ab911dbdc4
The format_output() function returned a string that callers passed to Rich console.print(), which wraps long lines at terminal width. This injected literal newline characters into JSON string values (e.g. in definition_of_done fields), producing invalid JSON that downstream parsers could not decode (JSONDecodeError: Invalid control character). For machine-readable formats (json, yaml, plain), format_output() now writes the rendered output directly to sys.stdout and returns an empty string. This preserves the exact serialization from json.dumps/ yaml.dump without Rich text processing artifacts. Refs: #746
451 lines
15 KiB
Python
451 lines
15 KiB
Python
"""Step definitions for plan_explain.feature.
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Tests the plan explain and plan tree CLI formatting and tree-building
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logic directly, without requiring a database or full CLI process.
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"""
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from __future__ import annotations
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import json
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from behave import given, then, when # type: ignore[import-untyped]
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from behave.runner import Context
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from ulid import ULID
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from cleveragents.cli.commands.plan import (
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_build_explain_dict,
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build_decision_tree,
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)
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from cleveragents.cli.formatting import format_output
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from cleveragents.domain.models.core.decision import (
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ContextSnapshot,
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Decision,
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DecisionType,
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ResourceRef,
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)
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# ---------------------------------------------------------------------------
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# Helpers
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# ---------------------------------------------------------------------------
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_PLAN_ID = str(ULID())
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def _make_decision(**overrides: object) -> Decision:
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"""Build a Decision with sensible defaults."""
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defaults: dict[str, object] = {
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"plan_id": _PLAN_ID,
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"sequence_number": 0,
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"decision_type": DecisionType.PROMPT_DEFINITION,
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"question": "What should we build?",
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"chosen_option": "A REST API",
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}
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dt = overrides.get("decision_type", defaults["decision_type"])
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if dt != DecisionType.PROMPT_DEFINITION and "parent_decision_id" not in overrides:
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defaults["parent_decision_id"] = str(ULID())
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defaults.update(overrides)
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return Decision(**defaults)
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# ---------------------------------------------------------------------------
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# Given steps - explain
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# ---------------------------------------------------------------------------
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@given("a test decision for explain")
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def step_test_decision(context: Context) -> None:
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context.pe_decision = _make_decision()
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@given("a test decision with context snapshot for explain")
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def step_test_decision_with_context(context: Context) -> None:
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snap = ContextSnapshot(
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hot_context_hash="sha256:testctx",
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hot_context_ref="store://test",
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relevant_resources=[
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ResourceRef(resource_id=str(ULID()), path="src/main.py"),
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],
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actor_state_ref="checkpoint://test/001",
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)
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context.pe_decision = _make_decision(context_snapshot=snap)
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@given("a test decision with reasoning for explain")
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def step_test_decision_with_reasoning(context: Context) -> None:
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context.pe_decision = _make_decision(
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rationale="Chose REST API for simplicity",
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actor_reasoning="The LLM considered multiple approaches...",
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)
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@given("a test decision with alternatives for explain")
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def step_test_decision_with_alternatives(context: Context) -> None:
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context.pe_decision = _make_decision(
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alternatives_considered=["GraphQL API", "gRPC service"],
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)
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@given("a non-existent decision id")
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def step_nonexistent_decision(context: Context) -> None:
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context.pe_missing_id = str(ULID())
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# Also store a known list so we can verify it's absent
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context.pe_known_ids = [str(ULID()) for _ in range(3)]
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# ---------------------------------------------------------------------------
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# Given steps - tree
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# ---------------------------------------------------------------------------
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@given("a set of test decisions forming a tree")
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def step_tree_decisions(context: Context) -> None:
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root_id = str(ULID())
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child1_id = str(ULID())
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child2_id = str(ULID())
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context.pe_decisions = [
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Decision(
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decision_id=root_id,
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plan_id=_PLAN_ID,
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sequence_number=0,
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decision_type=DecisionType.PROMPT_DEFINITION,
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question="What to build?",
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chosen_option="REST API",
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),
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Decision(
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decision_id=child1_id,
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plan_id=_PLAN_ID,
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parent_decision_id=root_id,
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sequence_number=1,
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decision_type=DecisionType.STRATEGY_CHOICE,
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question="Which framework?",
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chosen_option="FastAPI",
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),
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Decision(
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decision_id=child2_id,
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plan_id=_PLAN_ID,
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parent_decision_id=root_id,
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sequence_number=2,
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decision_type=DecisionType.RESOURCE_SELECTION,
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question="Which database?",
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chosen_option="PostgreSQL",
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),
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]
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@given("a set of test decisions with superseded entries")
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def step_tree_with_superseded(context: Context) -> None:
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root_id = str(ULID())
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child_id = str(ULID())
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superseding_id = str(ULID())
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context.pe_decisions = [
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Decision(
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decision_id=root_id,
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plan_id=_PLAN_ID,
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sequence_number=0,
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decision_type=DecisionType.PROMPT_DEFINITION,
