import os
import threading
import tempfile
import urllib.request
from fastapi import FastAPI, UploadFile, File, Form, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
import psycopg
from pgvector.psycopg import register_vector
import numpy as np
import uuid
import io
from PIL import Image
from deepface import DeepFace
from datetime import date
from dotenv import load_dotenv

load_dotenv()

app = FastAPI(title="VisionAttend API")

# Configure CORS
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],  # In production, replace with frontend URL
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

DATABASE_URL = os.getenv("DATABASE_URL")
FACENET_WEIGHTS_PATH = os.path.join(
    os.path.expanduser("~"),
    ".deepface",
    "weights",
    "facenet_weights.h5",
)
FACENET_WEIGHTS_URL = "https://huggingface.co/junjiang/GestureFace/resolve/main/facenet_weights.h5"
FACENET_MIN_BYTES = 80 * 1024 * 1024
_facenet_model_lock = threading.Lock()
_facenet_model_ready = False

class MatchResponse(BaseModel):
    message: str
    student_name: str
    roll_number: str

from psycopg_pool import ConnectionPool

def configure_conn(conn):
    register_vector(conn)

# By using a ConnectionPool, we keep the TCP connection alive to Neon.
# This eliminates the ~6-8 second TLS/SSL handshake delay on every request.
db_pool = None
if DATABASE_URL:
    try:
        db_pool = ConnectionPool(
            conninfo=DATABASE_URL, 
            configure=configure_conn, 
            min_size=1, 
            max_size=5,
            timeout=30.0
        )
    except Exception as e:
        print(f"WARNING: Failed to initialize database pool: {e}")
else:
    print("WARNING: DATABASE_URL is not set. Database connections will fail.")

def get_db_connection():
    if not db_pool:
        raise HTTPException(status_code=500, detail="Database is not configured or failed to connect. Please set DATABASE_URL in Hugging Face Spaces Settings -> Variables and secrets.")
    return db_pool.connection()

def ensure_facenet_weights_file() -> None:
    weights_dir = os.path.dirname(FACENET_WEIGHTS_PATH)
    os.makedirs(weights_dir, exist_ok=True)

    if os.path.exists(FACENET_WEIGHTS_PATH) and os.path.getsize(FACENET_WEIGHTS_PATH) >= FACENET_MIN_BYTES:
        return

    with tempfile.NamedTemporaryFile(delete=False, dir=weights_dir, suffix=".tmp") as temp_file:
        temp_path = temp_file.name

    try:
        with urllib.request.urlopen(FACENET_WEIGHTS_URL, timeout=120) as response, open(temp_path, "wb") as output_file:
            while True:
                chunk = response.read(1024 * 1024)
                if not chunk:
                    break
                output_file.write(chunk)

        if os.path.getsize(temp_path) < FACENET_MIN_BYTES:
            raise ValueError("Downloaded FaceNet weights file is incomplete.")

        os.replace(temp_path, FACENET_WEIGHTS_PATH)
    finally:
        if os.path.exists(temp_path):
            os.remove(temp_path)

def ensure_facenet_model_loaded() -> None:
    global _facenet_model_ready

    if _facenet_model_ready:
        return

    with _facenet_model_lock:
        if _facenet_model_ready:
            return

        try:
            ensure_facenet_weights_file()
            DeepFace.build_model("Facenet")
            _facenet_model_ready = True
            return
        except Exception as first_error:
            if os.path.exists(FACENET_WEIGHTS_PATH):
                try:
                    os.remove(FACENET_WEIGHTS_PATH)
                except OSError:
                    raise first_error

            ensure_facenet_weights_file()
            DeepFace.build_model("Facenet")
            _facenet_model_ready = True

def extract_face_embedding(file_bytes: bytes) -> tuple[list[float], str]:
    try:
        ensure_facenet_model_loaded()
        image = Image.open(io.BytesIO(file_bytes)).convert("RGB")
        img_array = np.array(image)
        
        results = DeepFace.represent(
            img_path=img_array, 
            enforce_detection=True, 
            model_name="Facenet",
            detector_backend="opencv"
        )
        
        if len(results) == 0:
            raise ValueError("No face detected.")
        if len(results) > 1:
            raise ValueError("Multiple faces detected. Please show only one face.")
            
        embedding = results[0]["embedding"]
        return embedding, "success"
    except ValueError as ve:
        return [], str(ve)
    except Exception as e:
        return [], f"An error occurred during face extraction: {str(e)}"

