from __future__ import annotations

import itertools
import random
from typing import Any, Dict, Optional

from edgeeda.agents.base import Action, Agent
from edgeeda.config import Config
from edgeeda.utils import sanitize_variant_prefix, stable_hash


class RandomSearchAgent(Agent):
    def __init__(self, cfg: Config):
        self.cfg = cfg
        self.counter = 0
        self.variant_prefix = sanitize_variant_prefix(cfg.experiment.name)

    def _sample_knobs(self) -> Dict[str, Any]:
        out: Dict[str, Any] = {}
        for name, spec in self.cfg.tuning.knobs.items():
            if spec.type == "int":
                out[name] = random.randint(int(spec.min), int(spec.max))
            else:
                out[name] = float(spec.min) + random.random() * (float(spec.max) - float(spec.min))
                out[name] = round(out[name], 3)
        return out

    def propose(self) -> Action:
        self.counter += 1
        knobs = self._sample_knobs()
        variant = f"{self.variant_prefix}_t{self.counter:05d}_{stable_hash(str(knobs))}"
        fidelity = self.cfg.flow.fidelities[0]  # always start cheap
        return Action(variant=variant, fidelity=fidelity, knobs=knobs)

    def observe(self, action: Action, ok: bool, reward: Optional[float], metrics_flat: Optional[Dict[str, Any]]) -> None:
        # Random agent doesn't adapt.
        return