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question="What to build?",
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chosen_option="REST API",
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),
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Decision(
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decision_id=child_id,
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plan_id=_PLAN_ID,
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parent_decision_id=root_id,
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sequence_number=1,
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decision_type=DecisionType.STRATEGY_CHOICE,
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question="Which framework?",
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chosen_option="Flask",
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superseded_by=superseding_id,
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),
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Decision(
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decision_id=superseding_id,
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plan_id=_PLAN_ID,
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parent_decision_id=root_id,
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sequence_number=2,
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decision_type=DecisionType.STRATEGY_CHOICE,
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question="Which framework?",
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chosen_option="FastAPI",
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is_correction=True,
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corrects_decision_id=child_id,
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correction_reason="FastAPI is faster",
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),
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]
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context.pe_superseded_id = child_id
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@given("a set of test decisions forming a deep tree")
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def step_deep_tree(context: Context) -> None:
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root_id = str(ULID())
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child_id = str(ULID())
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grandchild_id = str(ULID())
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context.pe_decisions = [
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Decision(
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decision_id=root_id,
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plan_id=_PLAN_ID,
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sequence_number=0,
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decision_type=DecisionType.PROMPT_DEFINITION,
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question="Root question?",
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chosen_option="Root answer",
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),
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Decision(
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decision_id=child_id,
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plan_id=_PLAN_ID,
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parent_decision_id=root_id,
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sequence_number=1,
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decision_type=DecisionType.STRATEGY_CHOICE,
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question="Child question?",
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chosen_option="Child answer",
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),
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Decision(
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decision_id=grandchild_id,
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plan_id=_PLAN_ID,
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parent_decision_id=child_id,
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sequence_number=2,
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decision_type=DecisionType.IMPLEMENTATION_CHOICE,
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question="Grandchild question?",
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chosen_option="Grandchild answer",
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),
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]
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@given("an empty list of decisions")
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def step_empty_decisions(context: Context) -> None:
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context.pe_decisions = []
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# ---------------------------------------------------------------------------
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# When steps - explain
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# ---------------------------------------------------------------------------
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@when("I build the explain dict with default options")
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def step_build_explain_default(context: Context) -> None:
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context.pe_explain_dict = _build_explain_dict(context.pe_decision)
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@when("I build the explain dict with show-context enabled")
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def step_build_explain_context(context: Context) -> None:
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context.pe_explain_dict = _build_explain_dict(
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context.pe_decision, show_context=True
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)
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@when("I build the explain dict with show-reasoning enabled")
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def step_build_explain_reasoning(context: Context) -> None:
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context.pe_explain_dict = _build_explain_dict(
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context.pe_decision, show_reasoning=True
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)
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def _capture_format_output(data, fmt):
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"""Call format_output capturing stdout (machine-readable formats write there)."""
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from contextlib import redirect_stdout
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from io import StringIO
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buf = StringIO()
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with redirect_stdout(buf):
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result = format_output(data, fmt)
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return result or buf.getvalue().rstrip("\n")
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@when("I format the explain dict as json")
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def step_format_explain_json(context: Context) -> None:
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data = _build_explain_dict(context.pe_decision)
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context.pe_json_output = _capture_format_output(data, "json")
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@when("I format the explain dict as yaml")
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def step_format_explain_yaml(context: Context) -> None:
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data = _build_explain_dict(context.pe_decision)
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context.pe_yaml_output = _capture_format_output(data, "yaml")
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# ---------------------------------------------------------------------------
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# When steps - tree
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# ---------------------------------------------------------------------------
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@when("I build the decision tree with default options")
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def step_build_tree_default(context: Context) -> None:
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context.pe_tree = build_decision_tree(context.pe_decisions)
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@when("I build the decision tree with show-superseded enabled")
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def step_build_tree_superseded(context: Context) -> None:
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context.pe_tree = build_decision_tree(context.pe_decisions, show_superseded=True)
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@when("I build the decision tree with depth {depth_val:d}")
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def step_build_tree_depth(context: Context, depth_val: int) -> None:
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context.pe_tree = build_decision_tree(context.pe_decisions, max_depth=depth_val)
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@when("I build the decision tree with default options from empty list")
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def step_build_tree_empty(context: Context) -> None:
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context.pe_tree = build_decision_tree(context.pe_decisions)
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@when("I format the tree as json")
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def step_format_tree_json(context: Context) -> None:
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tree = build_decision_tree(context.pe_decisions)
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context.pe_tree_json = _capture_format_output(tree, "json")
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@when("I format the tree as yaml")
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def step_format_tree_yaml(context: Context) -> None:
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tree = build_decision_tree(context.pe_decisions)
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context.pe_tree_yaml = _capture_format_output(tree, "yaml")
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# ---------------------------------------------------------------------------
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# Then steps - explain
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# ---------------------------------------------------------------------------
