import gradio as gr
from PIL import Image, ImageOps
import numpy as np
import easyocr
from pokedex import (
    get_base_hp,
    estimate_level_from_hp,
    get_english_name,
    get_pokemon_info,
)

reader = easyocr.Reader(['en'], gpu=False)

def find_pokemon_from_name_and_hp(name: str, hp: int) -> str:
    name_en = get_english_name(name)
    if "❌" in name_en:
        return "❌ Pokémon not recognized."

    try:
        base = get_base_hp(name_en)
        level = estimate_level_from_hp(int(hp), base)
        if not level:
            return "⚠️ Could not estimate level with provided HP."
        info = get_pokemon_info(name_en, level)
        return f"## 📊 Estimated Level: {level}\n\n{info}"
    except Exception as e:
        return f"⚠️ Error: {str(e)}"


def find_pokemon_from_name_and_level(name: str, level: int) -> str:
    name_en = get_english_name(name)
    if "❌" in name_en:
        return "❌ Pokémon not recognized."

    try:
        info = get_pokemon_info(name_en, level)
        return f"## 📊 Level: {level}\n\n{info}"
    except Exception as e:
        return f"⚠️ Error: {str(e)}"


manual_hp_interface = gr.Interface(
    fn=find_pokemon_from_name_and_hp,
    inputs=[
        gr.Text(label="Pokémon Name (EN or FR)"),
        gr.Number(label="Observed HP")
    ],
    outputs="markdown",
    title="Estimate Level from HP",
    description="Enter a Pokémon name and its observed HP to estimate its level and view full info."
)

manual_level_interface = gr.Interface(
    fn=find_pokemon_from_name_and_level,
    inputs=[
        gr.Text(label="Pokémon Name (EN or FR)"),
        gr.Slider(minimum=1, maximum=100, value=50, step=1, label="Level")
    ],
    outputs="markdown",
    title="Pokémon Stats at Specific Level",
    description="Enter a Pokémon name and a level to get its full info sheet."
)


# 📌 Mode OCR
def find_pokemon_from_card_image(image: Image.Image, source: str) -> str:
    if image is None:
        return "❌ No image provided."

    if source == "webcam":
        image = ImageOps.mirror(image)

    image_np = np.array(image)
    results = reader.readtext(image_np)

    all_texts = "### 📄 OCR Detected Texts:\n"
    for i, (bbox, text, conf) in enumerate(results):
        all_texts += f"- Text #{i+1}: `{text.strip()}` (confidence: {round(conf, 2)})\n"

    card_name = None
    if len(results) >= 1:
        text1 = results[0][1].strip().upper()
        if "IVEA" not in text1:
            card_name = get_english_name(results[0][1].strip())
        elif len(results) >= 2:
            card_name = get_english_name(results[1][1].strip())

    hp = None
    for (bbox, text, conf) in results[:5]:
        text_clean = text.strip()
        if conf > 0.9 and text_clean.isdigit():
            hp = int(text_clean)
            break

    level_info = ""
    pokemon_sheet = ""
    if hp is not None and card_name and "❌" not in card_name:
        try:
            base_hp = get_base_hp(card_name)
            level = estimate_level_from_hp(hp, base_hp)
            if level:
                level_info = f"## 📊 Estimated Level: {level}"
                pokemon_sheet = get_pokemon_info(card_name, level)
            else:
                level_info = "⚠️ Unable to estimate level from provided data."
        except Exception as e:
            level_info = f"⚠️ Error while processing: {str(e)}"
    else:
        level_info = "⚠️ Not enough information to estimate level."

    return f"""
### 🃏 OCR Result
**Pokémon Name (EN)**: {card_name or '❓ Not detected'}  
**HP**: {hp if hp is not None else '❓ Not detected'}  
{level_info}

---

{pokemon_sheet}
""".strip()

ocr_interface = gr.Interface(
    fn=find_pokemon_from_card_image,
    inputs=[
        gr.Image(type="pil", label="Pokémon Card Image", height=300, width=300),
        gr.Radio(["upload", "webcam"], label="Image Source", value="upload")
    ],
    outputs="markdown",
    title="OCR Pokémon Scanner",
    description="Upload or scan a Pokémon card to automatically extract info and estimate level.",
)

# 🌐 Multi-MCP Tabbed Interface
demo = gr.TabbedInterface(
    interface_list=[manual_hp_interface, manual_level_interface, ocr_interface],
    tab_names=["Manual from HP", "Manual from level", "Image OCR"]
)

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