@app.post("/api/register")
async def register_student(
    name: str = Form(...),
    roll_number: str = Form(...),
    image: UploadFile = File(...)
):
    file_bytes = await image.read()
    
    embedding, error = extract_face_embedding(file_bytes)
    if not embedding:
        raise HTTPException(status_code=400, detail=error)
        
    try:
        with get_db_connection() as conn:
            with conn.cursor() as cur:
                cur.execute("SELECT id FROM students WHERE roll_number = %s", (roll_number,))
                if cur.fetchone():
                    raise HTTPException(status_code=400, detail="Student with this roll number already exists.")
                    
                cur.execute("""
                    SELECT name, roll_number, (face_encoding <=> %s::vector) AS distance
                    FROM students
                    ORDER BY distance ASC
                    LIMIT 1;
                """, (str(embedding),))
                
                result = cur.fetchone()
                if result:
                    existing_name, existing_roll_number, distance = result
                    if distance <= 0.40:
                        raise HTTPException(status_code=400, detail=f"Face already registered to {existing_name} under roll number {existing_roll_number}.")
                    
                cur.execute(
                    "INSERT INTO students (name, roll_number, face_encoding) VALUES (%s, %s, %s) RETURNING id",
                    (name, roll_number, str(embedding))
                )
                student_id = cur.fetchone()[0]
                conn.commit()
                
        return {"message": "Student registered successfully", "student_id": student_id}
    except HTTPException:
        raise
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Database error: {str(e)}")


@app.post("/api/recognize", response_model=MatchResponse)
async def recognize_student(image: UploadFile = File(...)):
    file_bytes = await image.read()
    
    embedding, error = extract_face_embedding(file_bytes)
    if not embedding:
        raise HTTPException(status_code=400, detail=error)
        
    try:
        with get_db_connection() as conn:
            with conn.cursor() as cur:
                cur.execute("""
                    SELECT id, name, roll_number, (face_encoding <=> %s::vector) AS distance
                    FROM students
                    ORDER BY distance ASC
                    LIMIT 1;
                """, (str(embedding),))
                
                result = cur.fetchone()
                
                if not result:
                    raise HTTPException(status_code=404, detail="No match found in database.")
                    
                student_id, name, roll_number, distance = result
                print(f"Discovered {name} with distance {distance}")
                
                if distance > 0.40: # Threshold for Facenet
                    raise HTTPException(status_code=404, detail="Face recognized but distance exceeds confidence threshold.")
                    
                cur.execute("""
                    SELECT id FROM attendance 
                    WHERE student_id = %s AND timestamp::date = %s
                """, (student_id, date.today()))
                
                if not cur.fetchone():
                    cur.execute(
                        "INSERT INTO attendance (student_id, status) VALUES (%s, 'Present')",
                        (student_id,)
                    )
                    conn.commit()
                    message = "Attendance marked."
                else:
                    message = "Attendance already marked for today."
                    
                return MatchResponse(message=message, student_name=name, roll_number=roll_number)
                
    except HTTPException:
        raise
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Database error: {str(e)}")

@app.get("/api/attendance")
async def get_attendance(date_filter: str = None):
    try:
        with get_db_connection() as conn:
            with conn.cursor() as cur:
                if date_filter:
                    cur.execute("""
                        SELECT s.id, s.name, s.roll_number, a.timestamp, 
                               CASE WHEN a.id IS NOT NULL THEN 'Present' ELSE 'Absent' END as status,
                               s.id as student_id
                        FROM students s
                        LEFT JOIN attendance a ON s.id = a.student_id AND DATE(a.timestamp) = %s
                        ORDER BY 
                            CASE WHEN a.id IS NOT NULL THEN 0 ELSE 1 END,
                            s.name ASC
                        LIMIT 100;
                    """, (date_filter,))
                    rows = cur.fetchall()
                    logs = [
                        {
                            "id": str(row[0]),
                            "name": row[1],
                            "roll_number": row[2],
                            "timestamp": row[3],
                            "status": row[4],
                            "student_id": str(row[5])
                        } for row in rows
                    ]
                else:
                    cur.execute("""
                        SELECT a.id, s.name, s.roll_number, a.timestamp, a.status, s.id as student_id
                        FROM attendance a
                        JOIN students s ON a.student_id = s.id
                        ORDER BY a.timestamp DESC
                        LIMIT 100;
                    """)
                    rows = cur.fetchall()
                    logs = [
                        {
                            "id": str(row[0]),
                            "name": row[1],
                            "roll_number": row[2],
                            "timestamp": row[3],
                            "status": row[4],
                            "student_id": str(row[5])
                        } for row in rows
                    ]
                return {"logs": logs}
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Database error: {str(e)}")

class StudentUpdate(BaseModel):
    name: str
    roll_number: str

@app.put("/api/students/{student_id}")
async def update_student(student_id: uuid.UUID, data: StudentUpdate):
    try:
        with get_db_connection() as conn:
            with conn.cursor() as cur:
                cur.execute("SELECT id FROM students WHERE roll_number = %s AND id != %s", (data.roll_number, student_id))
                if cur.fetchone():
                    raise HTTPException(status_code=400, detail="Another student with this roll number already exists.")
                
                cur.execute(
                    "UPDATE students SET name = %s, roll_number = %s WHERE id = %s RETURNING id",
                    (data.name, data.roll_number, student_id)
                )
                if not cur.fetchone():
                    raise HTTPException(status_code=404, detail="Student not found.")
                conn.commit()
                return {"message": "Student updated successfully."}
    except HTTPException:
        raise
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Database error: {str(e)}")

@app.delete("/api/students/{student_id}")
async def delete_student(student_id: uuid.UUID):
    try:
        with get_db_connection() as conn:
            with conn.cursor() as cur:
                cur.execute("DELETE FROM students WHERE id = %s RETURNING id", (student_id,))
                if not cur.fetchone():
                    raise HTTPException(status_code=404, detail="Student not found.")
                conn.commit()
                return {"message": "Student deleted successfully."}
    except HTTPException:
        raise
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Database error: {str(e)}")

@app.put("/api/students/{student_id}/photo")
async def update_student_photo(student_id: uuid.UUID, image: UploadFile = File(...)):
    file_bytes = await image.read()
    embedding, error = extract_face_embedding(file_bytes)
    if not embedding:
        raise HTTPException(status_code=400, detail=error)
        
    try:
        with get_db_connection() as conn:
            with conn.cursor() as cur:
                cur.execute("""
                    SELECT name, roll_number, (face_encoding <=> %s::vector) AS distance
                    FROM students
                    WHERE id != %s
                    ORDER BY distance ASC
                    LIMIT 1;
                """, (str(embedding), student_id))
                
                result = cur.fetchone()
                if result:
                    existing_name, existing_roll_number, distance = result
                    if distance <= 0.40:
                        raise HTTPException(status_code=400, detail=f"This face is already registered to {existing_name} (Roll: {existing_roll_number}).")

                cur.execute(
                    "UPDATE students SET face_encoding = %s WHERE id = %s RETURNING id",
                    (str(embedding), student_id)
                )
                if not cur.fetchone():
                    raise HTTPException(status_code=404, detail="Student not found.")
                conn.commit()
                return {"message": "Student photo updated successfully."}
    except HTTPException:
        raise
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Database error: {str(e)}")

class ManualAttendance(BaseModel):
    student_id: uuid.UUID
    date: str  # YYYY-MM-DD
    status: str # "Present" or "Absent"

@app.post("/api/attendance/manual")
async def mark_manual_attendance(data: ManualAttendance):
    try:
        with get_db_connection() as conn:
            with conn.cursor() as cur:
                if data.status == "Present":
                    cur.execute("""
                        SELECT id FROM attendance 
                        WHERE student_id = %s AND timestamp::date = %s
                    """, (data.student_id, data.date))
                    
                    if not cur.fetchone():
                        cur.execute(
                            "INSERT INTO attendance (student_id, status, timestamp) VALUES (%s, 'Present', %s)",
                            (data.student_id, f"{data.date} 12:00:00") # Default to noon for manual entries
                        )
                        conn.commit()
                        return {"message": "Marked present successfully."}
                    else:
                        return {"message": "Already marked present for this date."}
                elif data.status == "Absent":
                    cur.execute("""
                        DELETE FROM attendance 
                        WHERE student_id = %s AND timestamp::date = %s
                    """, (data.student_id, data.date))
                    conn.commit()
                    return {"message": "Marked absent successfully."}
                else:
                    raise HTTPException(status_code=400, detail="Invalid status.")
    except HTTPException:
        raise
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Database error: {str(e)}")

@app.get("/")
def read_root():
    return {"status": "ok", "message": "VisionAttend API is active"}