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/vcVnxPZhCXRVL2fn3rG6B.jpeg');
  background-size: cover;
  background-position: center;
  background-repeat: no-repeat;
}
.gradio-container {
  display: flex;
  flex-direction: column;
  justify-content: center;
  min-height: 100vh;
  padding-top: 2rem;
  padding-bottom: 2rem;
}
#chat-panel {
  background-color: rgba(255, 255, 255, 0.85);
  padding: 2rem;
  border-radius: 12px;
  justify-content: center;
  width: 100%;
  max-width: 700px;
  height: 70vh;
  box-shadow: 0 0 12px rgba(0, 0, 0, 0.3);
  overflow-y: auto;
}
/* Improved title styling */
.gradio-container .chatbot h1 {
   color: var(--custom-title-color) !important;
   font-family: 'Noto Sans', serif !important;
   font-size: 5rem !important;  /* Increased font size */
   font-weight: bold !important;
   text-align: center !important;
   margin-bottom: 1.5rem !important;
   width: 100%;  /* Ensure full width for centering */
}
"""

client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")

def respond(
    message,
    history,
    system_message,
    max_tokens,
    temperature,
    top_p,
):
    messages = [{"role": "system", "content": system_message}]
    
    # Handle history based on its format (tuple format or messages format)
    if history and isinstance(history[0], tuple):
        # Old tuple format
        for user_msg, assistant_msg in history:
            if user_msg:
                messages.append({"role": "user", "content": user_msg})
            if assistant_msg:
                messages.append({"role": "assistant", "content": assistant_msg})
    else:
        # New messages format
        messages.extend(history)
    
    messages.append({"role": "user", "content": message})
    
    response = ""
    
    for msg in client.chat_completion(
        messages,
        max_tokens=max_tokens,
        stream=True,
        temperature=temperature,
        top_p=top_p,
    ):
        token = msg.choices[0].delta.content
        response += token
        yield response

with gr.Blocks(css=css) as demo:
    # Title Markdown block
    gr.Markdown("French 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 language tutor. You help users learn French vocabulary, grammar, and cultural contexts. When appropriate, include both the French writing and pronunciation. For beginners, focus on simple phrases and gradually increase difficulty based on user proficiency.", 
                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
            ],
            type="messages"  # Set to new message format
        )

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