PMFlow/backend/tests/test_pmflow_ai_object_ledger_packet_i.py

from __future__ import annotations

from app.schemas.rag import RAGAskRequest
from app.schemas.pmflow_ai_turn_runtime import (
    PMFlowAIAnswerState,
    PMFlowAIGoalFrame,
    PMFlowAIRuntimeAction,
    PMFlowAITargetScope,
    PMFlowAITurnEvidenceState,
    PMFlowAITurnObjectRef,
    PMFlowAITurnObjectState,
    PMFlowAITurnState,
)
from app.services.pmflow_ai_turn_object_ledger import (
    build_object_ledger_from_payload,
    merge_object_ledger_into_context_packet,
    object_ledger_from_context_capsules,
    upsert_object_ledger_capsule,
)
from app.services.pmflow_ai_turn_state_reviser import PMFlowAITurnStateReviser
from app.services.pmflow_ai_turn_runtime_service import PMFlowAITurnRuntimeService


def _service() -> PMFlowAITurnRuntimeService:
    return PMFlowAITurnRuntimeService(object(), tenant_id=1)


def test_packet_i_builds_customer_safe_object_ledger_from_turn_payload() -> None:
    payload = {
        "answer_mode": "turn_runtime_state_answer",
        "pmflow_ai_turn_state": {
            "customer_packet_draft": {
                "items": [
                    {
                        "object_type": "project",
                        "object_ref": "project:141",
                        "title": "童析",
                        "status": "进行中",
                    }
                ]
            }
        },
        "customer_interaction_context_packet": {"visible_objects": []},
    }

    ledger = build_object_ledger_from_payload(payload=payload)

    assert ledger["current_focus_object"]["object_ref"] == "project:141"
    assert ledger["current_focus_object"]["title"] == "童析"
    assert ledger["last_shown_objects"] == [
        {"object_type": "project", "object_ref": "project:141", "title": "童析", "object_id": 141, "status": "进行中"}
    ]
    merged = merge_object_ledger_into_context_packet(context_packet={}, object_ledger=ledger)
    assert merged["current_focus_object"]["object_ref"] == "project:141"
    assert merged["last_shown_objects"][0]["title"] == "童析"


def test_packet_i_upserts_ledger_into_session_context_capsules() -> None:
    ledger = build_object_ledger_from_payload(
        payload={
            "pmflow_ai_turn_state": {
                "customer_packet_draft": {
                    "items": [{"object_type": "project", "object_ref": "project:141", "title": "童析"}]
                }
            }
        }
    )

    capsules = upsert_object_ledger_capsule(capsules=[{"capsule_type": "other", "value": 1}], object_ledger=ledger)
    loaded = object_ledger_from_context_capsules(capsules)

    assert capsules[0]["capsule_type"] == "pmflow_ai_object_ledger"
    assert loaded["current_focus_object"]["object_ref"] == "project:141"
    assert capsules[1]["capsule_type"] == "other"


def test_packet_i_session_object_ledger_binds_weak_followup_primary_object() -> None:
    ledger = {
        "packet_version": "pmflow_ai_object_ledger.v1",
        "current_focus_object": {
            "object_type": "project",
            "object_ref": "project:141",
            "title": "童析",
        },
        "last_shown_objects": [],
        "recent_objects": [],
    }

    state = _service().build_initial_turn_state(
        request=RAGAskRequest(question="这个项目你觉得发展怎么样"),
        route_plan={},
        conversation_context={"object_ledger": ledger},
        turn_hypothesis={
            "normalized_goal": "判断当前项目发展状态",
            "answer_shape": "strategic_judgement",
            "primary_object": {"binding_strength": "none"},
            "goal_frames": [
                {
                    "frame_id": "followup-project-judgement",
                    "operation_kind": "inspect_object",
                    "target_scope": {"scope_type": "current_project", "binding_strength": "workspace"},
                    "target_object_requirement": "single",
                    "answer_shape": "strategic_judgement",
                }
            ],
            "operation_gaps": [
                {
                    "key": "project_status_snapshot",
                    "gap_type": "system_evidence_gap",
                    "blocking": False,
                    "user_actionable": False,
                    "system_action_hint": "需要读取项目状态快照",
                    "reason": "需要先读取绑定项目证据。",
                }
            ],
            "can_answer_with_assumptions": False,
        },
    )

