import os
import uuid
import shutil
import re
from datetime import datetime
from typing import Dict, List, Optional

import numpy as np
from fastapi import (
    FastAPI,
    UploadFile,
    File,
    HTTPException,
    Depends,
    Header,
    Request,
    Form,
)
from fastapi.responses import FileResponse, JSONResponse
from pydantic import BaseModel
from PIL import Image
import cv2
import logging

from bson import ObjectId
from pymongo import MongoClient
import time

logging.basicConfig(level=logging.INFO)
log = logging.getLogger("api")

from src.core import process_inpaint

# Directories (use writable space on HF Spaces)
BASE_DIR = os.environ.get("DATA_DIR", "/data")
if not os.path.isdir(BASE_DIR):
    # Fallback to /tmp if /data not available
    BASE_DIR = "/tmp"

UPLOAD_DIR = os.path.join(BASE_DIR, "uploads")
OUTPUT_DIR = os.path.join(BASE_DIR, "outputs")

os.makedirs(UPLOAD_DIR, exist_ok=True)
os.makedirs(OUTPUT_DIR, exist_ok=True)

# Optional Bearer token: set env API_TOKEN to require auth; if not set, endpoints are open
ENV_TOKEN = os.environ.get("API_TOKEN")

app = FastAPI(title="Photo Object Removal API", version="1.0.0")

# In-memory stores
file_store: Dict[str, Dict[str, str]] = {}
logs: List[Dict[str, str]] = []

MONGO_URI = "mongodb+srv://harilogicgo_db_user:pdnh6UCMsWvuTCoi@kiddoimages.k2a4nuv.mongodb.net/?appName=KiddoImages"
mongo_client = MongoClient(MONGO_URI)
mongo_db = mongo_client["object_remover"]
mongo_logs = mongo_db["api_logs"]

ADMIN_MONGO_URI = os.environ.get("MONGODB_ADMIN")
DEFAULT_CATEGORY_ID = "69368f722e46bd68ae188984"
admin_media_clicks = None


def _init_admin_mongo() -> None:
    global admin_media_clicks
    if not ADMIN_MONGO_URI:
        log.info("Admin Mongo URI not provided; media click logging disabled")
        return
    try:
        admin_client = MongoClient(ADMIN_MONGO_URI)
        # get_default_database() extracts database from connection string (e.g., /adminPanel)
        admin_db = admin_client.get_default_database()
        if admin_db is None:
            # Fallback if no database in URI
            admin_db = admin_client["admin"]
            log.warning("No database in connection string, defaulting to 'admin'")
        
        admin_media_clicks = admin_db["media_clicks"]
        log.info(
            "Admin media click logging initialized: db=%s collection=%s",
            admin_db.name,
            admin_media_clicks.name,
        )
        try:
            admin_media_clicks.drop_index("user_id_1_header_1_media_id_1")
            log.info("Dropped legacy index user_id_1_header_1_media_id_1")
        except Exception as idx_err:
            # Index drop failure is non-critical (often permission issue)
            if "Unauthorized" not in str(idx_err):
                log.info("Skipping legacy index drop: %s", idx_err)
    except Exception as err:
        log.error("Failed to init admin Mongo client: %s", err)
        admin_media_clicks = None


_init_admin_mongo()


def _admin_logging_status() -> Dict[str, object]:
    if admin_media_clicks is None:
        return {
            "enabled": False,
            "db": None,
            "collection": None,
        }
    return {
        "enabled": True,
        "db": admin_media_clicks.database.name,
        "collection": admin_media_clicks.name,
    }

def bearer_auth(authorization: Optional[str] = Header(default=None)) -> None:
    if not ENV_TOKEN:
        return
    if authorization is None or not authorization.lower().startswith("bearer "):
        raise HTTPException(status_code=401, detail="Unauthorized")
    token = authorization.split(" ", 1)[1]
    if token != ENV_TOKEN:
        raise HTTPException(status_code=403, detail="Forbidden")


class InpaintRequest(BaseModel):
    image_id: str
    mask_id: str
    invert_mask: bool = True  # True => selected/painted area is removed
    passthrough: bool = False  # If True, return the original image unchanged
    user_id: Optional[str] = None
    category_id: Optional[str] = None


