from typing import List, Optional
from fastapi import APIRouter, Depends, Query
from sqlalchemy.orm import Session
from backend.app.core.database import get_db
from backend.app.repositories.users import UserRepository
from backend.app.schemas.auth import WorkerSearchResult

router = APIRouter(prefix="/workers", tags=["workers"])

def calculate_ai_score(
    rating: float, 
    completion_rate: int, 
    distance: float, 
    online: bool, 
    verified: bool
) -> int:
    """
    Simulated AI ranking score calculation.
    Formula: rating * 7 + completion_rate * 0.25 + online (25 pts) + verified (15 pts) + distance (max 25 - distance * 3)
    """
    online_score = 25 if online else 0
    verified_score = 15 if verified else 0
    distance_score = max(0.0, 25.0 - float(distance) * 3.0)
    
    score = (float(rating) * 7.0) + (int(completion_rate) * 0.25) + online_score + verified_score + distance_score
    return round(score)

@router.get("", response_model=List[WorkerSearchResult])
def search_workers(
    skill: Optional[str] = Query("All", description="Filter by worker skill type"),
    radius: Optional[float] = Query(5.0, description="Max search radius in kilometers"),
    online: Optional[str] = Query("yes", description="Filter: 'yes' for online only, 'all' for all"),
    q: Optional[str] = Query("", alias="query", description="Search by name or skill query text"),
    db: Session = Depends(get_db)
):
    """
    Search and rank construction workers using the location-aware AI ranking algorithm.
    """
    user_repo = UserRepository(db)
    
    # Resolve online boolean filter
    online_only = (online == "yes")
    
    # Query database workers matching filters
    workers = user_repo.get_all_workers(
        skill=skill,
        radius=radius,
        online_only=online_only
    )
    
    results = []
    text_filter = q.strip().lower()
    
    for user in workers:
        prof = user.worker_profile
        if not prof:
            continue
            
        # Text query filtering (by name or skill)
        if text_filter and text_filter not in f"{user.name} {prof.skill}".lower():
            continue
            
        # Compute dynamic match score
        score = calculate_ai_score(
            rating=prof.rating,
            completion_rate=prof.completion_rate,
            distance=prof.distance,
            online=prof.online,
            verified=prof.verified
        )
        
        results.append(
            WorkerSearchResult(
                id=user.id,
                name=user.name,
                phone=user.phone,
                city=user.city,
                skill=prof.skill,
                rate=prof.rate,
                rating=prof.rating,
                distance=prof.distance,
                online=prof.online,
                verified=prof.verified,
                completed_jobs=prof.completed_jobs,
                completion_rate=prof.completion_rate,
                map_x=prof.map_x,
                map_y=prof.map_y,
                ai_score=score
            )
        )
        
    # Sort results in descending order of AI Match Score
    results.sort(key=lambda w: w.ai_score, reverse=True)
    return results