform: translateY(-5px);
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| 133 |
+
box-shadow: 0 5px 20px rgba(0, 0, 0, 0.12);
|
| 134 |
+
}
|
| 135 |
+
|
| 136 |
+
.info-card h3 {
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| 137 |
+
color: #667eea;
|
| 138 |
+
margin-bottom: 10px;
|
| 139 |
+
font-size: 1.2rem;
|
| 140 |
+
}
|
| 141 |
+
|
| 142 |
+
.info-card p {
|
| 143 |
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color: #666;
|
| 144 |
+
line-height: 1.6;
|
| 145 |
+
}
|
| 146 |
+
|
| 147 |
+
@media (max-width: 768px) {
|
| 148 |
+
.header h1 {
|
| 149 |
+
font-size: 1.8rem;
|
| 150 |
+
}
|
| 151 |
+
|
| 152 |
+
.header p {
|
| 153 |
+
font-size: 1rem;
|
| 154 |
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}
|
| 155 |
+
|
| 156 |
+
.features {
|
| 157 |
+
gap: 10px;
|
| 158 |
+
}
|
| 159 |
+
|
| 160 |
+
.app-container {
|
| 161 |
+
padding: 20px;
|
| 162 |
+
}
|
| 163 |
+
}
|
| 164 |
+
|
| 165 |
+
.tech-badge {
|
| 166 |
+
display: inline-block;
|
| 167 |
+
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
|
| 168 |
+
color: white;
|
| 169 |
+
padding: 4px 12px;
|
| 170 |
+
border-radius: 12px;
|
| 171 |
+
font-size: 0.85rem;
|
| 172 |
+
margin: 5px;
|
| 173 |
+
}
|
| 174 |
+
|
| 175 |
+
gradio-lite {
|
| 176 |
+
width: 100%;
|
| 177 |
+
min-height: 500px;
|
| 178 |
+
}
|
| 179 |
+
</style>
|
| 180 |
+
</head>
|
| 181 |
+
<body>
|
| 182 |
+
<div class="container">
|
| 183 |
+
<div class="header">
|
| 184 |
+
<h1>🤖 AI Chat Assistant</h1>
|
| 185 |
+
<p>Powered by Gemma 270M Model & Hugging Face Transformers</p>
|
| 186 |
+
<div class="features">
|
| 187 |
+
<div class="feature">
|
| 188 |
+
<span class="feature-icon">⚡</span>
|
| 189 |
+
<span>Fast Inference</span>
|
| 190 |
+
</div>
|
| 191 |
+
<div class="feature">
|
| 192 |
+
<span class="feature-icon">🔒</span>
|
| 193 |
+
<span>100% Browser-Based</span>
|
| 194 |
+
</div>
|
| 195 |
+
<div class="feature">
|
| 196 |
+
<span class="feature-icon">🌐</span>
|
| 197 |
+
<span>No Server Required</span>
|
| 198 |
+
</div>
|
| 199 |
+
</div>
|
| 200 |
+
</div>
|
| 201 |
+
|
| 202 |
+
<div class="info-cards">
|
| 203 |
+
<div class="info-card">
|
| 204 |
+
<h3>💡 How It Works</h3>
|
| 205 |
+
<p>This application runs entirely in your browser using WebAssembly and Pyodide. The AI model is loaded directly in your browser for complete privacy and offline capability.</p>
|
| 206 |
+
</div>
|
| 207 |
+
<div class="info-card">
|
| 208 |
+
<h3>🚀 Technologies Used</h3>
|
| 209 |
+
<p>
|
| 210 |
+
<span class="tech-badge">Gradio Lite</span>
|
| 211 |
+
<span class="tech-badge">Hugging Face</span>
|
| 212 |
+
<span class="tech-badge">ONNX Runtime</span>
|
| 213 |
+
<span class="tech-badge">WebAssembly</span>
|
| 214 |
+
</p>
|
| 215 |
+
</div>
|
| 216 |
+
<div class="info-card">
|
| 217 |
+
<h3>📝 Getting Started</h3>
|
| 218 |
+
<p>Simply type your message in the chat interface below. The AI will process your request locally and generate a response using the Gemma model.</p>
|
| 219 |
+
</div>
|
| 220 |
+
</div>
|
| 221 |
+
|
| 222 |
+
