57 lines
2.0 KiB
Python
57 lines
2.0 KiB
Python
import json
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from pathlib import Path
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from multi_swarm.genome.hypothesis import HypothesisAgentGenome, ModelTier
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from multi_swarm.persistence.repository import Repository
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def make_genome(idx: int) -> HypothesisAgentGenome:
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return HypothesisAgentGenome(
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system_prompt=f"p-{idx}", feature_access=["close"], temperature=0.9,
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top_p=0.95, model_tier=ModelTier.C, lookback_window=100, cognitive_style="x",
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)
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def test_repository_creates_schema(tmp_path: Path):
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repo = Repository(db_path=tmp_path / "runs.db")
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repo.init_schema()
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assert (tmp_path / "runs.db").exists()
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def test_repository_create_run_and_get(tmp_path: Path):
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repo = Repository(db_path=tmp_path / "runs.db")
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repo.init_schema()
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run_id = repo.create_run(name="phase1-test", config={"k": 20})
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run = repo.get_run(run_id)
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assert run["name"] == "phase1-test"
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assert json.loads(run["config_json"])["k"] == 20
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def test_repository_save_genome_and_evaluation(tmp_path: Path):
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repo = Repository(db_path=tmp_path / "runs.db")
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repo.init_schema()
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run_id = repo.create_run(name="t", config={})
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g = make_genome(0)
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repo.save_genome(run_id=run_id, generation_idx=0, genome=g)
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repo.save_evaluation(
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run_id=run_id, genome_id=g.id, fitness=0.5, dsr=0.7, dsr_pvalue=0.05,
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sharpe=1.5, max_dd=0.2, total_return=0.3, n_trades=30,
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parse_error=None, raw_text="(strategy ...)",
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)
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evals = repo.list_evaluations(run_id)
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assert len(evals) == 1
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assert evals[0]["fitness"] == 0.5
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def test_repository_save_generation_summary(tmp_path: Path):
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repo = Repository(db_path=tmp_path / "runs.db")
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repo.init_schema()
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run_id = repo.create_run(name="t", config={})
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repo.save_generation_summary(
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run_id=run_id, generation_idx=0, n_genomes=20,
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fitness_median=0.3, fitness_max=0.8, fitness_p90=0.7, entropy=0.85,
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)
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gens = repo.list_generations(run_id)
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assert len(gens) == 1
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assert gens[0]["fitness_max"] == 0.8
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