import pytest from app.services.adaptive_rag_service.mixin_answer_mainline import AdaptiveRAGAnswerMainlineMixin from app.services.adaptive_rag_service.mixin_answer_payload import AdaptiveRAGAnswerPayloadMixin from app.services.adaptive_rag_service.mixin_deep_guard_answer import AdaptiveRAGDeepGuardAnswerMixin from app.services.adaptive_rag_service.mixin_fast_answer_project_utils import AdaptiveRAGFastAnswerProjectUtilsMixin from app.services.adaptive_rag_service.mixin_query_route_gateway import AdaptiveRAGQueryRouteGatewayMixin from app.services.adaptive_rag_service.mixin_target_resolution import AdaptiveRAGTargetResolutionMixin from app.services.adaptive_rag_service.internal_query_context import InternalContextPacket class _PacketBuilderService( AdaptiveRAGAnswerMainlineMixin, AdaptiveRAGQueryRouteGatewayMixin, ): tenant_id = 9 class _VerifierService( AdaptiveRAGAnswerPayloadMixin, AdaptiveRAGQueryRouteGatewayMixin, ): pass class _RuntimeSummaryService(AdaptiveRAGTargetResolutionMixin): pass class _ProjectUtilsService(AdaptiveRAGFastAnswerProjectUtilsMixin): pass def _build_internal_packet(**overrides) -> InternalContextPacket: payload = { "packet_version": "v1", "question": "系统里面有没有开票系统？", "scope": { "tenant_id": 9, "project_id": 6, "session_id": 101, "conversation_scope_key": "scope:chat:1", "reply_to_message_id": "om_reply_1", "root_message_id": "om_root_1", }, "route_decision": { "route_mode": "internal", "effective_source_policy": "internal", "decision_origin": "query_semantics_contract", "reply_contract": {"mode": "explicit_source", "head": "内部知识库查询："}, "query_profile": { "needs_private_context": True, "needs_freshness": False, "referenced_objects": ["project_object"], "confidence": 0.92, }, }, "operation_contract": { "query_type": "existence", "answer_contract": "yes_no_with_evidence", "object_mentions": ["开票系统"], "clarify_policy": "ask_when_target_ambiguous", }, "target_resolution": { "target_entity_type": "project", "target_ref": "project:6", "resolved_label": "自动开票系统", "resolution_mode": "deterministic", "confidence": 0.96, "candidate_summary": [], }, "query_plan": { "plan_version": "v2", "query_type": "existence", "entity_type": "project", "answer_contract": "yes_no_with_evidence", "target_ref": "project:6", "filters": [{"field": "project_id", "operator": "equals", "value": 6}], "scope": {"tenant_bound": True, "project_id": 6, "scope_hint": "project"}, "retrieval_policy": {"facts_first": True, "allow_fallback_text": True}, "verifier_checks": ["contract_matches_query_type", "evidence_backed"], }, "executor_summary": {}, "verifier_summary": {}, "uncertainties": [], } payload.update(overrides) return InternalContextPacket.model_validate(payload) def test_build_internal_query_context_packet_returns_packet_for_internal_route() -> None: service = _PacketBuilderService() packet = service._build_internal_query_context_packet( question="系统里面有没有开票系统？", project_id=6, session_id=101, conversation_scope_key="scope:chat:1", reply_to_message_id="om_reply_1", root_message_id="om_root_1", route_decision={ "route_mode": "internal", "effective_source_policy": "internal", "decision_origin": "query_semantics_contract", "reply_contract": {"mode": "explicit_source", "head": "内部知识库查询："}, "query_profile": { "needs_private_context": True, "needs_freshness": False, "referenced_objects": ["project_object"], "confidence": 0.92, }, }, operation_contract={ "query_type": "existence", "answer_contract": "yes_no_with_evidence", "object_mentions": ["开票系统"], }, target_resolution={ "target_entity_type": "project", "target_ref": "project:6", "resolved_label": "自动开票系统", "resolution_mode": "deterministic", "confidence": 0.96, }, query_plan={ "plan_version": "v2", "query_type": "existence", "entity_type": "project", "answer_contract": "yes_no_with_evidence", "target_ref": "project:6", "filters": [{"field": "project_id", "operator": "equals", "value": 6}], }, ) assert isinstance(packet, InternalContextPacket) assert packet.scope["tenant_id"] == 9 assert packet.scope["project_id"] == 6 assert packet.route_decision["effective_source_policy"] == "internal" assert