main.py

import datetime
import json
from typing import Optional, Dict, List
from fastapi import FastAPI, Depends, HTTPException, status
from fastapi.staticfiles import StaticFiles
from fastapi.security import OAuth2PasswordBearer, OAuth2PasswordRequestForm
from pydantic import BaseModel
from psycopg2.extras import DictCursor
from jose import JWTError, jwt
from passlib.context import CryptContext

import db
import queries

# --- Security Configuration ---
pwd_context = CryptContext(schemes=["bcrypt"], deprecated="auto")
SECRET_KEY = "your-super-secret-key-that-you-should-change"
ALGORITHM = "HS256"
ACCESS_TOKEN_EXPIRE_MINUTES = 30
oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token")

app = FastAPI()

# --- Pydantic Models ---
class User(BaseModel):
    username: str
class Token(BaseModel):
    access_token: str
    token_type: str
class TokenData(BaseModel):
    username: Optional[str] = None

class Score(BaseModel):
    metric: str
    role: str
    value: float
    ms: int

class InterestProfile(BaseModel):
    R: int
    I: int
    A: int
    S: int
    E: int
    C: int
class ValuesProfile(BaseModel):
    values: Dict[str, int]
class StylesProfile(BaseModel):
    styles: Dict[str, int]

# --- Static Files ---
app.mount("/static", StaticFiles(directory="public"), name="static")

# --- Security and User Utility Functions ---
def verify_password(plain_password, hashed_password):
    return pwd_context.verify(plain_password, hashed_password)

def get_password_hash(password):
    return pwd_context.hash(password)

def create_access_token(data: dict, expires_delta: Optional[datetime.timedelta] = None):
    to_encode = data.copy()
    if expires_delta:
        expire = datetime.datetime.utcnow() + expires_delta
    else:
        expire = datetime.datetime.utcnow() + datetime.timedelta(minutes=15)
    to_encode.update({"exp": expire})
    encoded_jwt = jwt.encode(to_encode, SECRET_KEY, algorithm=ALGORITHM)
    return encoded_jwt

async def get_current_user(token: str = Depends(oauth2_scheme)):
    credentials_exception = HTTPException(
        status_code=status.HTTP_401_UNAUTHORIZED,
        detail="Could not validate credentials",
        headers={"WWW-Authenticate": "Bearer"},
    )
    try:
        payload = jwt.decode(token, SECRET_KEY, algorithms=[ALGORITHM])
        username: str = payload.get("sub")
        if username is None:
            raise credentials_exception
        token_data = TokenData(username=username)
    except JWTError:
        raise credentials_exception
    return token_data

# --- Authentication Endpoints ---
@app.post("/token", response_model=Token)
async def login_for_access_token(form_data: OAuth2PasswordRequestForm = Depends()):
    conn = None
    try:
        conn = db.get_db_connection()
        with conn.cursor(cursor_factory=DictCursor) as cur:
            cur.execute("SELECT * FROM users WHERE username = %s", (form_data.username,))
            user = cur.fetchone()
        if not user or not verify_password(form_data.password, user['hashed_password']):
            raise HTTPException(
                status_code=status.HTTP_401_UNAUTHORIZED,
                detail="Incorrect username or password",
                headers={"WWW-Authenticate": "Bearer"},
            )
        access_token_expires = datetime.timedelta(minutes=ACCESS_TOKEN_EXPIRE_MINUTES)
        access_token = create_access_token(
            data={"sub": user['username']}, expires_delta=access_token_expires
        )
        return {"access_token": access_token, "token_type": "bearer"}
    finally:
        if conn: db.return_db_connection(conn)

@app.post("/register", response_model=User)
async def register_user(form_data: OAuth2PasswordRequestForm = Depends()):
    conn = None
    try:
        conn = db.get_db_connection()
        with conn.cursor(cursor_factory=DictCursor) as cur:
            cur.execute("SELECT * FROM users WHERE username = %s", (form_data.username,))
            if cur.fetchone():
                raise HTTPException(status_code=400, detail="Username already registered")

            hashed_password = get_password_hash(form_data.password)
            cur.execute("INSERT INTO users (username, hashed_password) VALUES (%s, %s)",
                        (form_data.username, hashed_password))
        conn.commit()
        return {"username": form_data.username}
    finally:
        if conn: db.return_db_connection(conn)

# --- SECURED Endpoints ---
@app.get("/matches")
def get_matches(current_user: User = Depends(get_current_user)):
    user_id = current_user.username
    conn = None
    try:
        conn = db.get_db_connection()
        with conn.cursor(cursor_factory=DictCursor) as cur:
            user_vector = _get_and_normalize_user_vector(cur, user_id)
            if not user_vector:
                raise HTTPException(status_code=404, detail="User profile is incomplete. Please take all assessments and profilers.")
            params = {'user_vector_json': json.dumps(user_vector)}
            match_query = queries.get_cosine_similarity_query()
            cur.execute(match_query, params)
            matches = [dict(row) for row in cur.fetchall()]
            for match in matches:
                match['match_score'] = round(match['match_score'] * 100, 2)
            return {"matches": matches}
    finally:
        if conn: db.return_db_connection(conn)

@app.post("/save_score")
def save_score(score_data: Score, current_user: User = Depends(get_current_user)):
    user_id = current_user.username
    conn = None
    try:
        conn = db.get_db_connection()
        with conn.cursor() as cur:
            cur.execute("INSERT INTO scores (user_id, role, metric, value, ms) VALUES (%s, %s, %s, %s, %s)",
                        (user_id, score_data.role, score_data.metric, score_data.value, score_data.ms))
        conn.commit()
        return {"status": "success"}
    finally:
        if conn: db.return_db_connection(conn)

