portfolio-optimiser/tests/conftest.py
Kjell Tore Guttormsen 37547fe292
refactor(examples): replace sector-specific example material with generic, fictitious examples
The context sets, the packaged knowledge bases and the example bundles are
replaced by one fictitious example set about IT operations in an invented
organisation: three context sets (serverrom-2027, driftsavtale-2027 and the
two-base drift-og-avtale-2027), two synthetic knowledge bases under
src/portfolio_optimiser/data/kunnskapsbaser and two example bundles under
src/portfolio_optimiser/data/bundles. Numbers, codes and structural values in
tests and fixtures are kept; names, ids and wording change. Dated measurement
documents that only recorded runs on the replaced material are deleted.

Gate figures measured on the new set are not comparable with earlier ones.
The exclusion gate from the previous commit is green: 0 tracked files hit
outside the shared/ subtree.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-09-23 15:04:21 +02:00

257 lines
12 KiB
Python

"""Shared e2e fixtures (Step 13): a scripted chat client that emits a SYNTHETIC UsageDetails
(so token accounting is real-shaped without an LLM), plus store + docs-dir fixtures.
The synthetic ``UsageDetails`` is what lets the budget meter / provenance ``token_usage`` be a
positive, UsageDetails-sourced number in CI — the REAL-provider populated-usage assertion is
the gated live arm (Step 14).
"""
from __future__ import annotations
import json
from collections.abc import Callable, Sequence
from pathlib import Path
import pytest
from agent_framework import BaseChatClient
from portfolio_optimiser.reference_domain import load_reference_projects
from portfolio_optimiser.run import RunResult
from portfolio_optimiser.simulation import ScriptedChatClient
from portfolio_optimiser.verdicts import VerdictStore, seed_store
class SyntheticUsageChatClient(ScriptedChatClient):
"""The scripted-list-then-default test double — now a THIN subclass of the canonical
``ScriptedChatClient`` (S2.5 consolidation). It keeps its full PUBLIC surface (the
``default_reply=`` kwarg constructor, the ``call_count`` attribute, ``model``/OTEL
``"synthetic"``) but delegates the shared ``_inner_get_response`` body to the canonical — the
scripted-list-then-default behaviour lives in its selector."""
def __init__(
self,
scripted: Sequence[str] | None = None,
*,
default_reply: str = "ok",
tokens_per_reply: int = 8,
) -> None:
scripted_list = list(scripted or [])
counter = {"i": 0}
def _select(_blob: str, _role: str) -> str:
i = counter["i"]
counter["i"] = i + 1
return scripted_list[i] if i < len(scripted_list) else default_reply
super().__init__(
reply_selector=_select, default_reply=default_reply, tokens_per_reply=tokens_per_reply
)
@pytest.fixture()
def make_client_factory() -> Callable[..., Callable[[str], BaseChatClient]]:
"""Return a maker that builds a per-role client factory emitting synthetic usage."""
def _make(default_reply: str, *, tokens: int = 8) -> Callable[[str], BaseChatClient]:
def factory(role: str) -> BaseChatClient:
return SyntheticUsageChatClient(default_reply=default_reply, tokens_per_reply=tokens)
return factory
return _make
_DEFAULT_CLAIM = 20_000
# Last-resort reply for a prompt naming NO known reference project (the anchored per-project
# fallback below cannot be built then). Kept for that case only.
_PORTFOLIO_DEFAULT_REPLY = (
'{"measure":"Reduce scope","affected_items":'
'[{"code":"01.1","quantity":1,"unit_cost":100000}],"claimed_saving_nok":20000}'
)
def _anchored_default_replies() -> dict[str, str]:
"""A VALID default proposal PER reference project, quoting that project's OWN first cost line
verbatim (S4.0): since the reference path anchors the validator to ``project.cost_items``, a generic
reply carrying an invented magnitude for code ``01.1`` is now — correctly — rejected as a
fabricated cost line. Anchoring the fixture is the fix; weakening the gate is not.
