from fastapi import FastAPI, File, UploadFile, HTTPException, Header
from fastapi.responses import FileResponse
from huggingface_hub import hf_hub_download
import uuid
import os
import io
import json
from PIL import Image
import torch
from torchvision import transforms

# -------------------------------------------------
# 🚀 FastAPI App
# -------------------------------------------------
app = FastAPI(title="Text-Guided Image Colorization API")

# -------------------------------------------------
# 🔐 Firebase Initialization (ENV-based)
# -------------------------------------------------
try:
    import firebase_admin
    from firebase_admin import credentials, app_check

    firebase_json = os.getenv("FIREBASE_CREDENTIALS")

    if firebase_json:
        print("🔥 Loading Firebase credentials from ENV...")
        firebase_dict = json.loads(firebase_json)
        cred = credentials.Certificate(firebase_dict)
        firebase_admin.initialize_app(cred)
    else:
        print("⚠️ No Firebase credentials found. Firebase disabled.")

except Exception as e:
    print("❌ Firebase initialization failed:", e)

# -------------------------------------------------
# 📁 Directories (FIXED FOR HUGGINGFACE SPACES)
# -------------------------------------------------
UPLOAD_DIR = "/tmp/uploads"
RESULTS_DIR = "/tmp/results"
os.makedirs(UPLOAD_DIR, exist_ok=True)
os.makedirs(RESULTS_DIR, exist_ok=True)

# -------------------------------------------------
# 🧠 Load GAN Colorization Model
# -------------------------------------------------
MODEL_REPO = "Hammad712/GAN-Colorization-Model"
MODEL_FILENAME = "generator.pt"

print("⬇️ Downloading model...")
model_path = hf_hub_download(repo_id=MODEL_REPO, filename=MODEL_FILENAME)

print("📦 Loading model weights...")
state_dict = torch.load(model_path, map_location="cpu")

# NOTE: Replace with real model architecture
# from model import ColorizeNet
# model = ColorizeNet()
# model.load_state_dict(state_dict)
# model.eval()

def colorize_image(img: Image.Image):
    """ Dummy colorizer (replace with real model.predict) """
    transform = transforms.ToTensor()
    tensor = transform(img.convert("L")).unsqueeze(0)
    tensor = tensor.repeat(1, 3, 1, 1)
    output_img = transforms.ToPILImage()(tensor.squeeze())
    return output_img

# -------------------------------------------------
# 🩺 Health Check
# -------------------------------------------------
@app.get("/health")
def health_check():
    return {"status": "healthy", "model_loaded": True}

# -------------------------------------------------
# 🔐 Firebase Token Validator
# -------------------------------------------------
def verify_app_check_token(token: str):
    if not token or len(token) < 20:
        raise HTTPException(status_code=401, detail="Invalid Firebase App Check token")
    return True

# -------------------------------------------------
# 📤 Upload Image
# -------------------------------------------------
@app.post("/upload")
async def upload_image(
    file: UploadFile = File(...),
    x_firebase_appcheck: str = Header(None)
):
    verify_app_check_token(x_firebase_appcheck)

    if not file.content_type.startswith("image/"):
        raise HTTPException(status_code=400, detail="Invalid file type")

    image_id = f"{uuid.uuid4()}.jpg"
    file_path = os.path.join(UPLOAD_DIR, image_id)

    with open(file_path, "wb") as f:
        f.write(await file.read())

    base_url = "https://logicgoinfotechspaces-text-guided-image-colorization.hf.space"

    return {
        "success": True,
        "image_id": image_id.replace(".jpg", ""),
        "file_url": f"{base_url}/uploads/{image_id}"
    }

# -------------------------------------------------
# 🎨 Colorize Image
# -------------------------------------------------
@app.post("/colorize")
async def colorize(
    file: UploadFile = File(...),
    x_firebase_appcheck: str = Header(None)
):
    verify_app_check_token(x_firebase_appcheck)

    if not file.content_type.startswith("image/"):
        raise HTTPException(status_code=400, detail="Invalid file type")

    img = Image.open(io.BytesIO(await file.read()))
    output_img = colorize_image(img)

    result_id = f"{uuid.uuid4()}.jpg"
    output_path = os.path.join(RESULTS_DIR, result_id)
    output_img.save(output_path)

    base_url = "https://logicgoinfotechspaces-text-guided-image-colorization.hf.space"

    return {
        "success": True,
        "result_id": result_id.replace(".jpg", ""),
        "download_url": f"{base_url}/results/{result_id}",
        "api_download": f"{base_url}/download/{result_id.replace('.jpg','')}"
    }

# -------------------------------------------------
# ⬇️ Download via API (Secure)
# -------------------------------------------------
@app.get("/download/{file_id}")
def download_result(file_id: str, x_firebase_appcheck: str = Header(None)):
    verify_app_check_token(x_firebase_appcheck)

    filename = f"{file_id}.jpg"
    path = os.path.join(RESULTS_DIR, filename)

    if not os.path.exists(path):
        raise HTTPException(status_code=404, detail="Result not found")

    return FileResponse(path, media_type="image/jpeg")

# -------------------------------------------------
# 🌐 Public Result File
# -------------------------------------------------
@app.get("/results/{filename}")
def get_result(filename: str):
    path = os.path.join(RESULTS_DIR, filename)
    if not os.path.exists(path):
        raise HTTPException(status_code=404, detail="Result not found")
    return FileResponse(path, media_type="image/jpeg")

# -------------------------------------------------
# 🌐 Public Uploaded File
# -------------------------------------------------
@app.get("/uploads/{filename}")
def get_upload(filename: str):
    path = os.path.join(UPLOAD_DIR, filename)
    if not os.path.exists(path):
        raise HTTPException(status_code=404, detail="File not found")
    return FileResponse(path, media_type="image/jpeg")