"""Model Comparator Router"""
from fastapi import APIRouter
from pydantic import BaseModel
from typing import Optional

router = APIRouter()


class CompareRequest(BaseModel):
    prompt: str
    models: list[str]
    temperature: float = 0.7
    max_tokens: int = 500


class ModelResponse(BaseModel):
    model: str
    response: str
    latency_ms: float
    tokens_used: int
    estimated_cost: float


class CompareResult(BaseModel):
    prompt: str
    responses: list[ModelResponse]
    fastest: str
    cheapest: str
    quality_scores: Optional[dict] = None


class EvalRequest(BaseModel):
    prompt: str
    responses: dict  # model -> response
    criteria: list[str] = ["coherence", "accuracy", "relevance", "helpfulness"]


@router.post("/run", response_model=CompareResult)
async def compare_models(request: CompareRequest):
    """Run a prompt against multiple models and compare"""
    # TODO: Implement model comparison
    return CompareResult(
        prompt=request.prompt,
        responses=[],
        fastest="",
        cheapest=""
    )


@router.post("/evaluate")
async def evaluate_responses(request: EvalRequest):
    """Evaluate and score model responses"""
    # TODO: Implement response evaluation
    return {
        "scores": {},
        "winner": None,
        "analysis": ""
    }


@router.get("/benchmarks")
async def list_benchmarks():
    """List available benchmark prompts"""
    return {
        "benchmarks": [
            {"name": "general_qa", "prompts": 10},
            {"name": "coding", "prompts": 15},
            {"name": "creative_writing", "prompts": 8},
            {"name": "reasoning", "prompts": 12},
        ]
    }


@router.post("/benchmark/{benchmark_name}")
async def run_benchmark(
    benchmark_name: str,
    models: list[str]
):
    """Run a full benchmark suite against models"""
    # TODO: Implement benchmark running
    return {
        "benchmark": benchmark_name,
        "results": {},
        "summary": ""
    }
