app.py

# pip install gradio openai

import gradio as gr
import os
from openai import OpenAI 

# --- API Initialization ---
os.environ["HF_TOKEN"]

try:
    hf_client = OpenAI(
        base_url="https://router.huggingface.co/v1",
        api_key=os.environ["HF_TOKEN"],
    )
except KeyError:
    print("FATAL ERROR: Please set the 'HF_TOKEN' environment variable.")
    raise


# ===========================================
#      VR CONFIGURATION (MULTI-MODEL)
# ===========================================
yacht_models = {
    "Princess Y85": {
        "Compact": "https://vrcloud.com/?pv=1550754573&play=1",
        "Tall":    "https://vrcloud.com/?pv=1550754573&play=1",
        "Full":    "https://vrcloud.com/?pv=1550754573&play=1"
    },
    "Princess X95": {
        "Compact": "https://vrcloud.com/?pv=1620886782&play=1",
        "Tall":    "https://vrcloud.com/?pv=1620886782&play=1",
        "Full":    "https://vrcloud.com/?pv=1620886782&play=1"
    }
}

DEFAULT_MODEL = "Princess Y85"
DEFAULT_VIEW = "Full"

DEFAULT_VR_HTML = """
<div style="text-align:center; padding: 20px; border: 1px dashed #ccc; border-radius: 5px;">
    <h3>🚢 Ask the chat to start the Virtual Reality Experience!</h3>
    <p>Try phrases like: <b>Show me the Y85 full VR view</b> or <b>Show me the X95 compact view</b>.</p>
</div>
"""


# ===========================================
#              VR HTML BUILDER
# ===========================================
def generate_vr_html(model, view):
    try:
        link = yacht_models[model][view]
    except KeyError:
        model = DEFAULT_MODEL
        view = DEFAULT_VIEW
        link = yacht_models[model][view]

    return f"""
    <div style="text-align:center">
        <h3>🚢 {model} – {view} VR View</h3>
        <iframe src="{link}" width="100%" height="600px" style="border:none; border-radius:10px;"></iframe>
    </div>
    """


# ===========================================
#              MAIN CHATBOT LOGIC
# ===========================================
def yacht_chatbot(user_input, chat_history):

    # Convert history formats
    messages = [
        {
            "role": "system",
            "content": (
                "You are a knowledgeable yacht expert who provides information about "
                "Princess Yachts. You may also trigger VR views for Y85 or X95 "
                "in Compact, Tall, or Full view modes."
            )
        }
    ]

    for item in chat_history:
        if isinstance(item, tuple) and len(item) == 2:
            user_msg, bot_msg = item
            if user_msg:
                messages.append({"role": "user", "content": user_msg})
            if bot_msg:
                messages.append({"role": "assistant", "content": bot_msg})
        elif isinstance(item, dict) and "role" in item and "content" in item:
            messages.append(item)

    # Add new user input
    messages.append({"role": "user", "content": user_input})

    bot_reply = "Let me help with that."

    # --- LLM Response ---
    try:
        resp = hf_client.chat.completions.create(
            #model="moonshotai/Kimi-K2-Thinking",
            #model="deepseek-ai/DeepSeek-V3.2-Exp",
            model="meta-llama/Llama-3.1-8B-Instruct",
            messages=messages,
            temperature=0.7
        )
        bot_reply = resp.choices[0].message.content

    except Exception as e:
        bot_reply = f"AI service error: {e}"
        chat_history.append((user_input, bot_reply))
        return format_history(chat_history), DEFAULT_VR_HTML


    # ===========================================
    #            VR MODEL & VIEW PARSER
    # ===========================================
    text = user_input.lower()

    # Model detection
    if "y85" in text:
        model = "Princess Y85"
    elif "x95" in text:
        model = "Princess X95"
    else:
        model = DEFAULT_MODEL

    # View detection
    if "compact" in text:
        view = "Compact"
    elif "tall" in text:
        view = "Tall"
    elif "full" in text or "3d" in text or "vr" in text:
        view = "Full"
    else:
        view = DEFAULT_VIEW

    # Generate VR HTML
    vr_html = generate_vr_html(model, view)

    # Save conversation
    chat_history.append((user_input, bot_reply))
    return format_history(chat_history), vr_html


# ===========================================
#          HISTORY FORMAT NORMALIZER
# ===========================================
def format_history(history_items):
    formatted = []
    for item in history_items:

        if isinstance(item, tuple) and len(item) == 2:
            formatted.append({"role": "user", "content": item[0]})
            formatted.append({"role": "assistant", "content": item[1]})

        elif isinstance(item, dict) and "role" in item:
            formatted.append(item)

    return formatted


def clear_textbox():
    return ""

def clear_all():
    return [], DEFAULT_VR_HTML, ""


# ===========================================
#                   UI
# ===========================================
with gr.Blocks(title="Princess Yacht Virtual Chatbot") as demo:

    gr.Markdown("""
    # 🛥️ Princess Yacht Virtual Experience
    Chat with the AI and load a **live 3D VR yacht view** for Princess Y85 or X95.
    """)

    dynamic_vr_html = gr.HTML(DEFAULT_VR_HTML)

    chatbot = gr.Chatbot(label="Princess Yacht Chat", height=400)
    
    msg = gr.Textbox(
        label="Ask about the yacht or VR",
        placeholder="Try: show me the X95 full VR"
    )

    clear = gr.Button("Clear Chat")

    msg.submit(
        yacht_chatbot,
        inputs=[msg, chatbot],
        outputs=[chatbot, dynamic_vr_html],
        queue=False
    ).then(
        clear_textbox,
        None,
        [msg],
        queue=False
    )

    clear.click(
        clear_all,
        None,
        [chatbot, dynamic_vr_html, msg],
        queue=False
    )


demo.launch(
    debug=True,
    share=False,
    ssr_mode=False
)