Adriano
654ab7b6d9
Aggiunge HypothesisAgent che invoca LLMClient con system/user template parametrizzati sul genoma e sul MarketSummary, poi estrae la S-expression (da fence markdown lisp/scheme/sexp o testo nudo), la parsa e la valida. Restituisce HypothesisProposal con strategy=None + parse_error in caso di output malformato, mantenendo sempre il CompletionResult per accounting. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
94 lines
2.9 KiB
Python
94 lines
2.9 KiB
Python
from multi_swarm.agents.hypothesis import HypothesisAgent, MarketSummary
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from multi_swarm.genome.hypothesis import HypothesisAgentGenome, ModelTier
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from multi_swarm.llm.client import CompletionResult
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def make_summary() -> MarketSummary:
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return MarketSummary(
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symbol="BTC/USDT",
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timeframe="1h",
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n_bars=1000,
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return_mean=0.0001,
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return_std=0.01,
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skew=0.1,
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kurtosis=3.5,
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volatility_regime="high",
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)
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def test_hypothesis_agent_calls_llm_and_parses(mocker): # type: ignore[no-untyped-def]
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fake_llm = mocker.MagicMock()
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fake_llm.complete.return_value = CompletionResult(
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text="(strategy (when (gt (indicator rsi 14) 70.0) (entry-short)))",
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input_tokens=200,
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output_tokens=80,
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tier=ModelTier.C,
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model="qwen",
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)
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g = HypothesisAgentGenome(
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system_prompt="Pensa come un fisico.",
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feature_access=["close"],
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temperature=0.9,
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top_p=0.95,
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model_tier=ModelTier.C,
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lookback_window=200,
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cognitive_style="physicist",
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)
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agent = HypothesisAgent(llm=fake_llm)
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proposal = agent.propose(g, make_summary())
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assert proposal.strategy is not None
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assert proposal.raw_text.startswith("(strategy")
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assert proposal.completion.input_tokens == 200
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fake_llm.complete.assert_called_once()
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def test_hypothesis_agent_returns_none_on_parse_error(mocker): # type: ignore[no-untyped-def]
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fake_llm = mocker.MagicMock()
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fake_llm.complete.return_value = CompletionResult(
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text="this is not s-expression",
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input_tokens=200,
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output_tokens=80,
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tier=ModelTier.C,
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model="qwen",
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)
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g = HypothesisAgentGenome(
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system_prompt="x",
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feature_access=["close"],
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temperature=0.9,
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top_p=0.95,
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model_tier=ModelTier.C,
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lookback_window=200,
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cognitive_style="physicist",
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)
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agent = HypothesisAgent(llm=fake_llm)
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proposal = agent.propose(g, make_summary())
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assert proposal.strategy is None
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assert proposal.parse_error is not None
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def test_hypothesis_agent_extracts_sexp_from_markdown_fence(mocker): # type: ignore[no-untyped-def]
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fake_llm = mocker.MagicMock()
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fake_llm.complete.return_value = CompletionResult(
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text=(
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"Ecco la strategia:\n```lisp\n"
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"(strategy (when (lt (indicator rsi 14) 30.0) (entry-long)))\n"
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"```\nFatta."
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),
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input_tokens=200,
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output_tokens=80,
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tier=ModelTier.C,
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model="qwen",
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)
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g = HypothesisAgentGenome(
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system_prompt="x",
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feature_access=["close"],
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temperature=0.9,
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top_p=0.95,
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model_tier=ModelTier.C,
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lookback_window=200,
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cognitive_style="physicist",
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)
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agent = HypothesisAgent(llm=fake_llm)
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proposal = agent.propose(g, make_summary())
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assert proposal.strategy is not None
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