app.py

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;
}

.gradio-container {
  display: flex;
  flex-direction: column;
  justify-content: center;
  align-items: center;
  min-height: 100vh;
  padding-top: 2rem;
  padding-bottom: 2rem;
}

#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;
  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("# 🇫🇷 French Tutor", elem_id="custom-title")
    
    with gr.Column(elem_id="chat-panel"):
        gr.ChatInterface(respond)

if __name__ == "__main__":
    demo.launch()