import gradio as gr
import os
from huggingface_hub import InferenceClient
from huggingface_hub.inference._generated.types.chat_completion import ChatCompletionStreamOutput

MODEL = "nomiChroma3.1"
client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")

def respond(
    message,
    history: list[tuple[str, str]],
    system_message,
    max_tokens,
    temperature,
    top_p,
):
    messages = [{"role": "system", "content": system_message}]
    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 = ""
    try:
        for message in client.chat_completion(
            messages,
            max_tokens=max_tokens,
            stream=True,
            temperature=temperature,
            top_p=top_p,
        ):
            try:
                if isinstance(message, ChatCompletionStreamOutput):
                    content = message.choices[0].delta.content
                    if content is not None:
                        response += content
                        yield response
                    if message.choices[0].finish_reason == 'stop':
                        break
                elif isinstance(message, dict):
                    content = message.get('choices', [{}])[0].get('delta', {}).get('content')
                    if content:
                        response += content
                        yield response
                    if message.get('choices', [{}])[0].get('finish_reason') == 'stop':
                        break
                elif isinstance(message, str):
                    if message.strip():
                        response += message
                        yield response
            except Exception as e:
                print(f"Error processing message: {e}")
                continue

        if response:
            yield response

    except Exception as e:
        print(f"An error occurred: {e}")
        yield f"An error occurred: {e}"

# Custom CSS for maritime theme with sidebar
custom_css = """
    /* Global styles */
    .gradio-container {
        background-color: #e6f3ff !important;
    }

    /* Header styling */
    .header-container {
        text-align: center;
        padding: 2rem 0;
        margin-bottom: 2rem;
        border-bottom: 2px solid rgba(26, 54, 93, 0.1);
    }

    .header-title {
        color: #1a365d;
        font-size: 2.5rem;
        margin-bottom: 0.5rem;
    }

    .header-subtitle {
        color: #2c5282;
        font-size: 1.1rem;
    }

    /* Sidebar styling */
    .sidebar {
        background: rgba(255, 255, 255, 0.9) !important;
        border-radius: 12px !important;
        padding: 20px !important;
        border: 1px solid rgba(26, 54, 93, 0.1) !important;
        height: fit-content !important;
    }

    .sidebar-title {
        font-size: 1.2rem !important;
        color: #1a365d !important;
        margin-bottom: 1rem !important;
        padding-bottom: 0.5rem !important;
        border-bottom: 2px solid rgba(26, 54, 93, 0.1) !important;
    }

    /* Chat container */
    .chat-container {
        background: rgba(255, 255, 255, 0.7) !important;
        border-radius: 12px !important;
        padding: 20px !important;
        height: 600px !important;
        overflow-y: auto !important;
    }

    /* Message styling */
    .message.user, .message.bot {
        padding: 12px 16px !important;
        margin: 8px 0 !important;
        border-radius: 8px !important;
    }

    .message.user {
        background-color: #e1f0ff !important;
    }

    .message.bot {
        background-color: #ffffff !important;
    }

    /* Input styling */
    textarea {
        background-color: #ffffff !important;
        border: 1px solid rgba(26, 54, 93, 0.2) !important;
        border-radius: 8px !important;
        padding: 12px !important;
    }

    /* Slider styling */
    .gr-slider {
        margin: 1rem 0 !important;
    }
"""

# Main application
with gr.Blocks(css=custom_css, theme=gr.themes.Base()) as demo:
    # Header
    gr.HTML("""
        <div class="header-container">
            <h1 class="header-title">Maritime Legal Compliance</h1>
            <p class="header-subtitle">AI-powered assistance for Indian maritime law queries</p>
        </div>
    """)

    # Main layout with sidebar
    with gr.Row():
        # Sidebar
        with gr.Column(scale=1, elem_classes="sidebar"):
            gr.Markdown("### Configuration", elem_classes="sidebar-title")
            system_message = gr.Textbox(
                value="You are a maritime legal assistant with expertise strictly in Indian maritime law. Provide detailed legal advice and information based on Indian maritime legal principles and regulations.",
                label="System Prompt",
                lines=4
            )
            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 Level"
            )
            top_p = gr.Slider(
                minimum=0.1,
                maximum=1.0,
                value=0.95,
                step=0.05,
                label="Response Focus"
            )
            
            gr.Markdown("### Example Queries", elem_classes="sidebar-title")
            examples = gr.Examples(
                examples=[
                    ["What are the key regulations governing ports in India?"],
                    ["Explain the concept of cabotage in Indian maritime law."],
                    ["What are the legal requirements for registering a vessel in India?"],
                ],
                inputs=[system_message],
                label="Click on any example to load it"
            )

        # Main chat area
        with gr.Column(scale=3):
            chatbot = gr.Chatbot(height=500, elem_classes="chat-container")
            msg = gr.Textbox(
                show_label=False,
                placeholder="Type your maritime law query here...",
                container=False
            )
            with gr.Row():
                submit = gr.Button("Send", variant="primary")
                clear = gr.Button("Clear")

            # Event handlers
            submit_click = submit.click(
                respond,
                inputs=[msg, chatbot, system_message, max_tokens, temperature, top_p],
                outputs=chatbot
            )
            msg_submit = msg.submit(
                respond,
                inputs=[msg, chatbot, system_message, max_tokens, temperature, top_p],
                outputs=chatbot
            )
            clear.click(lambda: None, None, chatbot, queue=False)

# Launch the app
if __name__ == "__main__":
    demo.launch()