Уточнить subject-оси Autonomy Core 1С

llm_normalizer/backend/dist/services/assistantEvidencePlanner.js

@@ -37,12 +37,29 @@ function uniqueStrings(values) {
 function isExplicitDate(value) {
     return Boolean(value && /^\d{4}-\d{2}-\d{2}$/.test(value));
 }
-function providedAxesFromMeaning(meaning, graph) {
+const SUBJECT_AXIS_SET = new Set([
+    "counterparty",
+    "business_entity",
+    "item",
+    "supplier",
+    "buyer",
+    "document",
+    "contract"
+]);
+function providedAxesFromMeaning(meaning, graph, requiredAxes) {
     const result = [];
     if ((meaning?.explicit_entity_candidates?.length ?? 0) > 0) {
         result.push("counterparty");
         result.push("business_entity");
     }
+    if ((graph?.subject_candidates.length ?? 0) > 0) {
+        result.push("business_entity");
+        for (const axis of requiredAxes) {
+            if (SUBJECT_AXIS_SET.has(axis)) {
+                result.push(axis);
+            }
+        }
+    }
     if (toNonEmptyString(meaning?.explicit_organization_scope)) {
         result.push("organization");
     }
@@ -126,7 +143,7 @@ function buildAssistantEvidencePlanner(input) {
     const plan = input.discoveryPlan;
     const turnMeaning = plan.turn_meaning_ref;
     const requiredAxes = uniqueStrings(plan.required_axes);
-    const providedAxes = providedAxesFromMeaning(turnMeaning, graph);
+    const providedAxes = providedAxesFromMeaning(turnMeaning, graph, requiredAxes);
     const graphClarificationGaps = uniqueStrings(graph?.clarification_gaps ?? []);
     const additionalAxisGaps = uniqueStrings(input.additionalMissingAxes ?? []).filter((axis) => !providedAxes.includes(axis) && (requiredAxes.includes(axis) || USER_ACTIONABLE_AXIS_SET.has(axis)));
     const axisGaps = uniqueStrings([...additionalAxisGaps, ...missingAxes(requiredAxes, providedAxes)]);

llm_normalizer/backend/dist/services/assistantMcpDiscoveryDataNeedGraph.js

@@ -178,6 +178,23 @@ function hasOpenScopeOneSidedValueTotalHintUtf8Safe(rawUtterance, action) {
     }
     return false;
 }
+function inferredOpenScopeOneSidedValueAction(rawUtterance) {
+    if (hasOpenScopeOneSidedValueTotalHintUtf8Safe(rawUtterance, "turnover") ||
+        hasOpenScopeOneSidedValueTotalHint(rawUtterance, "turnover")) {
+        return "turnover";
+    }
+    if (hasOpenScopeOneSidedValueTotalHintUtf8Safe(rawUtterance, "payout") ||
+        hasOpenScopeOneSidedValueTotalHint(rawUtterance, "payout")) {
+        return "payout";
+    }
+    return null;
+}
+function hasDetailedBusinessOverviewMoneyBreakdownHint(rawUtterance) {
+    if (!rawUtterance) {
+        return false;
+    }
+    return /(?:\u0440\u0430\u0441\u043a\u0440\u043e\p{L}*|\u043f\u043e\u0434\u0440\u043e\u0431\p{L}*|\u0440\u0430\u0437\u0431\u0435\p{L}*|\u0440\u0430\u0437\u0432\u0435\u0440\u043d\p{L}*|\u043a\u0442\u043e\s+\u0433\u043b\u0430\u0432\p{L}*|\u0433\u043b\u0430\u0432\p{L}*\s+\u043a\u043b\u0438\u0435\u043d\p{L}*|\u0433\u043b\u0430\u0432\p{L}*\s+\u043f\u043e\u0441\u0442\u0430\u0432\p{L}*|\u0447\u0438\u0441\u0442\p{L}*\s+\u0434\u0435\u043d\u0435\u0436\p{L}*\s+\u043f\u043e\u0442\u043e\p{L}*|\u043f\u043e\u043b\u0443\u0447\p{L}*[\s\S]{0,80}\u0437\u0430\u043f\u043b\u0430\u0442\p{L}*|\u0432\u0445\u043e\u0434\p{L}*[\s\S]{0,80}\u0438\u0441\u0445\u043e\u0434\p{L}*|detail|breakdown|drill\s*down|main\s+customer|main\s+supplier)/iu.test(rawUtterance);
+}
 function supportsOrganizationScopedOpenTotal(action) {
     return action === "turnover" || action === "payout";
 }
@@ -393,7 +410,7 @@ function buildAssistantMcpDiscoveryDataNeedGraph(input) {
     const semanticDataNeed = lower(input.semanticDataNeed);
     const turnMeaning = input.turnMeaning ?? null;
     const domain = lower(turnMeaning?.asked_domain_family);
-    const action = lower(turnMeaning?.asked_action_family);
+    const rawAction = lower(turnMeaning?.asked_action_family);
     const unsupported = lower(turnMeaning?.unsupported_but_understood_family);
     const rawUtterance = lower(input.rawUtterance);
     const rawQuestionSignal = lower([input.rawUtterance, turnMeaning?.raw_message, turnMeaning?.effective_message].join(" "));
@@ -406,12 +423,19 @@ function buildAssistantMcpDiscoveryDataNeedGraph(input) {
     const subjectCandidates = (turnMeaning?.explicit_entity_candidates ?? [])
         .map((item) => toNonEmptyString(item))
         .filter((item) => Boolean(item));
-    const businessFactFamily = businessFactFamilyFor({
+    const initialBusinessFactFamily = businessFactFamilyFor({
         semanticDataNeed,
         domain,
-        action,
+        action: rawAction,
         unsupported
     });
+    const oneSidedValueAction = inferredOpenScopeOneSidedValueAction(rawQuestionSignal);
+    const detailedBusinessOverviewMoneyBreakdownHint = hasDetailedBusinessOverviewMoneyBreakdownHint(rawQuestionSignal);
+    const oneSidedBusinessOverviewValueFlowOverride = initialBusinessFactFamily === "business_overview" &&
+        Boolean(oneSidedValueAction) &&
+        !detailedBusinessOverviewMoneyBreakdownHint;
+    const action = oneSidedBusinessOverviewValueFlowOverride ? oneSidedValueAction : rawAction;
+    const businessFactFamily = oneSidedBusinessOverviewValueFlowOverride ? "value_flow" : initialBusinessFactFamily;
     const aggregationNeed = aggregationNeedFor(aggregationAxis);
     const comparisonNeed = comparisonNeedFor(action);
     const allTimeScopeHint = hasAllTimeScopeHint(rawUtterance);
@@ -529,6 +553,9 @@ function buildAssistantMcpDiscoveryDataNeedGraph(input) {
     if (directBusinessOverviewMoneyAnswerHint) {
         pushReason(reasonCodes, "data_need_graph_business_overview_direct_money_answer");
     }
+    if (oneSidedBusinessOverviewValueFlowOverride) {
+        pushReason(reasonCodes, "data_need_graph_business_overview_one_sided_money_total_routed_to_value_flow");
+    }
     if (clarificationGaps.includes("organization")) {
         pushReason(reasonCodes, "data_need_graph_open_scope_total_needs_organization");
     }
@@ -542,7 +569,7 @@ function buildAssistantMcpDiscoveryDataNeedGraph(input) {
         metadata_scope_hint: metadataScopeHint,
         subject_resolution_optional: subjectResolutionOptional || undefined,
         business_fact_family: businessFactFamily,
-        action_family: toNonEmptyString(turnMeaning?.asked_action_family),
+        action_family: toNonEmptyString(action),
         aggregation_need: aggregationNeed,
         time_scope_need: timeScopeNeed,
         comparison_need: comparisonNeed,

