from __future__ import annotations

from app.schemas.pmflow_ai_turn_runtime import PMFlowAITurnState
from app.schemas.rag import RAGAskRequest
from app.services.pmflow_ai_turn_runtime_service import PMFlowAITurnRuntimeService
from app.services.pmflow_ai_turn_state_reviser import PMFlowAITurnStateReviser


def test_packet_e_goal_frames_drive_working_state_without_legacy_decision_fields() -> None:
    state = PMFlowAITurnRuntimeService(object(), tenant_id=1).build_initial_turn_state(
        request=RAGAskRequest(question="现在最新的 Agent 应用机会是什么"),
        route_plan={"legacy_policy": "internal_only"},
        turn_hypothesis={
            "normalized_goal": "判断当前最新 Agent 应用机会",
            "desired_outcome": "给出机会、风险和下一步",
            "goal_frames": [
                {
                    "frame_id": "agent-opportunity",
                    "operation_kind": "judge_direction",
                    "target_scope": {
                        "scope_type": "external_public",
                        "binding_strength": "surface",
                        "source": "turn_goal_assessment",
                    },
                    "target_object_requirement": "none",
                    "answer_shape": "strategic_judgement",
                    "confidence": 0.82,
                }
            ],
            "operation_gaps": [
                {
                    "key": "fresh_public_market_evidence",
                    "gap_type": "freshness_gap",
                    "blocking": False,
                    "user_actionable": False,
                    "system_action_hint": "external_search",
                    "reason": "需要当前公开市场证据。",
                }
            ],
            "can_answer_with_assumptions": True,
            "primary_object": {"binding_strength": "none"},
        },
    )

    decision = PMFlowAITurnRuntimeService(object(), tenant_id=1).assess_sufficiency(state)

    assert state.selected_frame is not None
    assert state.selected_frame.operation_kind == "judge_direction"
    assert state.answer_state.answer_shape == "strategic_judgement"
    assert [gap.key for gap in state.operation_gaps] == ["fresh_public_market_evidence"]
    assert decision.next_action_type == "external_search"


def test_packet_e_goal_frames_beat_conflicting_legacy_fields() -> None:
    state = PMFlowAITurnRuntimeService(object(), tenant_id=1).build_initial_turn_state(
        request=RAGAskRequest(question="暂存想法里有没有值得推进的"),
        route_plan={},
        turn_hypothesis={
            "normalized_goal": "列出暂存想法",
            "answer_shape": "status_answer",
            "decision_type": "project_status",
            "evidence_needs": ["project_status"],
            "goal_frames": [
                {
                    "frame_id": "saved-ideas",
                    "operation_kind": "list_collection",
                    "target_scope": {
                        "scope_type": "current_space",
                        "binding_strength": "surface",
                        "source": "turn_goal_assessment",
                    },
                    "target_collection": {
                        "object_type": "saved_idea",
                        "required": True,
                    },
                    "target_object_requirement": "none",
                    "answer_shape": "fact_list",
                    "confidence": 0.86,
                }
            ],
            "operation_gaps": [
                {
                    "key": "saved_ideas",
                    "gap_type": "system_evidence_gap",
                    "system_action_hint": "inspect_saved_ideas",
                    "reason": "需要读取暂存想法集合。",
                }
            ],
            "can_answer_with_assumptions": True,
        },
    )

    action = PMFlowAITurnRuntimeService(object(), tenant_id=1).select_next_minimal_action(state)

    assert state.selected_frame is not None
    assert state.selected_frame.operation_kind == "list_collection"
    assert state.answer_state.answer_shape == "fact_list"
    assert action is not None
    assert action.action_type == "inspect_saved_ideas"


def test_packet_e_user_actionable_operation_gap_controls_clarification_gate() -> None:
    state = PMFlowAITurnRuntimeService(object(), tenant_id=1).build_initial_turn_state(
        request=RAGAskRequest(question="帮我处理一下"),
        route_plan={},
        turn_hypothesis={
            "normalized_goal": "确认执行动作边界",
            "goal_frames": [
                {
                    "frame_id": "execution-boundary",
                    "operation_kind": "guide_execution",
                    "target_scope": {
                        "scope_type": "current_space",
                        "binding_strength": "none",
                        "source": "turn_goal_assessment",
                    },
                    "target_object_requirement": "authorization",
                    "answer_shape": "execution_guidance",
                    "confidence": 0.7,
                }
            ],
            "operation_gaps": [
                {
                    "key": "execution_boundary_required",
                    "gap_type": "user_clarification_gap",
                    "blocking": True,
                    "user_actionable": True,
                    "customer_question": "请补充要处理的对象和动作边界。",
                    "reason": "执行前缺少对象和动作边界。",
                }
            ],
            "can_answer_with_assumptions": False,
        },
    )

    decision = PMFlowAITurnRuntimeService(object(), tenant_id=1).assess_sufficiency(state)

    assert decision.must_ask_user is True
    assert decision.next_action_type == "ask_clarification"
    assert state.operation_gaps[0].user_actionable is True


def test_packet_e_reviser_accepts_direct_goal_frame_payload() -> None:
    state = PMFlowAITurnState()
    PMFlowAITurnStateReviser().initialize_working_state(
        turn_state=state,
        hypothesis={
            "goal_frames": [
                {
                    "frame_id": "assistant-profile",
                    "operation_kind": "explain_assistant",
                    "target_scope": {
                        "scope_type": "current_space",
                        "binding_strength": "surface",
                        "source": "turn_goal_assessment",
                    },
                    "target_object_requirement": "none",
                    "answer_shape": "general_answer",
                    "confidence": 0.9,
                }
            ],
            "operation_gaps": [],
            "decision_type": "project_status",
            "evidence_needs": ["project_status"],
        },
    )

    assert state.selected_frame is not None
    assert state.selected_frame.operation_kind == "explain_assistant"
    assert state.operation_gaps == []