"""
Interfaz Gradio para el Spanish Menu Translator.
"""

import gradio as gr

from config import MAX_QUEUE_SIZE, SERVER_PORT
from core.pipeline import MenuTranslatorPipeline


def build_interface(pipeline_instance: MenuTranslatorPipeline) -> gr.Blocks:
    """Construye y retorna la interfaz Gradio."""

    def process_image(image, target_lang, detail_level, include_cultural_notes):
        if image is None:
            return "⚠️ Por favor, sube una imagen de menú.", "{}", ""
        return pipeline_instance.process_menu(
            image, target_lang, detail_level, include_cultural_notes
        )

    with gr.Blocks(theme=gr.themes.Soft(), title="Spanish Menu Translator") as demo:
        gr.Markdown("""
        # 🍽️ Spanish Menu Translator & Cultural Guide

        Upload an image of a Spanish menu to get:
        - ✅ **Accurate OCR** text extraction
        - ✅ **Professional translation** to English (or other languages)
        - ✅ **Cultural descriptions** of each dish

        **Powered by 3 AI Models:**
        - 📷 OCR: LightOnOCR-2-1B (1.1B params)
        - 🌐 Translation: NLLB-200 (600M params)
        - 📝 Descriptions: GPT-2 Spanish (355M params)
        """)

        with gr.Row():
            # --- INPUT ---
            with gr.Column(scale=1):
                gr.Markdown("## 📥 Input")

                image_input = gr.Image(
                    type="pil",
                    label="Upload Menu Image",
                    sources=["upload", "clipboard", "webcam"],
                )

                with gr.Accordion("⚙️ Settings", open=True):
                    target_lang = gr.Dropdown(
                        choices=["English", "French", "German", "Italian"],
                        value="English",
                        label="Target Language",
                    )
                    detail_level = gr.Slider(
                        minimum=1, maximum=3, value=2, step=1,
                        label="Description Detail Level",
                        info="1=Brief, 2=Medium, 3=Detailed",
                    )
                    include_cultural = gr.Checkbox(
                        value=True, label="Include Cultural Notes"
                    )

                process_btn = gr.Button(
                    "🚀 Translate Menu", variant="primary", size="lg"
                )

            # --- OUTPUT ---
            with gr.Column(scale=1):
                gr.Markdown("## 📤 Output")

                with gr.Tabs():
                    with gr.TabItem("📄 Translation"):
                        markdown_output = gr.Markdown(
                            label="Translated Menu",
                            value="*Results will appear here...*",
                        )
                    with gr.TabItem("📊 Statistics"):
                        stats_output = gr.Code(
                            language="json",
                            label="Processing Statistics",
                            value="{}",
                        )
                    with gr.TabItem("🔍 Raw OCR Text"):
                        raw_output = gr.Textbox(
                            label="Extracted Spanish Text", lines=15, value=""
                        )

        process_btn.click(
            fn=process_image,
            inputs=[image_input, target_lang, detail_level, include_cultural],
            outputs=[markdown_output, stats_output, raw_output],
        )

        with gr.Accordion("ℹ️ About This Tool", open=False):
            gr.Markdown("""
            ### How it works:

            1. **OCR Extraction** (LightOnOCR-2-1B) — Extracts text from your menu image (~3-4s)
            2. **Translation** (NLLB-200) — Translates dish names preserving culinary terminology
            3. **Description Generation** (GPT-2 Spanish) — Creates cultural context for each dish

            ### Limitations:
            - Processing time: ~15-20 seconds
            - Works best with clear, well-lit images
            - Maximum 20 dishes per menu

            ### Privacy:
            - All processing happens on this server
            - Images are not stored
            - No data is sent to external APIs
            """)

    return demo


def launch(demo: gr.Blocks):
    """Lanza la aplicación."""
    demo.queue(max_size=MAX_QUEUE_SIZE)
    demo.launch(server_name="0.0.0.0", server_port=SERVER_PORT, share=False)