    assert state.object_state.primary_object is not None
    assert state.object_state.primary_object.object_ref == "project:141"
    assert state.object_state.primary_object.binding_strength == "session_object_ledger"


def test_packet_i_system_probe_wins_before_user_clarification_when_object_is_bound() -> None:
    ledger = {
        "packet_version": "pmflow_ai_object_ledger.v1",
        "current_focus_object": {
            "object_type": "project",
            "object_ref": "project:141",
            "title": "童析",
        },
    }

    state = _service().build_initial_turn_state(
        request=RAGAskRequest(question="这个项目你觉得发展怎么样"),
        route_plan={},
        conversation_context={"object_ledger": ledger},
        turn_hypothesis={
            "normalized_goal": "判断当前项目发展状态",
            "answer_shape": "strategic_judgement",
            "primary_object": {"binding_strength": "none"},
            "goal_frames": [
                {
                    "frame_id": "project-development-judgement",
                    "operation_kind": "inspect_object",
                    "target_scope": {"scope_type": "current_project", "binding_strength": "workspace"},
                    "target_object_requirement": "single",
                    "answer_shape": "strategic_judgement",
                }
            ],
            "operation_gaps": [
                {
                    "key": "project_status_snapshot",
                    "gap_type": "system_evidence_gap",
                    "blocking": False,
                    "user_actionable": False,
                    "system_action_hint": "需要读取项目状态快照",
                    "reason": "需要读取绑定项目状态证据。",
                },
                {
                    "key": "user_metric_preference",
                    "gap_type": "user_clarification_gap",
                    "blocking": True,
                    "user_actionable": True,
                    "customer_question": "你更关心增长、交付还是风险？",
                    "reason": "补充维度可提升判断质量。",
                },
            ],
            "needs_user_input": True,
            "can_answer_with_assumptions": False,
        },
    )

    decision = _service().assess_sufficiency(state)

    assert decision.must_ask_user is False
    assert decision.next_action_type == "inspect_project_status"


def test_packet_x_bound_project_blocks_external_search_until_project_operating_probe() -> None:
    ledger = {
        "packet_version": "pmflow_ai_object_ledger.v1",
        "current_focus_object": {
            "object_type": "project",
            "object_ref": "project:141",
            "title": "童析",
        },
    }

    state = _service().build_initial_turn_state(
        request=RAGAskRequest(question="现在这个项目怎么样了，详细跟我说下"),
        route_plan={},
        conversation_context={"object_ledger": ledger},
        turn_hypothesis={
            "normalized_goal": "获取当前项目整体状态与关键进展细节",
            "answer_shape": "composite_answer",
            "primary_object": {"binding_strength": "none"},
            "object_binding_decision": {"decision": "accept_previous_focus"},
            "goal_frames": [
                {
                    "frame_id": "wrong-external-composite",
                    "operation_kind": "judge_direction",
                    "target_scope": {"scope_type": "external_public", "binding_strength": "surface"},
                    "target_object_requirement": "none",
                    "source_policy": "external",
                    "answer_shape": "composite_answer",
                }
            ],
            "operation_gaps": [
                {
                    "key": "public_project_evidence",
                    "gap_type": "freshness_gap",
                    "blocking": False,
                    "user_actionable": False,
                    "system_action_hint": "external_search",
                    "reason": "错误地要求外部公开证据。",
                }
            ],
            "can_answer_with_assumptions": True,
        },
    )

    decision = _service().assess_sufficiency(state)
    action = _service().select_next_minimal_action(state)