class SimpleRemoveRequest(BaseModel):
    image_id: str  # Image with pink/magenta segments to remove


def _coerce_object_id(value: Optional[str]) -> ObjectId:
    if value is None:
        return ObjectId()
    value_str = str(value).strip()
    if re.fullmatch(r"[0-9a-fA-F]{24}", value_str):
        return ObjectId(value_str)
    if value_str.isdigit():
        hex_str = format(int(value_str), "x")
        if len(hex_str) > 24:
            hex_str = hex_str[-24:]
        hex_str = hex_str.rjust(24, "0")
        return ObjectId(hex_str)
    return ObjectId()


def _coerce_category_id(category_id: Optional[str]) -> ObjectId:
    raw = category_id or DEFAULT_CATEGORY_ID
    raw_str = str(raw).strip()
    if re.fullmatch(r"[0-9a-fA-F]{24}", raw_str):
        return ObjectId(raw_str)
    return _coerce_object_id(raw_str)


def log_media_click(user_id: Optional[str], category_id: Optional[str]) -> None:
    """Log to admin media_clicks collection only if user_id is provided."""
    if admin_media_clicks is None:
        return
    # Only log if user_id is provided (not None/empty)
    if not user_id or not user_id.strip():
        return
    try:
        user_obj = _coerce_object_id(user_id)
        category_obj = _coerce_category_id(category_id)
        now = datetime.utcnow()

        doc = admin_media_clicks.find_one({"userId": user_obj})
        if doc:
            categories = doc.get("categories") or []
            if any(cat.get("categoryId") == category_obj for cat in categories):
                admin_media_clicks.update_one(
                    {"_id": doc["_id"], "categories.categoryId": category_obj},
                    {
                        "$inc": {"categories.$.click_count": 1},
                        "$set": {
                            "categories.$.lastClickedAt": now,
                            "updatedAt": now,
                        },
                    },
                )
            else:
                admin_media_clicks.update_one(
                    {"_id": doc["_id"]},
                    {
                        "$push": {
                            "categories": {
                                "categoryId": category_obj,
                                "click_count": 1,
                                "lastClickedAt": now,
                            }
                        },
                        "$set": {"updatedAt": now},
                    },
                )
        else:
            admin_media_clicks.insert_one(
                {
                    "userId": user_obj,
                    "categories": [
                        {
                            "categoryId": category_obj,
                            "click_count": 1,
                            "lastClickedAt": now,
                        }
                    ],
                    "createdAt": now,
                    "updatedAt": now,
                }
            )
    except Exception as err:
        err_str = str(err)
        if "Unauthorized" in err_str or "not authorized" in err_str.lower():
            log.warning(
                "Admin media click logging failed (permissions): user lacks read/write on db=%s collection=%s. "
                "Check MongoDB user permissions.",
                admin_media_clicks.database.name,
                admin_media_clicks.name,
            )
        else:
            log.warning("Admin media click logging failed: %s", err)


@app.get("/")
def root() -> Dict[str, object]:
    return {
        "name": "Photo Object Removal API",
        "status": "ok",
        "endpoints": {
            "GET /health": "health check",
            "POST /upload-image": "form-data: image=file",
            "POST /upload-mask": "form-data: mask=file",
            "POST /inpaint": "JSON: {image_id, mask_id}",
            "POST /inpaint-multipart": "form-data: image=file, mask=file",
            "POST /remove-pink": "form-data: image=file (auto-detects pink segments and removes them)",
            "GET /download/{filename}": "download result image",
            "GET /result/{filename}": "view result image in browser",
            "GET /logs": "recent uploads/results",
        },
        "auth": "set API_TOKEN env var to require Authorization: Bearer <token> (except /health)",
    }


@app.get("/health")
def health() -> Dict[str, str]:
    return {"status": "healthy"}


@app.get("/logging-status")
def logging_status(_: None = Depends(bearer_auth)) -> Dict[str, object]:
    """Helper endpoint to verify admin media logging wiring (no secrets exposed)."""
    return _admin_logging_status()