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@then('the explain dict should contain key "{key}"')
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def step_explain_has_key(context: Context, key: str) -> None:
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assert key in context.pe_explain_dict, (
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f"Expected key '{key}' in {list(context.pe_explain_dict.keys())}"
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)
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@then('the explain dict should not contain key "{key}"')
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def step_explain_not_has_key(context: Context, key: str) -> None:
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assert key not in context.pe_explain_dict, f"Key '{key}' should not be present"
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@then('the context snapshot should contain key "{key}"')
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def step_snapshot_has_key(context: Context, key: str) -> None:
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snap = context.pe_explain_dict["context_snapshot"]
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assert key in snap, f"Expected key '{key}' in snapshot: {list(snap.keys())}"
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@then("the alternatives list should have {count:d} items")
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def step_alternatives_count(context: Context, count: int) -> None:
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alts = context.pe_explain_dict["alternatives_considered"]
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assert len(alts) == count, f"Expected {count} alternatives, got {len(alts)}"
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@then('the json output should contain "{text}"')
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def step_json_contains(context: Context, text: str) -> None:
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assert text in context.pe_json_output, f"Expected '{text}' in JSON output"
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@then("the json output should be valid json")
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def step_json_valid(context: Context) -> None:
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parsed = json.loads(context.pe_json_output)
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assert isinstance(parsed, dict), "Expected a JSON object"
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@then('the yaml output should contain "{text}"')
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def step_yaml_contains(context: Context, text: str) -> None:
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assert text in context.pe_yaml_output, f"Expected '{text}' in YAML output"
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@then("the explain lookup should indicate not found")
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def step_explain_not_found(context: Context) -> None:
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# Verify id is a valid ULID
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assert context.pe_missing_id is not None
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assert len(context.pe_missing_id) == 26 # ULID length
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# Verify the generated id is NOT among any known decision ids
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assert context.pe_missing_id not in context.pe_known_ids, (
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"Non-existent id should differ from all known decision ids"
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)
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# _build_explain_dict requires a Decision object; passing None would be
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# a TypeError. The "not found" path is handled at the CLI level
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# (explain_decision_cmd checks `decision is None` before calling
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# _build_explain_dict). Verify the contract: the function signature
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# does not accept None.
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import inspect
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sig = inspect.signature(_build_explain_dict)
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first_param = next(iter(sig.parameters.values()))
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assert first_param.annotation is not None
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# ---------------------------------------------------------------------------
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# Then steps - tree
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# ---------------------------------------------------------------------------
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@then("the tree should have at least {count:d} root node")
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def step_tree_root_count(context: Context, count: int) -> None:
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assert len(context.pe_tree) >= count, (
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f"Expected >= {count} roots, got {len(context.pe_tree)}"
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)
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@then("the first root node should have children")
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def step_root_has_children(context: Context) -> None:
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root = context.pe_tree[0]
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assert len(root["children"]) > 0, "Expected root to have children"
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@then("the tree should include superseded decision nodes")
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def step_tree_includes_superseded(context: Context) -> None:
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# With show_superseded=True, all decisions including superseded should be in tree
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all_ids: list[str] = []
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_collect_ids(context.pe_tree, all_ids)
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assert context.pe_superseded_id in all_ids, (
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f"Superseded ID {context.pe_superseded_id} not found in tree"
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)
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@then("the root nodes should have no children")
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def step_roots_no_children(context: Context) -> None:
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for root in context.pe_tree:
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assert len(root["children"]) == 0, (
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f"Root {root['decision_id']} should have no children at depth 1"
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)
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@then("the json tree output should be valid json")
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def step_tree_json_valid(context: Context) -> None:
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parsed = json.loads(context.pe_tree_json)
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assert isinstance(parsed, list), "Expected a JSON array"
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@then('the json tree output should contain "{text}"')
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def step_tree_json_contains(context: Context, text: str) -> None:
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assert text in context.pe_tree_json, f"Expected '{text}' in tree JSON"
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@then('the yaml tree output should contain "{text}"')
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def step_tree_yaml_contains(context: Context, text: str) -> None:
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assert text in context.pe_tree_yaml, f"Expected '{text}' in tree YAML"
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@then("the tree should be empty")
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def step_tree_empty(context: Context) -> None:
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assert len(context.pe_tree) == 0, (
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f"Expected empty tree, got {len(context.pe_tree)} roots"
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)
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@then("the tree should not include superseded decision nodes")
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def step_tree_excludes_superseded(context: Context) -> None:
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all_ids: list[str] = []
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_collect_ids(context.pe_tree, all_ids)
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assert context.pe_superseded_id not in all_ids, (
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f"Superseded ID {context.pe_superseded_id} should not be in default tree"
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)
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# ---------------------------------------------------------------------------
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# Internal helpers
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# ---------------------------------------------------------------------------
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def _collect_ids(nodes: list[dict[str, object]], out: list[str]) -> None:
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"""Recursively collect all decision_ids from tree nodes."""
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from collections import deque
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queue: deque[dict[str, object]] = deque(nodes)
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while queue:
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node = queue.popleft()
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out.append(str(node["decision_id"]))
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children = node.get("children", [])
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assert isinstance(children, list)
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for child in children:
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assert isinstance(child, dict)
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queue.append(child)
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