<div class="app-container">
|
| 223 |
+
<div class="loading-message">
|
| 224 |
+
<div class="loading-spinner"></div>
|
| 225 |
+
<h3>Loading AI Model...</h3>
|
| 226 |
+
<p>This may take 10-30 seconds on first load as we download and initialize the model.</p>
|
| 227 |
+
</div>
|
| 228 |
+
|
| 229 |
+
<gradio-lite theme="light">
|
| 230 |
+
<gradio-requirements>
|
| 231 |
+
transformers_js_py
|
| 232 |
+
</gradio-requirements>
|
| 233 |
+
|
| 234 |
+
<gradio-file name="app.py" entrypoint>
|
| 235 |
+
import gradio as gr
|
| 236 |
+
from transformers_js import import_transformers_js
|
| 237 |
+
import asyncio
|
| 238 |
+
|
| 239 |
+
# Import transformers.js
|
| 240 |
+
transformers = await import_transformers_js()
|
| 241 |
+
pipeline = transformers.pipeline
|
| 242 |
+
TextStreamer = transformers.TextStreamer
|
| 243 |
+
|
| 244 |
+
# Initialize the model pipeline
|
| 245 |
+
print("Loading model... This may take a moment.")
|
| 246 |
+
generator = await pipeline(
|
| 247 |
+
"text-generation",
|
| 248 |
+
"onnx-community/gemma-3-270m-it-ONNX",
|
| 249 |
+
{
|
| 250 |
+
"dtype": "fp32",
|
| 251 |
+
}
|
| 252 |
+
)
|
| 253 |
+
|
| 254 |
+
# Store conversation history
|
| 255 |
+
conversation_history = []
|
| 256 |
+
|
| 257 |
+
async def chat_with_ai(message, history):
|
| 258 |
+
"""Process user message and generate AI response"""
|
| 259 |
+
if not message:
|
| 260 |
+
return history
|
| 261 |
+
|
| 262 |
+
# Format the conversation for the model
|
| 263 |
+
messages = [
|
| 264 |
+
{"role": "system", "content": "You are a helpful AI assistant. Provide clear, concise, and informative responses."},
|
| 265 |
+
]
|
| 266 |
+
|
| 267 |
+
# Add conversation history
|
| 268 |
+
for user_msg, assistant_msg in history:
|
| 269 |
+
messages.append({"role": "user", "content": user_msg})
|
| 270 |
+
messages.append({"role": "assistant", "content": assistant_msg})
|
| 271 |
+
|
| 272 |
+
# Add current message
|
| 273 |
+
messages.append({"role": "user", "content": message})
|
| 274 |
+
|
| 275 |
+
try:
|
| 276 |
+
# Generate response
|
| 277 |
+
output = await generator(messages, {
|
| 278 |
+
"max_new_tokens": 256,
|
| 279 |
+
"temperature": 0.7,
|
| 280 |
+
"do_sample": True,
|
| 281 |
+
"top_p": 0.9,
|
| 282 |
+
})
|
| 283 |
+
|
| 284 |
+
# Extract the assistant's response
|
| 285 |
+
response = output[0]["generated_text"][-1]["content"]
|
| 286 |
+
|
| 287 |
+
# Update history
|
| 288 |
+
history.append([message, response])
|
| 289 |
+
return history
|
| 290 |
+
|
| 291 |
+
except Exception as e:
|
| 292 |
+
error_msg = f"Error generating response: {str(e)}"
|
| 293 |
+
history.append([message, error_msg])
|
| 294 |
+
return history
|
| 295 |
+
|
| 296 |
+
def clear_chat():
|
| 297 |
+
"""Clear the conversation history"""
|
| 298 |
+
return []
|
| 299 |
+
|
| 300 |
+
# Create the Gradio interface
|
| 301 |
+
with gr.Blocks(title="AI Chat Assistant") as demo:
|
| 302 |
+
gr.Markdown(
|
| 303 |
+
"""
|
| 304 |
+
# 🤖 AI Chat Assistant
|
| 305 |
+
Chat with an AI powered by the Gemma model running entirely in your browser!