@app.post("/upload-image")
def upload_image(image: UploadFile = File(...), _: None = Depends(bearer_auth)) -> Dict[str, str]:
    ext = os.path.splitext(image.filename)[1] or ".png"
    file_id = str(uuid.uuid4())
    stored_name = f"{file_id}{ext}"
    stored_path = os.path.join(UPLOAD_DIR, stored_name)
    with open(stored_path, "wb") as f:
        shutil.copyfileobj(image.file, f)
    file_store[file_id] = {
        "type": "image",
        "filename": image.filename,
        "stored_name": stored_name,
        "path": stored_path,
        "timestamp": datetime.utcnow().isoformat(),
    }
    logs.append({"id": file_id, "filename": image.filename, "type": "image", "timestamp": datetime.utcnow().isoformat()})
    return {"id": file_id, "filename": image.filename}


@app.post("/upload-mask")
def upload_mask(mask: UploadFile = File(...), _: None = Depends(bearer_auth)) -> Dict[str, str]:
    ext = os.path.splitext(mask.filename)[1] or ".png"
    file_id = str(uuid.uuid4())
    stored_name = f"{file_id}{ext}"
    stored_path = os.path.join(UPLOAD_DIR, stored_name)
    with open(stored_path, "wb") as f:
        shutil.copyfileobj(mask.file, f)
    file_store[file_id] = {
        "type": "mask",
        "filename": mask.filename,
        "stored_name": stored_name,
        "path": stored_path,
        "timestamp": datetime.utcnow().isoformat(),
    }
    logs.append({"id": file_id, "filename": mask.filename, "type": "mask", "timestamp": datetime.utcnow().isoformat()})
    return {"id": file_id, "filename": mask.filename}


def _load_rgba_image(path: str) -> Image.Image:
    img = Image.open(path)
    return img.convert("RGBA")


def _load_rgba_mask_from_image(img: Image.Image) -> np.ndarray:
    """
    Convert mask image to RGBA format (black/white mask).
    Standard convention: white (255) = area to remove, black (0) = area to keep
    Returns RGBA with white in RGB channels where removal is needed, alpha=255
    """
    if img.mode != "RGBA":
        # For RGB/Grayscale masks: white (value>128) = remove, black (value<=128) = keep
        gray = img.convert("L")
        arr = np.array(gray)
        # Create proper black/white mask: white pixels (>128) = remove, black (<=128) = keep
        mask_bw = np.where(arr > 128, 255, 0).astype(np.uint8)
        
        rgba = np.zeros((img.height, img.width, 4), dtype=np.uint8)
        rgba[:, :, 0] = mask_bw  # R
        rgba[:, :, 1] = mask_bw  # G
        rgba[:, :, 2] = mask_bw  # B
        rgba[:, :, 3] = 255  # Fully opaque
        log.info(f"Loaded {img.mode} mask: {int((mask_bw > 0).sum())} white pixels (to remove)")
        return rgba
    
    # For RGBA: check if alpha channel is meaningful
    arr = np.array(img)
    alpha = arr[:, :, 3]
    rgb = arr[:, :, :3]
    
    # If alpha is mostly opaque everywhere (mean > 200), treat RGB channels as mask values
    if alpha.mean() > 200:
        # Use RGB to determine mask: white/bright in RGB = remove
        gray = cv2.cvtColor(rgb, cv2.COLOR_RGB2GRAY)
        # Also detect magenta specifically
        magenta = np.all(rgb == [255, 0, 255], axis=2).astype(np.uint8) * 255
        mask_bw = np.maximum(np.where(gray > 128, 255, 0).astype(np.uint8), magenta)
        
        rgba = arr.copy()
        rgba[:, :, 0] = mask_bw  # R
        rgba[:, :, 1] = mask_bw  # G
        rgba[:, :, 2] = mask_bw  # B
        rgba[:, :, 3] = 255  # Fully opaque
        log.info(f"Loaded RGBA mask (RGB-based): {int((mask_bw > 0).sum())} white pixels (to remove)")
        return rgba
    
