"""
Gradio Blocks UI for the multilingual RAG chatbot.
Run: python3 app.py
"""

import subprocess
import pathlib
import gradio as gr
from rag_pipeline import RAGPipeline

if not pathlib.Path("faiss_index").exists():
    print("FAISS index not found — running ingest.py...")
    subprocess.run(["python3", "ingest.py"], check=True)

pipeline = RAGPipeline()

DESCRIPTION = """
# 🌐 Multilingual RAG Chatbot
Ask questions in **English**, **العربية (Arabic)**, or **Bahasa Melayu (Malay)**.
Answers are grounded in the knowledge base. Retrieved source passages appear below each answer.
"""

EXAMPLES = [
    ["What is retrieval-augmented generation?"],
    ["How does machine learning differ from deep learning?"],
    ["What are vector databases used for?"],
    ["ما هو الذكاء الاصطناعي؟"],
    ["كيف يعمل التعلم الآلي؟"],
    ["ما هي قواعد البيانات المتجهية؟"],
    ["Apakah itu kecerdasan buatan?"],
    ["Bagaimana pembelajaran mesin berfungsi?"],
    ["Apakah RAG dan kegunaannya?"],
]

RTL_CSS = """
.message-bubble p, .message-bubble span, .prose p {
    unicode-bidi: plaintext;
    text-align: start;
}
[lang="ar"], .rtl-text {
    direction: rtl;
    text-align: right;
    font-family: 'Segoe UI', Tahoma, Arial, sans-serif;
}
.source-box {
    border-left: 3px solid #6366f1;
    padding-left: 0.75rem;
    margin: 0.5rem 0;
    font-size: 0.875rem;
}
.example-btn { font-size: 0.82rem !important; }
"""

JS_RTL = """
function applyRTL() {
    document.querySelectorAll('.message-bubble p, .prose p').forEach(el => {
        if (/[؀-ۿ]/.test(el.innerText || '')) {
            el.setAttribute('dir', 'rtl');
            el.style.textAlign = 'right';
        }
    });
}
const observer = new MutationObserver(applyRTL);
observer.observe(document.body, { childList: true, subtree: true });
applyRTL();
"""


def format_sources(sources: list[dict]) -> str:
    if not sources:
        return "_No sources retrieved._"
    lines = []
    for i, s in enumerate(sources, 1):
        snippet = s["content"].replace("\n", " ").strip()
        if len(snippet) > 300:
            snippet = snippet[:300] + "…"
        file_name = s["source"].split("/")[-1]
        lines.append(f"**[{i}] `{file_name}`**\n> {snippet}")
    return "\n\n".join(lines)


def respond(message: str, history: list):
    if not message.strip():
        yield history, "_Please enter a question._"
        return

    result = pipeline.ask(message)
    answer = result["answer"]
    sources_md = format_sources(result["sources"])

    history = history + [
        {"role": "user", "content": message},
        {"role": "assistant", "content": answer},
    ]
    yield history, sources_md


def clear_all():
    pipeline.chain.memory.clear()
    return [], "_Sources will appear here after your first question._"


with gr.Blocks(title="Multilingual RAG Chatbot") as demo:
    gr.Markdown(DESCRIPTION)

    with gr.Row():
        with gr.Column(scale=3):
            chatbot = gr.Chatbot(
                elem_id="chatbot",
                label="Chat",
                height=480,
            )

            with gr.Row():
                msg_box = gr.Textbox(
                    placeholder="Type your question in English, العربية, or Bahasa Melayu…",
                    show_label=False,
                    scale=8,
                    autofocus=True,
                )
                send_btn = gr.Button("Send ➤", variant="primary", scale=1)

            with gr.Row():
                clear_btn = gr.Button("🗑 Clear Chat", variant="secondary", size="sm")

        with gr.Column(scale=2):
            gr.Markdown("### 📄 Retrieved Sources")
            sources_box = gr.Markdown(
                value="_Sources will appear here after your first question._",
            )

    with gr.Accordion("💡 Example Questions", open=True):
        with gr.Row():
            with gr.Column():
                gr.Markdown("**🇬🇧 English**")
                for ex in EXAMPLES[:3]:
                    gr.Button(ex[0], elem_classes="example-btn").click(
                        fn=lambda q=ex[0]: q,
                        outputs=msg_box,
                    )
            with gr.Column():
                gr.Markdown("**🇸🇦 العربية**")
                for ex in EXAMPLES[3:6]:
                    gr.Button(ex[0], elem_classes="example-btn").click(
                        fn=lambda q=ex[0]: q,
                        outputs=msg_box,
                    )
            with gr.Column():
                gr.Markdown("**🇲🇾 Bahasa Melayu**")
                for ex in EXAMPLES[6:]:
                    gr.Button(ex[0], elem_classes="example-btn").click(
                        fn=lambda q=ex[0]: q,
                        outputs=msg_box,
                    )

    submit_inputs = [msg_box, chatbot]
    submit_outputs = [chatbot, sources_box]

    msg_box.submit(respond, submit_inputs, submit_outputs).then(
        fn=lambda: "", outputs=msg_box
    )
    send_btn.click(respond, submit_inputs, submit_outputs).then(
        fn=lambda: "", outputs=msg_box
    )
    clear_btn.click(clear_all, outputs=[chatbot, sources_box])

if __name__ == "__main__":
    demo.launch(
        server_name="0.0.0.0",
        server_port=7860,
        show_error=True,
        css=RTL_CSS,
        js=JS_RTL,
    )