    assert state.object_state.primary_object is not None
    assert state.object_state.primary_object.object_ref == "project:141"
    assert decision.next_action_type == "inspect_project_status"
    assert action is not None
    assert action.action_type == "inspect_project_status"
    assert all(item.action_type != "external_search" for item in state.action_state.candidate_actions[:1])


def test_packet_z_final_answer_wrong_source_verifier_forces_project_probe() -> None:
    ledger = {
        "packet_version": "pmflow_ai_object_ledger.v1",
        "current_focus_object": {
            "object_type": "project",
            "object_ref": "project:141",
            "title": "童析",
        },
    }
    state = _service().build_initial_turn_state(
        request=RAGAskRequest(question="现在这个项目怎么样了，详细跟我说下"),
        route_plan={},
        conversation_context={"object_ledger": ledger},
        turn_hypothesis={
            "normalized_goal": "获取当前项目整体状态与关键进展细节",
            "answer_shape": "composite_answer",
            "primary_object": {"binding_strength": "none"},
            "object_binding_decision": {"decision": "accept_previous_focus"},
            "goal_frames": [
                {
                    "frame_id": "wrong-final-answer-frame",
                    "operation_kind": "judge_direction",
                    "target_scope": {"scope_type": "external_public", "binding_strength": "surface"},
                    "source_policy": "external",
                    "answer_shape": "composite_answer",
                }
            ],
            "operation_gaps": [],
            "can_answer_with_assumptions": True,
        },
    )

    failure = _service()._verify_runtime_payload(
        turn_state=state,
        payload={
            "_runtime_payload_kind": "final_answer",
            "answer": "当前无法提供该项目具体状态。",
            "source_policy": "external",
            "sources": [{"source_type": "external_public", "label": "外部公开来源"}],
        },
    )

    assert failure is not None
    assert failure.failure_type == "wrong_source_or_missing_project_operating_state"
    assert failure.next_action_hint == "inspect_project_status"
    assert failure.state_patch["needs_internal_evidence"] is True


def test_packet_aa_verifier_recovery_keeps_required_project_probe_executable() -> None:
    frame = PMFlowAIGoalFrame(
        frame_id="wrong-source-frame",
        operation_kind="judge_direction",
        target_scope=PMFlowAITargetScope(scope_type="external_public", binding_strength="surface"),
        answer_shape="composite_answer",
    )
    state = PMFlowAITurnState(
        selected_frame=frame,
        candidate_frames=[frame],
        answer_state=PMFlowAIAnswerState(answer_shape="composite_answer"),
        object_state=PMFlowAITurnObjectState(
            primary_object=PMFlowAITurnObjectRef(
                object_type="project",
                object_ref="project:141",
                title="童析",
                binding_strength="session_object_ledger",
            )
        ),
        evidence_state=PMFlowAITurnEvidenceState(),
    )

    failure = _service()._verify_runtime_payload(
        turn_state=state,
        payload={"_runtime_payload_kind": "final_answer", "answer": "当前无法提供项目具体状态。"},
    )
    PMFlowAITurnStateReviser().revise_from_verification(turn_state=state, failure=failure)

    decision = _service().assess_sufficiency(state)
    action = _service().select_next_minimal_action(state)

    assert failure is not None
    assert decision.next_action_type == "inspect_project_status"
    assert action is not None
    assert action.action_type == "inspect_project_status"
    assert state.completed is False


def test_packet_j_new_project_topic_does_not_inherit_previous_project_focus() -> None:
    ledger = {
        "packet_version": "pmflow_ai_object_ledger.v1",
        "current_focus_object": {
            "object_type": "project",
            "object_ref": "project:141",
            "title": "童析",
        },
    }