    # Alpha channel encodes the mask - convert to RGB-based
    # Transparent areas (alpha < 128) = remove, Opaque areas = keep
    mask_bw = np.where(alpha < 128, 255, 0).astype(np.uint8)
    rgba = arr.copy()
    rgba[:, :, 0] = mask_bw
    rgba[:, :, 1] = mask_bw
    rgba[:, :, 2] = mask_bw
    rgba[:, :, 3] = 255
    log.info(f"Loaded RGBA mask (alpha-based): {int((mask_bw > 0).sum())} white pixels (to remove)")
    return rgba

@app.post("/inpaint")
def inpaint(req: InpaintRequest, _: None = Depends(bearer_auth)) -> Dict[str, str]:
    start_time = time.time()
    status = "success"
    error_msg = None
    output_name = None

    try:
        if req.image_id not in file_store or file_store[req.image_id]["type"] != "image":
            raise HTTPException(status_code=404, detail="image_id not found")

        if req.mask_id not in file_store or file_store[req.mask_id]["type"] != "mask":
            raise HTTPException(status_code=404, detail="mask_id not found")

        img_rgba = _load_rgba_image(file_store[req.image_id]["path"])
        mask_img = Image.open(file_store[req.mask_id]["path"])
        mask_rgba = _load_rgba_mask_from_image(mask_img)

        if req.passthrough:
            result = np.array(img_rgba.convert("RGB"))
        else:
            result = process_inpaint(
                np.array(img_rgba), 
                mask_rgba, 
                invert_mask=req.invert_mask
            )

        output_name = f"output_{uuid.uuid4().hex}.png"
        output_path = os.path.join(OUTPUT_DIR, output_name)

        Image.fromarray(result).save(
            output_path, "PNG", optimize=False, compress_level=1
        )

        log_media_click(req.user_id, req.category_id)
        return {"result": output_name}

    except Exception as e:
        status = "fail"
        error_msg = str(e)
        raise

    finally:
        end_time = time.time()
        response_time_ms = (end_time - start_time) * 1000

        log_doc = {
            "input_image_id": req.image_id,
            "input_mask_id": req.mask_id,
            "output_id": output_name,
            "status": status,
            "timestamp": datetime.utcnow(),
            "ts": int(time.time()),
            "response_time_ms": response_time_ms
        }

        if error_msg:
            log_doc["error"] = error_msg

        try:
            mongo_logs.insert_one(log_doc)
        except Exception as mongo_err:
            log.error(f"Mongo log insert failed: {mongo_err}")

# @app.post("/inpaint")
# def inpaint(req: InpaintRequest, _: None = Depends(bearer_auth)) -> Dict[str, str]:
#     if req.image_id not in file_store or file_store[req.image_id]["type"] != "image":
#         raise HTTPException(status_code=404, detail="image_id not found")
#     if req.mask_id not in file_store or file_store[req.mask_id]["type"] != "mask":
#         raise HTTPException(status_code=404, detail="mask_id not found")

#     img_rgba = _load_rgba_image(file_store[req.image_id]["path"])
#     mask_img = Image.open(file_store[req.mask_id]["path"])  # may be RGB/gray/RGBA
#     mask_rgba = _load_rgba_mask_from_image(mask_img)

#     # Debug: check mask before processing
#     white_pixels = int((mask_rgba[:,:,0] > 128).sum())
#     log.info(f"Inpaint request: mask has {white_pixels} white pixels, invert_mask={req.invert_mask}")

#     if req.passthrough:
#         result = np.array(img_rgba.convert("RGB"))
#     else:
#         result = process_inpaint(np.array(img_rgba), mask_rgba, invert_mask=req.invert_mask)
#     result_name = f"output_{uuid.uuid4().hex}.png"
#     result_path = os.path.join(OUTPUT_DIR, result_name)
#     Image.fromarray(result).save(result_path, "PNG", optimize=False, compress_level=1)

#     logs.append({"result": result_name, "timestamp": datetime.utcnow().isoformat()})
#     return {"result": result_name}