|
| 306 |
+
"""
|
| 307 |
+
)
|
| 308 |
+
|
| 309 |
+
chatbot = gr.Chatbot(
|
| 310 |
+
height=400,
|
| 311 |
+
placeholder="Start chatting with the AI assistant...",
|
| 312 |
+
bubble_full_width=False,
|
| 313 |
+
)
|
| 314 |
+
|
| 315 |
+
with gr.Row():
|
| 316 |
+
msg = gr.Textbox(
|
| 317 |
+
placeholder="Type your message here and press Enter...",
|
| 318 |
+
label="Your Message",
|
| 319 |
+
lines=2,
|
| 320 |
+
scale=4
|
| 321 |
+
)
|
| 322 |
+
submit_btn = gr.Button("Send", variant="primary", scale=1)
|
| 323 |
+
|
| 324 |
+
with gr.Row():
|
| 325 |
+
clear_btn = gr.Button("🗑️ Clear Chat", variant="secondary")
|
| 326 |
+
|
| 327 |
+
gr.Examples(
|
| 328 |
+
examples=[
|
| 329 |
+
"What is machine learning?",
|
| 330 |
+
"Write a short poem about technology",
|
| 331 |
+
"Explain quantum computing in simple terms",
|
| 332 |
+
"What are the benefits of renewable energy?",
|
| 333 |
+
"How does the internet work?",
|
| 334 |
+
],
|
| 335 |
+
inputs=msg,
|
| 336 |
+
label="Example Questions"
|
| 337 |
+
)
|
| 338 |
+
|
| 339 |
+
# Set up event handlers
|
| 340 |
+
msg.submit(chat_with_ai, [msg, chatbot], chatbot)
|
| 341 |
+
msg.submit(lambda: "", None, msg)
|
| 342 |
+
|
| 343 |
+
submit_btn.click(chat_with_ai, [msg, chatbot], chatbot)
|
| 344 |
+
submit_btn.click(lambda: "", None, msg)
|
| 345 |
+
|
| 346 |
+
clear_btn.click(clear_chat, None, chatbot)
|
| 347 |
+
|
| 348 |
+
gr.Markdown(
|
| 349 |
+
"""
|
| 350 |
+
---
|
| 351 |
+
**Note:** This model runs entirely in your browser. No data is sent to any server.
|
| 352 |
+
Initial loading may take some time as the model is downloaded and initialized.
|
| 353 |
+
"""
|
| 354 |
+
)
|
| 355 |
+
|
| 356 |
+
demo.launch()
|
| 357 |
+
</gradio-file>
|
| 358 |
+
</gradio-lite>
|
| 359 |
+
</div>
|
| 360 |
+
</div>
|
| 361 |
+
|
| 362 |
+
<script>
|
| 363 |
+
// Hide loading message when Gradio app loads
|
| 364 |
+
window.addEventListener('load', () => {
|
| 365 |
+
setTimeout(() => {
|
| 366 |
+
const loadingMsg = document.querySelector('.loading-message');
|
| 367 |
+
if (loadingMsg) {
|
| 368 |
+
loadingMsg.style.display = 'none';
|
| 369 |
+
}
|
| 370 |
+
}, 5000);
|
| 371 |
+
});
|
| 372 |
+
</script>
|
| 373 |
+
</body>
|
| 374 |
+
</html>
|