import gradio as gr
import requests
import base64
import cv2
import numpy as np
from typing import List, Union

# =========================
# CONFIG
# =========================
API_BASE = "https://lifedebugger-face-recognition-sss-beta.hf.space/api/v1"

# =========================
# UTILITIES
# =========================
def img_np_to_base64(img: np.ndarray) -> str:
    """Convert numpy image to base64 JPG"""
    if img is None:
        return None
    success, buffer = cv2.imencode(".jpg", img)
    if not success:
        return None
    return base64.b64encode(buffer).decode("utf-8")


def load_gallery_item(item: Union[str, dict]) -> np.ndarray:
    """
    Gradio Gallery item handler (v4 compatible)
    item can be:
      - str (file path)
      - dict with key 'name'
    """
    if isinstance(item, dict) and "name" in item:
        path = item["name"]
    elif isinstance(item, str):
        path = item
    else:
        return None

    return cv2.imread(path)


# =========================
# VERIFY API
# =========================
def call_verify_api(img: np.ndarray, employee_id: str):
    if img is None:
        return "❌ No image provided", None

    b64 = img_np_to_base64(img)
    if b64 is None:
        return "❌ Failed to encode image", None

    payload = {
        "employee_id": employee_id,
        "image": b64,
    }

    try:
        r = requests.post(
            f"{API_BASE}/face/verify-image",
            json=payload,
            timeout=30,
        )
        r.raise_for_status()
        data = r.json()
    except Exception as e:
        return f"❌ API error: {e}", None

    if not data.get("detections"):
        return "❌ No face detected", None

    det = data["detections"][0]

    # Draw bounding box
    vis = img.copy()
    x1, y1, x2, y2 = map(int, det["bbox"])
    cv2.rectangle(vis, (x1, y1), (x2, y2), (0, 255, 0), 2)

    text = (
        f"Authorized : {det['authorized']}\n"
        f"Match User : {det.get('match_user')}\n"
        f"Confidence : {det['confidence']}\n"
        f"Det Score  : {det['det_score']}"
    )

    return text, vis


# =========================
# ENROLL API
# =========================
def call_enroll_api(images: List[Union[str, dict]], employee_id: str):
    if not images:
        return "❌ No images selected"

    b64_images = []

    for item in images:
        img = load_gallery_item(item)
        if img is None:
            continue

        b64 = img_np_to_base64(img)
        if b64:
            b64_images.append(b64)

    if not b64_images:
        return "❌ Failed to load images from gallery"

    payload = {
        "employee_id": employee_id,
        "images": b64_images,
    }

    try:
        r = requests.post(
            f"{API_BASE}/face/enroll",
            json=payload,
            timeout=60,
        )
        r.raise_for_status()
        data = r.json()
    except Exception as e:
        return f"❌ API error: {e}"

    return (
        "✅ ENROLL SUCCESS\n"
        f"Employee ID : {data.get('employee_id')}\n"
        f"Added       : {data.get('added')}\n"
        f"Total Files : {data.get('total', '-')}"
    )


# =========================
# GRADIO UI
# =========================
with gr.Blocks(title="Face Recognition Test (Uniface)") as demo:
    gr.Markdown("""
# 🧠 Face Recognition Frontend (TEST)
**Backend:** Uniface (RetinaFace + ArcFace)  
**API:** lifedebugger-face-recognition-sss-beta  
""")

    with gr.Tabs():

        # ================= VERIFY TAB =================
        with gr.Tab("🔍 Verify Face"):
            with gr.Row():
                with gr.Column():
                    verify_employee_id = gr.Textbox(
                        label="Employee ID",
                        value="1",
                    )
                    verify_image = gr.Image(
                        label="Input Image (Upload / Webcam)",
                        sources=["upload", "webcam"],
                        type="numpy",
                    )
                    verify_btn = gr.Button("Verify", variant="primary")

                with gr.Column():
                    verify_result = gr.Textbox(
                        label="Result",
                        lines=6,
                    )
                    verify_vis = gr.Image(
                        label="Visualization",
                        type="numpy",
                    )

            verify_btn.click(
                fn=call_verify_api,
                inputs=[verify_image, verify_employee_id],
                outputs=[verify_result, verify_vis],
            )

        # ================= ENROLL TAB =================
        with gr.Tab("➕ Enroll Face"):
            with gr.Row():
                with gr.Column():
                    enroll_employee_id = gr.Textbox(
                        label="Employee ID",
                        value="1",
                    )
                    enroll_images = gr.Gallery(
                        label="Upload Face Images (Multiple)",
                        columns=3,
                        height=250,
                    )
                    enroll_btn = gr.Button("Enroll", variant="primary")

                with gr.Column():
                    enroll_result = gr.Textbox(
                        label="Enroll Status",
                        lines=6,
                    )

            enroll_btn.click(
                fn=call_enroll_api,
                inputs=[enroll_images, enroll_employee_id],
                outputs=enroll_result,
            )

# =========================
# RUN
# =========================
if __name__ == "__main__":
    demo.launch(server_name="0.0.0.0", server_port=7860)