@app.post("/inpaint-url")
def inpaint_url(req: InpaintRequest, request: Request, _: None = Depends(bearer_auth)) -> Dict[str, str]:
    """Same as /inpaint but returns a JSON with a public download URL instead of image bytes."""
    start_time = time.time()
    status = "success"
    error_msg = None
    result_name = None

    try:
        if req.image_id not in file_store or file_store[req.image_id]["type"] != "image":
            raise HTTPException(status_code=404, detail="image_id not found")
        if req.mask_id not in file_store or file_store[req.mask_id]["type"] != "mask":
            raise HTTPException(status_code=404, detail="mask_id not found")

        img_rgba = _load_rgba_image(file_store[req.image_id]["path"])
        mask_img = Image.open(file_store[req.mask_id]["path"])  # may be RGB/gray/RGBA
        mask_rgba = _load_rgba_mask_from_image(mask_img)

        if req.passthrough:
            result = np.array(img_rgba.convert("RGB"))
        else:
            result = process_inpaint(np.array(img_rgba), mask_rgba, invert_mask=req.invert_mask)
        result_name = f"output_{uuid.uuid4().hex}.png"
        result_path = os.path.join(OUTPUT_DIR, result_name)
        Image.fromarray(result).save(result_path, "PNG", optimize=False, compress_level=1)

        url = str(request.url_for("download_file", filename=result_name))
        logs.append({"result": result_name, "url": url, "timestamp": datetime.utcnow().isoformat()})
        log_media_click(req.user_id, req.category_id)
        return {"result": result_name, "url": url}
    except Exception as e:
        status = "fail"
        error_msg = str(e)
        raise
    finally:
        # Always log to regular MongoDB (mandatory)
        end_time = time.time()
        response_time_ms = (end_time - start_time) * 1000
        log_doc = {
            "input_image_id": req.image_id,
            "input_mask_id": req.mask_id,
            "output_id": result_name,
            "status": status,
            "timestamp": datetime.utcnow(),
            "ts": int(time.time()),
            "response_time_ms": response_time_ms,
        }
        if error_msg:
            log_doc["error"] = error_msg
        try:
            mongo_logs.insert_one(log_doc)
        except Exception as mongo_err:
            log.error("Mongo log insert failed: %s", mongo_err)


@app.post("/inpaint-multipart")
def inpaint_multipart(
    image: UploadFile = File(...),
    mask: UploadFile = File(...),
    request: Request = None,
    invert_mask: bool = True,
    mask_is_painted: bool = False,  # if True, mask file is the painted-on image (e.g., black strokes on original)
    passthrough: bool = False,
    user_id: Optional[str] = Form(None),
    category_id: Optional[str] = Form(None),
    _: None = Depends(bearer_auth),
) -> Dict[str, str]:
    start_time = time.time()
    status = "success"
    error_msg = None
    result_name = None
    
    try:
        # Load in-memory
        img = Image.open(image.file).convert("RGBA")
        m = Image.open(mask.file).convert("RGBA")

        if passthrough:
            # Just echo the input image, ignore mask
            result = np.array(img.convert("RGB"))
            result_name = f"output_{uuid.uuid4().hex}.png"
            result_path = os.path.join(OUTPUT_DIR, result_name)
            Image.fromarray(result).save(result_path, "PNG", optimize=False, compress_level=1)

            url: Optional[str] = None
            try:
                if request is not None:
                    url = str(request.url_for("download_file", filename=result_name))
            except Exception:
                url = None

            entry: Dict[str, str] = {"result": result_name, "timestamp": datetime.utcnow().isoformat()}
            if url:
                entry["url"] = url
            logs.append(entry)
            resp: Dict[str, str] = {"result": result_name}
            if url:
                resp["url"] = url
            log_media_click(user_id, category_id)
            return resp

        if mask_is_painted:
            # Auto-detect pink/magenta paint and convert to black/white mask
            # White pixels = areas to remove, Black pixels = areas to keep
            log.info("Auto-detecting pink/magenta paint from uploaded image...")
            
            m_rgb = cv2.cvtColor(np.array(m), cv2.COLOR_RGBA2RGB)
            
