import json
from pathlib import Path

from multi_swarm.genome.hypothesis import HypothesisAgentGenome, ModelTier
from multi_swarm.persistence.repository import Repository


def make_genome(idx: int) -> HypothesisAgentGenome:
    return HypothesisAgentGenome(
        system_prompt=f"p-{idx}", feature_access=["close"], temperature=0.9,
        top_p=0.95, model_tier=ModelTier.C, lookback_window=100, cognitive_style="x",
    )


def test_repository_creates_schema(tmp_path: Path):
    repo = Repository(db_path=tmp_path / "runs.db")
    repo.init_schema()
    assert (tmp_path / "runs.db").exists()


def test_repository_create_run_and_get(tmp_path: Path):
    repo = Repository(db_path=tmp_path / "runs.db")
    repo.init_schema()
    run_id = repo.create_run(name="phase1-test", config={"k": 20})
    run = repo.get_run(run_id)
    assert run["name"] == "phase1-test"
    assert json.loads(run["config_json"])["k"] == 20


def test_repository_save_genome_and_evaluation(tmp_path: Path):
    repo = Repository(db_path=tmp_path / "runs.db")
    repo.init_schema()
    run_id = repo.create_run(name="t", config={})
    g = make_genome(0)
    repo.save_genome(run_id=run_id, generation_idx=0, genome=g)
    repo.save_evaluation(
        run_id=run_id, genome_id=g.id, fitness=0.5, dsr=0.7, dsr_pvalue=0.05,
        sharpe=1.5, max_dd=0.2, total_return=0.3, n_trades=30,
        parse_error=None, raw_text="(strategy ...)",
    )
    evals = repo.list_evaluations(run_id)
    assert len(evals) == 1
    assert evals[0]["fitness"] == 0.5


def test_repository_save_generation_summary(tmp_path: Path):
    repo = Repository(db_path=tmp_path / "runs.db")
    repo.init_schema()
    run_id = repo.create_run(name="t", config={})
    repo.save_generation_summary(
        run_id=run_id, generation_idx=0, n_genomes=20,
        fitness_median=0.3, fitness_max=0.8, fitness_p90=0.7, entropy=0.85,
    )
    gens = repo.list_generations(run_id)
    assert len(gens) == 1
    assert gens[0]["fitness_max"] == 0.8