open/portfolio-optimiser
1
0
Fork 0
Code Issues Pull requests Releases Wiki Activity Actions

style(fase1): ruff format spike modules

Browse source
This commit is contained in:
Kjell Tore Guttormsen 2026-06-24 10:34:27 +02:00
commit c1317689f1
6 changed files with 123 additions and 26 deletions
Download patch file Download diff file Expand all files Collapse all files

5
spikes/_harness.py
View file

@ -137,8 +137,11 @@ class FakeChatClient(BaseChatClient):
reply = self._next_reply()
if stream:
async def _agen() -> Any:
yield ChatResponseUpdate(role="assistant", contents=[{"type": "text", "text": reply}])
yield ChatResponseUpdate(
role="assistant", contents=[{"type": "text", "text": reply}]
)
return self._build_response_stream(_agen())

12
spikes/a_groupchat.py
View file

@ -109,7 +109,9 @@ def _caught_flaw(texts: Sequence[str]) -> bool:
return any(marker in blob for marker in _FLAW_MARKERS)
async def run_live(*, n_rounds: int = DEFAULT_ROUNDS, write_findings: bool = True) -> dict[str, object]:
async def run_live(
*, n_rounds: int = DEFAULT_ROUNDS, write_findings: bool = True
) -> dict[str, object]:
"""Gated empirical arm: run maker-checker vs single-agent against a reference
project carrying a planted flaw, measure, and write ``findings-a.md``.
@ -127,8 +129,12 @@ async def run_live(*, n_rounds: int = DEFAULT_ROUNDS, write_findings: bool = Tru
# --- maker-checker arm (3 roles) ---
proposer = Agent(client, "You propose one concrete cost-saving measure.", name="proposer")
critic = Agent(client, "You critique the proposal and flag any constraint violation.", name="critic")
validator = Agent(client, "You give the final valid/invalid decision with a reason.", name="validator")
critic = Agent(
client, "You critique the proposal and flag any constraint violation.", name="critic"
)
validator = Agent(
client, "You give the final valid/invalid decision with a reason.", name="validator"
)
names = ["proposer", "critic", "validator"]
counter = {"n": 0}

8
spikes/b_footguns.py
View file

@ -53,7 +53,9 @@ _NEVER_SATISFIED_LEDGER = json.dumps(
def _magentic(max_round_count: int | None) -> object:
"""Build a Magentic workflow whose manager never self-finalizes."""
manager = StandardMagenticManager(
agent=Agent(FakeChatClient(default_reply=_NEVER_SATISFIED_LEDGER), "manager", name="manager"),
agent=Agent(
FakeChatClient(default_reply=_NEVER_SATISFIED_LEDGER), "manager", name="manager"
),
max_round_count=max_round_count,
)
worker = Agent(FakeChatClient(default_reply="worker did some work"), "worker", name="worker")
@ -95,9 +97,7 @@ def fresh_workflow() -> tuple[object, tuple[FakeChatClient, FakeChatClient]]:
every call, so no state survives between runs."""
c1 = FakeChatClient(default_reply="participant one view")
c2 = FakeChatClient(default_reply="participant two view")
workflow = ConcurrentBuilder(
participants=[fake_agent(c1, "w1"), fake_agent(c2, "w2")]
).build()
workflow = ConcurrentBuilder(participants=[fake_agent(c1, "w1"), fake_agent(c2, "w2")]).build()
return workflow, (c1, c2)

8
spikes/c_validator.py
View file

@ -120,11 +120,15 @@ def _solve_max_feasible(items: list[AffectedItem], fraction: float) -> float:
prob += pulp.lpSum(xs) <= fraction * sum(it.total for it in items)
status = prob.solve(solver)
if pulp.LpStatus[status] != "Optimal":
raise CbcUnavailable(f"CBC did not reach an optimal solution (status={pulp.LpStatus[status]})")
raise CbcUnavailable(
f"CBC did not reach an optimal solution (status={pulp.LpStatus[status]})"
)
return float(pulp.value(prob.objective))
def _monte_carlo(proposal: SavingsProposal, *, fraction: float = MAX_SAVING_FRACTION) -> tuple[float, float, float]:
def _monte_carlo(
proposal: SavingsProposal, *, fraction: float = MAX_SAVING_FRACTION
) -> tuple[float, float, float]:
"""Vary uncertain unit-costs (seeded) and return (P10, P50, P90) of the feasible
saving. Uses the LP's closed-form optimum (= fraction x sum of sampled totals), which
is exact here, so we do NOT spawn a CBC subprocess per sample (D6)."""