            # Detect pink/magenta using fixed RGB bounds (same as /remove-pink)
            lower = np.array([150, 0, 100], dtype=np.uint8)
            upper = np.array([255, 120, 255], dtype=np.uint8)
            magenta_detected = (
                (m_rgb[:, :, 0] >= lower[0]) & (m_rgb[:, :, 0] <= upper[0]) &
                (m_rgb[:, :, 1] >= lower[1]) & (m_rgb[:, :, 1] <= upper[1]) &
                (m_rgb[:, :, 2] >= lower[2]) & (m_rgb[:, :, 2] <= upper[2])
            ).astype(np.uint8) * 255
            
            # Method 2: Also check if original image was provided to find differences
            if img is not None:
                img_rgb = cv2.cvtColor(np.array(img), cv2.COLOR_RGBA2RGB)
                if img_rgb.shape == m_rgb.shape:
                    diff = cv2.absdiff(img_rgb, m_rgb)
                    gray_diff = cv2.cvtColor(diff, cv2.COLOR_RGB2GRAY)
                    # Any significant difference (>50) could be paint
                    diff_mask = (gray_diff > 50).astype(np.uint8) * 255
                    # Combine with magenta detection
                    binmask = cv2.bitwise_or(magenta_detected, diff_mask)
                else:
                    binmask = magenta_detected
            else:
                # No original image provided, use magenta detection only
                binmask = magenta_detected
            
            # Clean up the mask: remove noise and fill small holes
            kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
            # Close small gaps in the mask
            binmask = cv2.morphologyEx(binmask, cv2.MORPH_CLOSE, kernel, iterations=2)
            # Remove small noise
            binmask = cv2.morphologyEx(binmask, cv2.MORPH_OPEN, kernel, iterations=1)
            
            nonzero = int((binmask > 0).sum())
            log.info("Pink/magenta paint detected: %d pixels marked for removal (white)", nonzero)
            
            # If very few pixels detected, assume the user may already be providing a BW mask
            # and proceed without forcing strict detection
            
            if nonzero < 50:
                log.error("CRITICAL: Could not detect pink/magenta paint! Returning original image.")
                result = np.array(img.convert("RGB")) if img else np.array(m.convert("RGB"))
                result_name = f"output_{uuid.uuid4().hex}.png"
                result_path = os.path.join(OUTPUT_DIR, result_name)
                Image.fromarray(result).save(result_path, "PNG", optimize=False, compress_level=1)
                return {"result": result_name, "error": "pink/magenta paint detection failed - very few pixels detected"}
            
            # Create binary mask: Pink pixels → white (255), Everything else → black (0)
            # Encode in RGBA format for process_inpaint
            # process_inpaint does: mask = 255 - mask[:,:,3]
            # So: alpha=0 (transparent/pink) → becomes 255 (white/remove)
            #     alpha=255 (opaque/keep) → becomes 0 (black/keep)
            mask_rgba = np.zeros((binmask.shape[0], binmask.shape[1], 4), dtype=np.uint8)
            mask_rgba[:, :, 0] = binmask  # R: white where pink (for visualization)
            mask_rgba[:, :, 1] = binmask  # G: white where pink
            mask_rgba[:, :, 2] = binmask  # B: white where pink
            # Alpha: invert so pink areas get alpha=0 → will become white after 255-alpha
            mask_rgba[:, :, 3] = 255 - binmask
            
            log.info("Successfully created binary mask: %d pink pixels → white (255), %d pixels → black (0)",
                     nonzero, binmask.shape[0] * binmask.shape[1] - nonzero)
        else:
            mask_rgba = _load_rgba_mask_from_image(m)

        # When mask_is_painted=true, we encode pink as alpha=0, so process_inpaint's default invert_mask=True works correctly
        actual_invert = invert_mask  # Use default True for painted masks
        log.info("Using invert_mask=%s (mask_is_painted=%s)", actual_invert, mask_is_painted)
        
        result = process_inpaint(np.array(img), mask_rgba, invert_mask=actual_invert)
        result_name = f"output_{uuid.uuid4().hex}.png"
        result_path = os.path.join(OUTPUT_DIR, result_name)
        Image.fromarray(result).save(result_path, "PNG", optimize=False, compress_level=1)

        url: Optional[str] = None
        try:
            if request is not None:
                url = str(request.url_for("download_file", filename=result_name))
        except Exception:
            url = None