    state = _service().build_initial_turn_state(
        request=RAGAskRequest(question="解决信息投流公司大量员工混剪视频的问题，通过AI自动化混剪降低人工成本"),
        route_plan={},
        conversation_context={"object_ledger": ledger},
        turn_hypothesis={
            "normalized_goal": "评估一个新的AI视频混剪自动化项目方向",
            "answer_shape": "strategic_judgement",
            "primary_object": {"binding_strength": "none"},
            "object_binding_decision": {
                "decision": "create_new_focus",
                "rejected_object_ref": "project:141",
                "new_focus_title": "信息投流公司AI自动化混剪",
            },
            "goal_frames": [
                {
                    "frame_id": "new-video-automation-direction",
                    "operation_kind": "guide_execution",
                    "target_scope": {"scope_type": "unspecified", "binding_strength": "none"},
                    "target_object_requirement": "none",
                    "answer_shape": "strategic_judgement",
                }
            ],
            "operation_gaps": [
                {
                    "key": "company_context",
                    "gap_type": "user_clarification_gap",
                    "blocking": True,
                    "user_actionable": True,
                    "customer_question": "请补充典型混剪工作流。",
                    "reason": "缺少业务上下文。",
                },
                {
                    "key": "old_project_scope_rejected",
                    "gap_type": "scope_gap",
                    "blocking": False,
                    "user_actionable": False,
                    "system_action_hint": "previous focus is unrelated to this new idea",
                    "reason": "上一轮项目与本轮新想法无关。",
                },
            ],
            "needs_user_input": True,
            "can_answer_with_assumptions": False,
        },
    )

    decision = _service().assess_sufficiency(state)
    action_types = [item.action_type for item in state.action_state.candidate_actions]

    assert state.object_state.primary_object is not None
    assert state.object_state.primary_object.object_ref == ""
    assert state.object_state.primary_object.object_type == "new_idea"
    assert state.object_state.primary_object.binding_strength == "active_workspace_strong"
    assert "inspect_project_status" not in action_types
    assert decision.next_action_type == "ask_clarification"


def test_packet_j_off_topic_project_evidence_is_not_absorbed_into_new_idea_goal() -> None:
    state = _service().build_initial_turn_state(
        request=RAGAskRequest(question="解决信息投流公司大量员工混剪视频的问题，通过AI自动化混剪降低人工成本"),
        route_plan={},
        turn_hypothesis={
            "normalized_goal": "评估一个新的AI视频混剪自动化项目方向",
            "answer_shape": "strategic_judgement",
            "primary_object": {"binding_strength": "none"},
            "object_binding_decision": {"decision": "create_new_focus", "rejected_object_ref": "project:141"},
            "goal_frames": [
                {
                    "frame_id": "new-video-automation-direction",
                    "operation_kind": "guide_execution",
                    "target_scope": {"scope_type": "unspecified", "binding_strength": "none"},
                    "target_object_requirement": "none",
                    "answer_shape": "strategic_judgement",
                }
            ],
            "can_answer_with_assumptions": True,
        },
    )

    updated = _service().absorb_evidence(
        turn_state=state,
        action=PMFlowAIRuntimeAction(
            action_id="inspect_project_status",
            action_type="inspect_project_status",
            reason="读取项目状态",
            tool_name="project_status_evidence_tool",
        ),
        payload={
            "_runtime_payload_kind": "evidence",
            "runtime_evidence_tool_result": {
                "tool_name": "project_status_evidence_tool",
                "action_type": "inspect_project_status",
                "findings": [
                    {
                        "fact": "童析 当前状态证据：项目状态 active",
                        "source": "PMFlow 项目状态证据",
                        "confidence": "high",
                    }
                ],
                "sources": [{"source": "project_status", "display_label": "PMFlow 项目状态证据"}],
                "remaining_gaps": [],
                "confidence": "high",
                "summary": "读取项目状态证据，得到 1 条事实。",
            },
        },
        started_at=0,
    )

    assert updated.evidence_state.known_facts == []
    assert "off_topic_evidence_excluded" in updated.evidence_state.stale_or_missing