``claimed_saving_nok`` stays ``20_000`` for every project, exactly as the single generic reply
claimed before, so every ledger/goal/budget assertion built on that figure is unchanged. Each
project's first line is code ``01.1`` (project management and operations, a lump sum) at
>= 480 000 NOK, so P90 (>= 144 000) clears the claim on every project."""
replies: dict[str, str] = {}
for project in load_reference_projects():
line = project.cost_items[0]
replies[project.id] = json.dumps(
{
"measure": "Reduce scope",
"affected_items": [
{"code": line.code, "quantity": line.quantity, "unit_cost": line.unit_cost}
],
"claimed_saving_nok": _DEFAULT_CLAIM,
}
)
return replies
class _ProjectAwareUsageChatClient(ScriptedChatClient):
"""Selects its reply by scanning the incoming prompt for a known ``project_id`` substring (the
prompt embeds ``project.id`` at run.py:162 and generate.py:48), falling back to a default valid
proposal — so ``run_portfolio``'s single ``client_factory`` stays production-shaped while tests
vary the proposal per project. A THIN subclass: the prompt-scan lives in its selector, the shared
``_inner_get_response`` body in the canonical.
The fallback is itself project-aware (S4.0): a prompt naming a reference project gets that
project's baseline-anchored default reply, so an un-mapped project still produces a proposal the
anchored validator admits. Only a prompt naming NO known project falls through to
``default_reply``."""
def __init__(
self, replies: dict[str, str], *, default_reply: str, tokens_per_reply: int = 8
) -> None:
table = dict(replies)
anchored = _anchored_default_replies()
def _select(blob: str, _role: str) -> str:
explicit = next((r for pid, r in table.items() if pid in blob), None)
if explicit is not None:
return explicit
return next((r for pid, r in anchored.items() if pid in blob), default_reply)
super().__init__(
reply_selector=_select, default_reply=default_reply, tokens_per_reply=tokens_per_reply
)
@pytest.fixture()
def make_portfolio_client_factory() -> Callable[..., Callable[[str], BaseChatClient]]:
"""Return a maker that builds a single project-aware client factory: every client it
produces picks its reply from ``replies`` by scanning the prompt for the project id, so one
factory serves the whole portfolio (matching ``run_portfolio``'s single-factory seam)."""
def _make(
replies: dict[str, str],
*,
default_reply: str = _PORTFOLIO_DEFAULT_REPLY,
tokens: int = 8,
) -> Callable[[str], BaseChatClient]:
def factory(role: str) -> BaseChatClient:
return _ProjectAwareUsageChatClient(
replies, default_reply=default_reply, tokens_per_reply=tokens
)
return factory
return _make
class _RecordingChatClient(ScriptedChatClient):
"""Records the incoming prompt blob per call into a SHARED sink, then returns a fixed valid
reply. Lets a test assert exactly what text reached the prompt — the probe the Step-1 ExpeL
wiring is made load-bearing against (does a prior verdict reach the hypothesis prompt?). A THIN
subclass: the canonical records to the ``sink`` (when given one) and returns the constant reply."""
def __init__(self, sink: list[str], reply: str, *, tokens_per_reply: int = 8) -> None:
super().__init__(reply, sink, tokens_per_reply=tokens_per_reply)
@pytest.fixture()
def make_recording_client_factory() -> Callable[
[str], tuple[Callable[[str], BaseChatClient], list[str]]
]:
"""Return a maker that builds a per-role client factory recording every prompt blob into a
shared list. Returns ``(factory, recorded_prompts)`` so the test inspects what reached the
prompt across the whole run (debate rounds + generation)."""