        entry: Dict[str, str] = {"result": result_name, "timestamp": datetime.utcnow().isoformat()}
        if url:
            entry["url"] = url
        logs.append(entry)
        resp: Dict[str, str] = {"result": result_name}
        if url:
            resp["url"] = url
        log_media_click(user_id, category_id)
        return resp
    except Exception as e:
        status = "fail"
        error_msg = str(e)
        raise
    finally:
        # Always log to regular MongoDB (mandatory)
        end_time = time.time()
        response_time_ms = (end_time - start_time) * 1000
        log_doc = {
            "endpoint": "inpaint-multipart",
            "output_id": result_name,
            "status": status,
            "timestamp": datetime.utcnow(),
            "ts": int(time.time()),
            "response_time_ms": response_time_ms,
        }
        if error_msg:
            log_doc["error"] = error_msg
        try:
            mongo_logs.insert_one(log_doc)
        except Exception as mongo_err:
            log.error("Mongo log insert failed: %s", mongo_err)


@app.post("/remove-pink")
def remove_pink_segments(
    image: UploadFile = File(...),
    request: Request = None,
    user_id: Optional[str] = Form(None),
    category_id: Optional[str] = Form(None),
    _: None = Depends(bearer_auth),
) -> Dict[str, str]:
    """
    Simple endpoint: upload an image with pink/magenta segments to remove.
    - Pink/Magenta segments → automatically removed (white in mask)
    - Everything else → automatically kept (black in mask)
    Just paint pink/magenta on areas you want to remove, upload the image, and it works!
    """
    start_time = time.time()
    status = "success"
    error_msg = None
    result_name = None
    
    try:
        log.info(f"Simple remove-pink: processing image {image.filename}")
        
        # Load the image (with pink paint on it)
        img = Image.open(image.file).convert("RGBA")
        img_rgb = cv2.cvtColor(np.array(img), cv2.COLOR_RGBA2RGB)
        
        # Auto-detect pink/magenta segments to remove
        # Pink/Magenta → white in mask (remove)
        # Everything else (natural image colors, including dark areas) → black in mask (keep)
        
        # Detect pink/magenta using fixed RGB bounds per requested logic
        lower = np.array([150, 0, 100], dtype=np.uint8)
        upper = np.array([255, 120, 255], dtype=np.uint8)
        binmask = (
            (img_rgb[:, :, 0] >= lower[0]) & (img_rgb[:, :, 0] <= upper[0]) &
            (img_rgb[:, :, 1] >= lower[1]) & (img_rgb[:, :, 1] <= upper[1]) &
            (img_rgb[:, :, 2] >= lower[2]) & (img_rgb[:, :, 2] <= upper[2])
        ).astype(np.uint8) * 255
        
        # Clean up the pink mask
        kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
        binmask = cv2.morphologyEx(binmask, cv2.MORPH_CLOSE, kernel, iterations=2)
        binmask = cv2.morphologyEx(binmask, cv2.MORPH_OPEN, kernel, iterations=1)
        
        nonzero = int((binmask > 0).sum())
        total_pixels = binmask.shape[0] * binmask.shape[1]
        log.info(f"Detected {nonzero} pink pixels ({100*nonzero/total_pixels:.2f}% of image) to remove")
        
        # Debug: log bounds used
        log.info("Pink detection bounds used: lower=[150,0,100], upper=[255,120,255]")
        
        if nonzero < 50:
            log.error("No pink segments detected! Returning original image.")
            result = np.array(img.convert("RGB"))
            result_name = f"output_{uuid.uuid4().hex}.png"
            result_path = os.path.join(OUTPUT_DIR, result_name)
            Image.fromarray(result).save(result_path, "PNG", optimize=False, compress_level=1)
            return {
                "result": result_name,
                "error": "No pink/magenta segments detected. Please paint areas to remove with magenta/pink color (RGB 255,0,255)."
            }
        