112
spikes/d_verdictstore.py
View file

@ -63,9 +63,12 @@ def similarity(query: ProposalFeatures, candidate: ProposalFeatures) -> float:
"""Weighted structural similarity in [0, 1] — text is ignored by design."""
codes = _jaccard(query.affected_codes, candidate.affected_codes)
measure = 1.0 if query.measure_type == candidate.measure_type else 0.0
magnitude = 1.0 if _magnitude_bucket(query.claimed_saving_nok) == _magnitude_bucket(
candidate.claimed_saving_nok
) else 0.0
magnitude = (
1.0
if _magnitude_bucket(query.claimed_saving_nok)
== _magnitude_bucket(candidate.claimed_saving_nok)
else 0.0
)
return _W_CODES * codes + _W_MEASURE * measure + _W_MAGNITUDE * magnitude
@ -106,7 +109,9 @@ class ExpeLContextProvider(ContextProvider):
body = "\n".join(f"- [{v.id}] {v.decision}: {v.rationale}" for v in hits)
return f"Relevant prior verdicts (ExpeL few-shot):\n{body}"
async def before_run(self, *, agent: object, session: object, context: object, state: dict) -> None:
async def before_run(
self, *, agent: object, session: object, context: object, state: dict
) -> None:
context.extend_instructions([self.format_fewshot()]) # type: ignore[attr-defined]
@ -114,18 +119,95 @@ def seed_store() -> VerdictStore:
"""Seed 12 synthetic verdicts spanning the reference domain's cost codes, measure
types, magnitudes, and decisions (B2 store of 10–20)."""
rows = [
("V01", {"05.2", "03.1"}, "scope_reduction", 180_000, "approved", "asphalt + base course trimmed within feasible range"),
("V02", {"05.2"}, "rate_renegotiation", 60_000, "approved", "renegotiated asphalt unit rate"),
("V03", {"07.4"}, "material_substitution", 120_000, "rejected", "granite kerb substitution unsafe"),
("V04", {"09.1"}, "scope_reduction", 240_000, "approved", "fewer LED masts on low-traffic stretch"),
("V05", {"02.3", "03.1"}, "scope_reduction", 350_000, "rejected", "soil replacement is load-bearing, cannot cut"),
(
"V01",
{"05.2", "03.1"},
"scope_reduction",
180_000,
"approved",
"asphalt + base course trimmed within feasible range",
),
(
"V02",
{"05.2"},
"rate_renegotiation",
60_000,
"approved",
"renegotiated asphalt unit rate",
),
(
"V03",
{"07.4"},
"material_substitution",
120_000,
"rejected",
"granite kerb substitution unsafe",
),
(
"V04",
{"09.1"},
"scope_reduction",
240_000,
"approved",
"fewer LED masts on low-traffic stretch",
),
(
"V05",
{"02.3", "03.1"},
"scope_reduction",
350_000,
"rejected",
"soil replacement is load-bearing, cannot cut",
),
("V06", {"21.2"}, "rate_renegotiation", 90_000, "approved", "blasting rate renegotiated"),
("V07", {"22.4"}, "material_substitution", 700_000, "rejected", "fiber shotcrete spec is mandated"),
("V08", {"88.2"}, "scope_reduction", 150_000, "approved", "concrete repair area re-measured smaller"),
("V09", {"87.3"}, "material_substitution", 130_000, "approved", "alternative membrane qualified"),
("V10", {"05.2", "03.1"}, "rate_renegotiation", 200_000, "approved", "combined paving rate discount"),
("V11", {"01.1"}, "scope_reduction", 95_000, "rejected", "rigging is fixed cost, no scope to cut"),
("V12", {"31.3"}, "scope_reduction", 110_000, "approved", "drainage length reduced after survey"),
(
"V07",
{"22.4"},
"material_substitution",
700_000,
"rejected",
"fiber shotcrete spec is mandated",
),
(
"V08",
{"88.2"},
"scope_reduction",
150_000,
"approved",
"concrete repair area re-measured smaller",
),
(
"V09",
{"87.3"},
"material_substitution",
130_000,
"approved",
"alternative membrane qualified",
),
(
"V10",
{"05.2", "03.1"},
"rate_renegotiation",
200_000,
"approved",
"combined paving rate discount",
),
(
"V11",
{"01.1"},
"scope_reduction",
95_000,
"rejected",
"rigging is fixed cost, no scope to cut",
),
(
"V12",
{"31.3"},
"scope_reduction",
110_000,
"approved",
"drainage length reduced after survey",
),
]
return VerdictStore(
verdicts=[

4
tests/spikes/test_d_verdictstore.py
View file

@ -73,7 +73,9 @@ def test_retrieve_finds_structural_match_over_text_decoys() -> None:
def test_retrieve_is_deterministic() -> None:
store, _ = _store_with_true_match_and_decoys()
assert [h.id for h in store.retrieve(_QUERY, k=3)] == [h.id for h in store.retrieve(_QUERY, k=3)]
assert [h.id for h in store.retrieve(_QUERY, k=3)] == [
h.id for h in store.retrieve(_QUERY, k=3)
]
def test_retrieve_rejects_non_positive_k() -> None: