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import gradio as gr | |
from huggingface_hub import InferenceClient | |
# Custom background CSS with semi-transparent panel | |
css = """ | |
body { | |
background-image: url('https://cdn-uploads.huggingface.co/production/uploads/67351c643fe51cb1aa28f2e5/wuyd5UYTh9jPrMJGmV9yC.jpeg'); | |
background-size: cover; | |
background-position: center; | |
background-repeat: no-repeat; | |
} | |
#custom-title { | |
color: #d63384; | |
font-family: 'Playfair Display', serif; | |
font-size: 2.5rem; | |
font-weight: bold; | |
text-align: center; | |
margin-bottom: 20px; | |
} | |
#chat-panel { | |
background-color: rgba(255, 255, 255, 0.85); | |
padding: 2rem; | |
border-radius: 12px; | |
justify-content: center; | |
justify-content: center; | |
width: 100%; | |
max-width: 700px; | |
height: 70vh; | |
box-shadow: 0 0 12px rgba(0, 0, 0, 0.3); | |
overflow-y: auto; | |
} | |
""" | |
client = InferenceClient("HuggingFaceH4/zephyr-7b-beta") | |
def respond(message, history): | |
messages = [{"role": "system", "content": "You are a helpful French tutor."}] | |
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, | |
stream=True, | |
): | |
token = message.choices[0].delta.content | |
response += token | |
yield response | |
with gr.Blocks(css=css) as demo: | |
# Title Markdown block | |
gr.Markdown("Japanese Instructor", elem_id="custom-title") | |
with gr.Column(elem_id="chat-panel"): | |
with gr.Accordion("⚙️ Advanced Settings", open=False): | |
system_message = gr.Textbox( | |
value="You are a helpful French tutor.", | |
label="System Message" | |
) | |
max_tokens = gr.Slider( | |
minimum=1, | |
maximum=2048, | |
value=512, | |
step=1, | |
label="Response Length" | |
) | |
temperature = gr.Slider( | |
minimum=0.1, | |
maximum=4.0, | |
value=0.7, | |
step=0.1, | |
label="Creativity" | |
) | |
top_p = gr.Slider( | |
minimum=0.1, | |
maximum=1.0, | |
value=0.95, | |
step=0.05, | |
label="Dynamic Text" | |
) | |
gr.ChatInterface( | |
respond, | |
additional_inputs=[ | |
system_message, | |
max_tokens, | |
temperature, | |
top_p | |
] | |
) | |
if __name__ == "__main__": | |
demo.launch() | |