from fastapi import APIRouter, HTTPException
from pydantic import BaseModel
from typing import List, Optional, Dict, Any, Tuple
from problems.interval_scheduling.problem import IntervalSchedulingProblem

router = APIRouter(
    prefix="/interval_scheduling",
    tags=["interval_scheduling"],
    responses={404: {"description": "Not found"}},
)

problem_solver = IntervalSchedulingProblem()

class GenerateRequest(BaseModel):
    size: int = 10
    min_time: int = 0
    max_time: int = 100

class SolveRequest(BaseModel):
    intervals: List[Tuple[int, int]]
    algorithms: List[str] = ["greedy", "brute_force"]

class BenchmarkRequest(BaseModel):
    sizes: List[int] = [5, 10, 15, 20]
    algorithms: List[str] = ["greedy", "brute_force"]

@router.post("/generate")
async def generate_case(req: GenerateRequest):
    return problem_solver.generate_case(size=req.size, min_time=req.min_time, max_time=req.max_time)

@router.post("/solve")
async def solve_case(req: SolveRequest):
    input_data = {"intervals": req.intervals}
    results = []
    for algo in req.algorithms:
        try:
            # Skip Brute Force for large inputs to avoid timeout
            if len(req.intervals) > 22 and algo == "brute_force":
                 results.append({
                    "algorithm": algo,
                    "error": "Input too large for Brute Force (limit 22)",
                    "skipped": True
                })
                 continue

            res = problem_solver.solve(input_data, algo)
            results.append(res)
        except ValueError as e:
            results.append({"algorithm": algo, "error": str(e)})
    return results

@router.post("/benchmark")
async def benchmark(req: BenchmarkRequest):
    benchmark_results = []
    for size in req.sizes:
        input_data = problem_solver.generate_case(size=size)
        
        size_result = {"size": size, "algorithms": []}
        for algo in req.algorithms:
            try:
                if size > 22 and algo == "brute_force":
                     size_result["algorithms"].append({
                        "algorithm": algo,
                        "time_seconds": None,
                        "skipped": True
                    })
                     continue

                res = problem_solver.solve(input_data, algo)
                size_result["algorithms"].append(res)
            except Exception as e:
                size_result["algorithms"].append({"algorithm": algo, "error": str(e)})
        
        benchmark_results.append(size_result)
    return benchmark_results