def _make(reply: str) -> tuple[Callable[[str], BaseChatClient], list[str]]:
sink: list[str] = []
def factory(role: str) -> BaseChatClient:
return _RecordingChatClient(sink, reply)
return factory, sink
return _make
@pytest.fixture()
def fresh_store() -> VerdictStore:
return VerdictStore(verdicts=[])
@pytest.fixture()
def seeded_store() -> VerdictStore:
return seed_store()
@pytest.fixture()
def docs_dir(tmp_path) -> str:
d = tmp_path / "docs"
d.mkdir()
(d / "cost.txt").write_text(
"Licence unit price renegotiation reduced the office-suite cost for the head office.",
encoding="utf-8",
)
return str(d)
# ------------------------------------------------------------------------------------------------
# Fase 1b — the FULL-RUN contract, in ONE copy (kø-(p): a second copy of an assertion drifts).
# ------------------------------------------------------------------------------------------------
#: What the paid run must fell, stated as an assertion rather than as prose. The open honesty limit
#: after økt 37 is narrow and specific: *"that the emitted structured schema IS accepted by the LIVE
#: endpoint is NOT verified — the tests prove conformance with the DOCUMENTED subset, not
#: acceptance."* So the contract asserts schema ACCEPTANCE, never model JUDGEMENT.
#:
#: The discriminator is an artefact this repo already owns: ``{run_id}-parse-failures.json`` is
#: written if and ONLY if some reply failed to parse (økt 35 invariant — "the file's presence is the
#: signal"). Its ABSENCE beside a RunResult therefore proves that every generation reply came back
#: in the requested shape, which is exactly what "the live endpoint honoured the schema" means.
#:
#: ``validator_decision`` is the second half: it mirrors the VALIDATOR alone (never the checker), so
#: reading it proves the deterministic gate actually ran on a parsed candidate. Both ``validated``
#: and ``rejected`` satisfy the contract — a P90 rejection is a run that CONCLUDED, and demanding
#: ``validated`` would be asserting that the model reasons well, which no schema can promise and
#: which one paid run could not establish anyway.
def assert_full_run_contract(result: RunResult, outbox_dir: str | Path, run_id: str) -> None:
"""Assert the Fase 1b full-run contract on a completed ``run_project`` result.
Two things, and deliberately nothing else:
1. **No parse-failure artefact** — every reply parsed, i.e. the live endpoint accepted the
emitted ``response_format`` schema. This is the honesty limit being felled.
2. **The validator was reached and decided** — ``provenance.validator_decision`` is one of the
two decisions the deterministic gate emits.
Deliberately NOT asserted: ``checker_verdict``, token counts, ``validated_count``, or the
content of the proposal. Those are model-judgement claims, and one run cannot carry them.
"""
artefact = Path(outbox_dir) / f"{run_id}-parse-failures.json"
if artefact.exists():
# Quote the evidence in the failure message: the whole point of økt 35 was that the operator
# should never again have to guess WHY a reply did not parse.
raise AssertionError(
f"the endpoint did NOT honour the structured schema — {artefact.name} exists.\n"
f"{artefact.read_text(encoding='utf-8')[:2000]}"
)
assert result.provenance.validator_decision in {"validated", "rejected"}, (
"the deterministic validator never decided — the run did not reach the gate with a "
f"parsed candidate (validator_decision={result.provenance.validator_decision!r})"
)
#: P13b: the §7 ownership stamp as the PINNED WRITER emits it. ONE copy, shared by the four ingest
#: tests that assert the emitted value, because four literals for one emitter fact are four places a
#: later okf release can leave half-corrected (the kø-(p) rule, and exactly how the pre-V1 form
#: survived in four asserts until P13 measured it). The actor token is okf's, not ours: measured
#: 2026-09-12 against llm-ingestion-okf 0.8.5, which writes `{ by: process:okf-ingest, at: <the
#: ingested_at the caller passed> }` where 0.3.2 wrote the literal `true`.
#:
#: A curated half-stamp written BY THIS REPO (`okf.write_concept_file`) is a different fact and keeps
#: its own literal — `tests/test_okf.py` round-trips `generated: true` and must not be pointed here.
def expected_generated_stamp(ingested_at: str) -> str:
"""The exact ``generated`` value okf's materializer writes for ``ingested_at``."""
return f"{{ by: process:okf-ingest, at: {ingested_at} }}"