@app.post("/save_interests")
def save_interests(profile: InterestProfile, current_user: User = Depends(get_current_user)):
    user_id = current_user.username
    conn = None
    try:
        conn = db.get_db_connection()
        interest_map = {
            'R': 'Realistic', 'I': 'Investigative', 'A': 'Artistic',
            'S': 'Social', 'E': 'Enterprising', 'C': 'Conventional'
        }
        data_dict = {interest_map[k]: v for k, v in profile.dict().items()}
        _save_profile_data(conn, user_id, "user_interests", data_dict, "interest")
        return {"status": "success"}
    finally:
        if conn: db.return_db_connection(conn)

@app.post("/save_values")
def save_values(profile: ValuesProfile, current_user: User = Depends(get_current_user)):
    user_id = current_user.username
    conn = None
    try:
        conn = db.get_db_connection()
        _save_profile_data(conn, user_id, "user_values", profile.values, "value")
        return {"status": "success"}
    finally:
        if conn: db.return_db_connection(conn)

@app.post("/save_styles")
def save_styles(profile: StylesProfile, current_user: User = Depends(get_current_user)):
    user_id = current_user.username
    conn = None
    try:
        conn = db.get_db_connection()
        _save_profile_data(conn, user_id, "user_styles", profile.styles, "style")
        return {"status": "success"}
    finally:
        if conn: db.return_db_connection(conn)

@app.get("/job_details/{soc_code}")
def get_job_details(soc_code: str, current_user: User = Depends(get_current_user)):
    user_id = current_user.username
    conn = None
    try:
        conn = db.get_db_connection()
        with conn.cursor(cursor_factory=DictCursor) as cur:
            cur.execute("SELECT title, description FROM occupations WHERE soc_code = %s", (soc_code,))
            job_info = cur.fetchone()
            if not job_info:
                raise HTTPException(status_code=404, detail="Job not found.")

            user_vector = _get_and_normalize_user_vector(cur, user_id)
            cur.execute("SELECT feature_name, normalized_value FROM job_profile_vectors WHERE soc_code = %s", (soc_code,))
            job_vector = {row['feature_name']: row['normalized_value'] for row in cur.fetchall()}

            comparison = {}
            for feature, user_score in user_vector.items():
                category, name = feature.split('_', 1)
                if category not in comparison:
                    comparison[category] = []
                comparison[category].append({
                    "name": name,
                    "user_score": round(user_score * 100, 1),
                    "job_score": round(job_vector.get(feature, 0) * 100, 1)
                })

            return {
                "title": job_info['title'],
                "description": job_info['description'],
                "profile_match": comparison
            }
    finally:
        if conn: db.return_db_connection(conn)


# --- Helper functions ---
def _save_profile_data(conn, user_id: str, table_name: str, data: dict, column_prefix: str):
    item_col_name = f"{column_prefix}_name"
    sql = (
        f"INSERT INTO {table_name} (user_id, {item_col_name}, score) "
        "VALUES (%s, %s, %s) "
        f"ON CONFLICT (user_id, {item_col_name}) "
        "DO UPDATE SET score = EXCLUDED.score;"
    )
    data_to_insert = [(user_id, name, score) for name, score in data.items()]
    with conn.cursor() as cur:
        cur.executemany(sql, data_to_insert)
    conn.commit()

def _get_and_normalize_user_vector(cur, user_id: str) -> dict:
    user_vector = {}
    
    # --- 1. Abilities (from aptitude tests) ---
    cur.execute("SELECT metric, value FROM scores WHERE user_id = %s", (user_id,))
    raw_aptitudes = {row['metric']: row['value'] for row in cur.fetchall()}
    
    # Handle Reaction Time (lower is better)
    rt_score = raw_aptitudes.get('Reaction Time')
    if rt_score is not None:
        best_rt, worst_rt = 150, 1000
        clamped_rt = max(best_rt, min(rt_score, worst_rt))
        user_vector['ability_Reaction Time'] = 1 - ((clamped_rt - best_rt) / (worst_rt - best_rt))
    
    # Handle other aptitudes
    for metric, value in raw_aptitudes.items():
        if metric in ['Number Facility', 'Spatial Orientation']:
            user_vector[f'ability_{metric}'] = value / 100.0
        # THE FIX: Add the same inverted logic for Manual Dexterity (lower is better)
        elif metric == 'Manual Dexterity':
            best_dex, worst_dex = 3000, 15000 # Define reasonable min/max ms
            clamped_dex = max(best_dex, min(value, worst_dex))
            user_vector['ability_Manual Dexterity'] = 1 - ((clamped_dex - best_dex) / (worst_dex - best_dex))

    # --- 2. Interests (RIASEC) ---
    cur.execute("SELECT interest_name, score FROM user_interests WHERE user_id = %s", (user_id,))
    for row in cur.fetchall():
        user_vector[f"interest_{row['interest_name']}"] = row['score'] / 4.0

    # --- 3. Values ---
    cur.execute("SELECT value_name, score FROM user_values WHERE user_id = %s", (user_id,))
    for row in cur.fetchall():
        user_vector[f"value_{row['value_name']}"] = row['score'] / 5.0

    # --- 4. Styles ---
    cur.execute("SELECT style_name, score FROM user_styles WHERE user_id = %s", (user_id,))
    for row in cur.fetchall():
        user_vector[f"style_{row['style_name']}"] = (row['score'] - 1) / 4.0
        
    return user_vector