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refactor(protocol): swap S-expression grammar for strict JSON Schema

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Sostituisce la grammatica S-expression con uno schema JSON stretto. La
grammatica S-expression falliva il parsing nel 64% delle generazioni del
modello Qwen3-235B sul run reale; JSON e' nativo per gli LLM moderni e
si parsa con json.loads.

Cambiamenti principali:
- grammar.py: costanti rinominate LOGICAL_OPS / COMPARATOR_OPS /
  CROSSOVER_OPS / ACTION_VALUES / KIND_VALUES.
- parser.py: nuovo AST a dataclass tipizzato (OpNode, IndicatorNode,
  FeatureNode, LiteralNode, Rule, Strategy); parse_strategy ora consuma
  JSON tramite json.loads.
- validator.py: walk dispatchato per tipo (isinstance) invece di
  pattern-matching su 'kind'; arity check su operatori e indicator.
- compiler.py: traversal del nuovo AST tipizzato, dispatch per
  isinstance; logica indicator/feature/literal invariata.
- hypothesis.py: prompt SYSTEM riscritto con esempi JSON e vincoli
  espliciti su no-nesting; estrazione via fence ```json``` + fallback
  brace-balanced.
- __init__.py: re-export pubblico delle entita' del protocollo.
- Tutti i test (parser, validator, compiler, hypothesis_agent,
  falsification, adversarial, e2e, smoke_run) migrati a JSON.
- Rimossa dipendenza sexpdata da pyproject.toml + uv.lock.

Test: 135 passed (era 122; aggiunti casi parser/validator).
ruff + mypy strict clean. Smoke run end-to-end OK.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
AdrianoDev
2026-05-10 21:17:26 +02:00
parent df76906505
commit 44eb6436c1
16 changed files with 1082 additions and 392 deletions
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tests/unit/test_hypothesis_agent.py
+76 -39
View File
@@ -1,3 +1,5 @@
import json
from multi_swarm.agents.hypothesis import HypothesisAgent, MarketSummary
from multi_swarm.genome.hypothesis import HypothesisAgentGenome, ModelTier
from multi_swarm.llm.client import CompletionResult
@@ -16,16 +18,26 @@ def make_summary() -> MarketSummary:
)
def test_hypothesis_agent_calls_llm_and_parses(mocker): # type: ignore[no-untyped-def]
fake_llm = mocker.MagicMock()
fake_llm.complete.return_value = CompletionResult(
text="(strategy (when (gt (indicator rsi 14) 70.0) (entry-short)))",
input_tokens=200,
output_tokens=80,
tier=ModelTier.C,
model="qwen",
)
g = HypothesisAgentGenome(
VALID_STRATEGY_JSON = json.dumps(
{
"rules": [
{
"condition": {
"op": "gt",
"args": [
{"kind": "indicator", "name": "rsi", "params": [14]},
{"kind": "literal", "value": 70.0},
],
},
"action": "entry-short",
}
]
}
)
def make_genome() -> HypothesisAgentGenome:
return HypothesisAgentGenome(
system_prompt="Pensa come un fisico.",
feature_access=["close"],
temperature=0.9,
@@ -34,10 +46,20 @@ def test_hypothesis_agent_calls_llm_and_parses(mocker): # type: ignore[no-untyp
lookback_window=200,
cognitive_style="physicist",
)
def test_hypothesis_agent_calls_llm_and_parses(mocker): # type: ignore[no-untyped-def]
fake_llm = mocker.MagicMock()
fake_llm.complete.return_value = CompletionResult(
text=VALID_STRATEGY_JSON,
input_tokens=200,
output_tokens=80,
tier=ModelTier.C,
model="qwen",
)
agent = HypothesisAgent(llm=fake_llm)
proposal = agent.propose(g, make_summary())
proposal = agent.propose(make_genome(), make_summary())
assert proposal.strategy is not None
assert proposal.raw_text.startswith("(strategy")
assert proposal.completion.input_tokens == 200
fake_llm.complete.assert_called_once()
@@ -45,49 +67,64 @@ def test_hypothesis_agent_calls_llm_and_parses(mocker): # type: ignore[no-untyp
def test_hypothesis_agent_returns_none_on_parse_error(mocker): # type: ignore[no-untyped-def]
fake_llm = mocker.MagicMock()
fake_llm.complete.return_value = CompletionResult(
text="this is not s-expression",
text="this is not JSON",
input_tokens=200,
output_tokens=80,
tier=ModelTier.C,
model="qwen",
)
g = HypothesisAgentGenome(
system_prompt="x",
feature_access=["close"],
temperature=0.9,
top_p=0.95,
model_tier=ModelTier.C,
lookback_window=200,
cognitive_style="physicist",
)
agent = HypothesisAgent(llm=fake_llm)
proposal = agent.propose(g, make_summary())
proposal = agent.propose(make_genome(), make_summary())
assert proposal.strategy is None
assert proposal.parse_error is not None
def test_hypothesis_agent_extracts_sexp_from_markdown_fence(mocker): # type: ignore[no-untyped-def]
def test_hypothesis_agent_extracts_json_from_markdown_fence(mocker): # type: ignore[no-untyped-def]
fenced = (
"Ecco la strategia:\n```json\n"
+ VALID_STRATEGY_JSON
+ "\n```\nFatta."
)
fake_llm = mocker.MagicMock()
fake_llm.complete.return_value = CompletionResult(
text=(
"Ecco la strategia:\n```lisp\n"
"(strategy (when (lt (indicator rsi 14) 30.0) (entry-long)))\n"
"```\nFatta."
),
text=fenced,
input_tokens=200,
output_tokens=80,
tier=ModelTier.C,
model="qwen",
)
g = HypothesisAgentGenome(
system_prompt="x",
feature_access=["close"],
temperature=0.9,
top_p=0.95,
model_tier=ModelTier.C,
lookback_window=200,
cognitive_style="physicist",
agent = HypothesisAgent(llm=fake_llm)
proposal = agent.propose(make_genome(), make_summary())
assert proposal.strategy is not None
def test_hypothesis_agent_returns_error_on_invalid_strategy(mocker): # type: ignore[no-untyped-def]
bad = json.dumps(
{
"rules": [
{
"condition": {
"op": "gt",
"args": [
{"kind": "indicator", "name": "wibble", "params": [14]},
{"kind": "literal", "value": 70.0},
],
},
"action": "entry-short",
}
]
}
)
fake_llm = mocker.MagicMock()
fake_llm.complete.return_value = CompletionResult(
text=bad,
input_tokens=200,
output_tokens=80,
tier=ModelTier.C,
model="qwen",
)
agent = HypothesisAgent(llm=fake_llm)
proposal = agent.propose(g, make_summary())
assert proposal.strategy is not None
proposal = agent.propose(make_genome(), make_summary())
assert proposal.strategy is None
assert proposal.parse_error is not None
assert "wibble" in proposal.parse_error or "unknown" in proposal.parse_error