        # Create binary mask: Pink pixels → white (255), Everything else → black (0)
        # Encode in RGBA format that process_inpaint expects
        # process_inpaint does: mask = 255 - mask[:,:,3]
        # So: alpha=0 (transparent/pink) → becomes 255 (white/remove)
        #     alpha=255 (opaque/keep) → becomes 0 (black/keep)
        mask_rgba = np.zeros((binmask.shape[0], binmask.shape[1], 4), dtype=np.uint8)
        # RGB channels don't matter for process_inpaint, but set them to white where pink for visualization
        mask_rgba[:, :, 0] = binmask  # R: white where pink
        mask_rgba[:, :, 1] = binmask  # G: white where pink  
        mask_rgba[:, :, 2] = binmask  # B: white where pink
        # Alpha: 0 (transparent) where pink → will become white after 255-alpha
        #        255 (opaque) everywhere else → will become black after 255-alpha
        mask_rgba[:, :, 3] = 255 - binmask  # Invert: pink areas get alpha=0, rest get alpha=255
        
        # Verify mask encoding
        alpha_zero_count = int((mask_rgba[:,:,3] == 0).sum())
        alpha_255_count = int((mask_rgba[:,:,3] == 255).sum())
        total_pixels = binmask.shape[0] * binmask.shape[1]
        log.info(f"Mask encoding: {alpha_zero_count} pixels with alpha=0 (pink), {alpha_255_count} pixels with alpha=255 (keep)")
        log.info(f"After 255-alpha conversion: {alpha_zero_count} will become white (255/remove), {alpha_255_count} will become black (0/keep)")
        
        # IMPORTANT: We need to use the ORIGINAL image WITHOUT pink paint for inpainting!
        # Remove pink from the original image before processing
        # Create a clean version: where pink was detected, keep original image colors
        img_clean = np.array(img.convert("RGBA"))
        # Where pink is detected, we want to inpaint, so we can leave it (or blend it out)
        # Actually, the model will inpaint over those areas, so we can pass the original
        # But for better results, we might want to remove the pink overlay first
        
        # Process with invert_mask=True (default) because process_inpaint expects alpha=0 for removal
        log.info(f"Starting inpainting process...")
        result = process_inpaint(img_clean, mask_rgba, invert_mask=True)
        log.info(f"Inpainting complete, result shape: {result.shape}")
        result_name = f"output_{uuid.uuid4().hex}.png"
        result_path = os.path.join(OUTPUT_DIR, result_name)
        Image.fromarray(result).save(result_path, "PNG", optimize=False, compress_level=1)
        
        url: Optional[str] = None
        try:
            if request is not None:
                url = str(request.url_for("download_file", filename=result_name))
        except Exception:
            url = None
        
        logs.append({
            "result": result_name,
            "filename": image.filename,
            "pink_pixels": nonzero,
            "timestamp": datetime.utcnow().isoformat()
        })
        
        resp: Dict[str, str] = {"result": result_name, "pink_segments_detected": str(nonzero)}
        if url:
            resp["url"] = url
        log_media_click(user_id, category_id)
        return resp
    except Exception as e:
        status = "fail"
        error_msg = str(e)
        raise
    finally:
        # Always log to regular MongoDB (mandatory)
        end_time = time.time()
        response_time_ms = (end_time - start_time) * 1000
        log_doc = {
            "endpoint": "remove-pink",
            "output_id": result_name,
            "status": status,
            "timestamp": datetime.utcnow(),
            "ts": int(time.time()),
            "response_time_ms": response_time_ms,
        }
        if error_msg:
            log_doc["error"] = error_msg
        try:
            mongo_logs.insert_one(log_doc)
        except Exception as mongo_err:
            log.error("Mongo log insert failed: %s", mongo_err)


@app.get("/download/{filename}")
def download_file(filename: str):
    path = os.path.join(OUTPUT_DIR, filename)
    if not os.path.isfile(path):
        raise HTTPException(status_code=404, detail="file not found")
    return FileResponse(path)


@app.get("/result/{filename}")
def view_result(filename: str):
    """View result image directly in browser (same as download but with proper content-type for viewing)"""
    path = os.path.join(OUTPUT_DIR, filename)
    if not os.path.isfile(path):
        raise HTTPException(status_code=404, detail="file not found")
    return FileResponse(path, media_type="image/png")


@app.get("/logs")
def get_logs(_: None = Depends(bearer_auth)) -> JSONResponse:
    return JSONResponse(content=logs)