packet.operation_contract["query_type"] == "existence" assert packet.target_resolution["target_ref"] == "project:6" assert packet.query_plan["answer_contract"] == "yes_no_with_evidence" def test_build_internal_query_context_packet_skips_external_route() -> None: service = _PacketBuilderService() packet = service._build_internal_query_context_packet( question="OpenAI 最新模型是什么？", project_id=None, session_id=101, conversation_scope_key="scope:chat:2", reply_to_message_id=None, root_message_id=None, route_decision={ "route_mode": "external", "effective_source_policy": "external", "decision_origin": "query_semantics_contract", "reply_contract": {"mode": "explicit_source", "head": "外部实时查询："}, "query_profile": { "needs_private_context": False, "needs_freshness": True, "referenced_objects": ["public_model"], "confidence": 0.95, }, }, operation_contract={}, target_resolution={}, query_plan=None, ) assert packet is None def test_internal_query_runtime_metrics_prefer_internal_context_packet() -> None: service = _RuntimeSummaryService() packet = _build_internal_packet() metrics = service._inject_internal_query_runtime_summaries( retrieval_metrics={"db_query_ms": 12}, query_semantics={ "operation_contract": { "query_type": "count", "answer_contract": "count_scalar", "object_mentions": ["错误镜像"], }, "target_resolution": { "target_entity_type": "project", "target_ref": "project:999", "resolved_label": "错误项目", "resolution_mode": "deterministic", "confidence": 0.5, }, "query_plan": { "plan_version": "v0", "query_type": "count", "entity_type": "project", "target_ref": "project:999", "answer_contract": "count_scalar", "filters": [], }, }, internal_context_packet=packet, ) assert metrics["db_query_ms"] == 12 assert metrics["operation_contract_summary"]["query_type"] == "existence" assert metrics["target_resolution_summary"]["target_ref"] == "project:6" assert metrics["query_plan_summary"]["plan_version"] == "v2" def test_internal_answer_contract_verifier_prefers_internal_context_packet_contract() -> None: service = _VerifierService() packet = _build_internal_packet() verdict = service._verify_internal_answer_contract( query_type="count", answer="当前系统里项目总数为 42 个。", sources=[ { "source": "db", "label": "Project database", "score": 0.99, "metadata": {"table": "projects"}, } ], route_decision={"route_mode": "internal", "effective_source_policy": "internal"}, internal_context_packet=packet, ) assert verdict["ok"] is False assert verdict["reason_code"] == "no_total_count_substitution" def test_internal_answer_contract_verifier_blocks_target_resolution_clarify() -> None: service = _VerifierService() packet = _build_internal_packet( target_resolution={ "target_entity_type": "unknown", "target_ref": None, "resolved_label": None, "resolution_mode": "clarify", "confidence": 0.41, "candidate_summary": [ { "target_entity_type": "project", "target_ref": "project:6", "resolved_label": "自动开票系统", "score": 0.62, "source_kind": "semantic_facts", } ], } ) verdict = service._verify_internal_answer_contract( query_type="existence", answer="有，当前匹配到 1 个相关项目：#6 自动开票系统（状态:active）", sources=[ { "source": "db", "label": "Project database", "score": 0.99, "metadata": {"table": "projects", "project_id": 6}, } ], route_decision={"route_mode": "internal", "effective_source_policy": "internal"}, internal_context_packet=packet, ) assert verdict["ok"] is False assert verdict["reason_code"] == "target_resolution_clarify" def test_internal_answer_contract_verifier_blocks_missing_internal_context_packet_for_internal_route() -> None: service = _VerifierService() verdict = service._verify_internal_answer_contract( query_type="existence", answer="有，当前匹配到 1 个相关项目：#6 自动开票系统（状态:active）", sources=[ { "source": "db", "label": "Project database", "score": 0.99, "metadata": {"table": "projects", "project_id": 6}, } ], route_decision={"route_mode": "internal", "effective_source_policy": "internal"}, internal_context_packet=None, ) assert verdict["ok"] is False assert verdict["reason_code"] == "missing_internal_context_packet" def test_internal_answer_contract_verifier_blocks_missing_query_plan_contract() -> None: service = _VerifierService() packet = _build_internal_packet( query_plan={ "plan_version": "v2", "query_type": "existence", "entity_type": "project", "answer_contract": "", "target_ref": "project:6", "filters": [{"field": "project_id", "operator": "equals", "value": 6}], } ) verdict = service._verify_internal_answer_contract( query_type="existence", answer="有，当前匹配到 1 个相关项目：#6 自动开票系统（状态:active）", sources=[ { "source": "db", "label": "Project database", "score": 0.99, "metadata": {"table": "projects", "project_id": 6}, } ], route_decision={"route_mode": "internal", "effective_source_policy": "internal"}, internal_context_packet=packet, ) assert verdict["ok"] is False assert verdict["reason_code"] == "missing_internal_query_plan_contract" def test_collect_structured_object_mentions_prefers_internal_context_packet() -> None: packet = _build_internal_packet( operation_contract={ "query_type": "existence", "answer_contract": "yes_no_with_evidence", "object_mentions": ["真实对象"], }, target_resolution={ "target_entity_type": "project", "target_ref": "project:6", "resolved_label": "真实项目", "resolution_mode": "deterministic", "confidence": 0.96, "candidate_summary": [], }, ) mentions = _ProjectUtilsService._collect_structured_object_mentions( query_semantics={ "operation_contract": { "query_type": "count", "answer_contract": "count_scalar", "object_mentions": ["错误对象"], }, "target_resolution": { "target_entity_type": "project", "target_ref": "project:999", "resolved_label": "错误项目", "resolution_mode": "deterministic", }, }, internal_context_packet=packet, ) assert mentions[:2] == ["真实对象", "真实项目"] @pytest.mark.asyncio async def test_internal_model_config_fast_answer_prefers_internal_context_packet() -> None: class _FakeLLM: async def _get_or_init_bundle(self, db, *, tenant_id: int): _ = (db, tenant_id) return object(), { "active_engine_id": "low-1", "engines": [ { "id": "low-1", "name": "Qwen 低阶引擎", "provider": "dashscope", "model": "qwen-plus", } ], "settings": { "enable_local_kb_qa": False, }, } def _resolve_active_engine_from_bundle(self, bundle: dict[str, object]): engines = list(bundle.get("engines") or []) return dict(engines[0]) async def _resolve_engine_for_call(self, db, *, tenant_id: int, function_name: str, routing_meta=None): _ = (db, tenant_id, function_name, routing_meta) return { "name": "Qwen 低阶引擎", "provider": "dashscope", "model": "qwen-plus", "_routing_meta": {"planned_tier": "low", "executed_tier": "low"}, } class _FakeService(AdaptiveRAGDeepGuardAnswerMixin): def __init__(self) -> None: self.db = object() self.tenant_id = 1 self.llm = _FakeLLM() service = _FakeService() packet = _build_internal_packet( question="我们系统当前接的是哪个模型配置？", route_decision={ "route_mode": "internal", "effective_source_policy": "internal", "decision_origin": "query_semantics_contract", "reply_contract": {"mode": "explicit_source", "head": "内部知识库查询："}, "query_profile": { "needs_private_context": True, "needs_freshness": False, "referenced_objects": ["system_config", "model_routing"], "confidence": 0.92, }, }, operation_contract={ "query_type": "status", "answer_contract": "entity_snapshot", "object_mentions": ["当前模型配置"], }, target_resolution={ "target_entity_type": "config", "target_ref": "config:model_routing", "resolved_label": "当前模型配置", "resolution_mode": "deterministic", "confidence": 0.98, "candidate_summary": [], }, query_plan={ "plan_version": "v2", "query_type": "status", "entity_type": "config", "answer_contract": "entity_snapshot", "target_ref": "config:model_routing", "filters": [], }, ) fast_result = await service._build_internal_model_config_fast_answer( question="我们系统当前接的是哪个模型配置？", query_semantics={ "effective_source_policy": "internal", "query_type": "existence", "operation_contract": { "query_type": "existence", "answer_contract": "yes_no_with_evidence", }, "query_profile": { "needs_private_context": True, "needs_freshness": False, "referenced_objects": [], }, "target_resolution": { "target_entity_type": "project", "target_ref": "project:72", }, }, internal_context_packet=packet, ) assert isinstance(fast_result, dict) assert "qwen-plus" in str(fast_result["answer"]) assert fast_result["query_type"] == "status"