llm_normalizer/backend/dist/services/assistantMcpDiscoveryPlanner.js

@@ -109,10 +109,16 @@ function hasReasonCode(graph, reasonCode) {
 function aggregationAxis(meaning) {
     return toNonEmptyString(meaning?.asked_aggregation_axis)?.toLowerCase() ?? null;
 }
-function addScopeAxes(axes, meaning) {
+function addScopeAxes(axes, meaning, graph) {
     if (hasEntity(meaning)) {
         pushUnique(axes, "counterparty");
     }
+    if (hasSubjectCandidates(graph)) {
+        const factFamily = lower(graph?.business_fact_family);
+        if (factFamily === "value_flow" || factFamily === "activity_lifecycle") {
+            pushUnique(axes, "counterparty");
+        }
+    }
     if (toNonEmptyString(meaning?.explicit_organization_scope)) {
         pushUnique(axes, "organization");
     }
@@ -498,7 +504,7 @@ function recipeFor(input) {
     const combined = `${domain} ${action} ${unsupported}`.trim();
     const axes = [];
     const requestedAggregationAxis = aggregationAxis(meaning);
-    addScopeAxes(axes, meaning);
+    addScopeAxes(axes, meaning, dataNeedGraph);
     addMetadataScopeAxis(axes, meaning);
     addTimeScopeAxes(axes, dataNeedGraph);
     if (graphClarificationGaps.includes("lane_family_choice")) {

llm_normalizer/backend/src/services/assistantEvidencePlanner.ts

@@ -117,15 +117,34 @@ function isExplicitDate(value: string | null): boolean {
   return Boolean(value && /^\d{4}-\d{2}-\d{2}$/.test(value));
 }
 
+const SUBJECT_AXIS_SET = new Set([
+  "counterparty",
+  "business_entity",
+  "item",
+  "supplier",
+  "buyer",
+  "document",
+  "contract"
+]);
+
 function providedAxesFromMeaning(
   meaning: AssistantMcpDiscoveryTurnMeaningRef | null,
-  graph: AssistantMcpDiscoveryDataNeedGraphContract | null
+  graph: AssistantMcpDiscoveryDataNeedGraphContract | null,
+  requiredAxes: string[]
 ): string[] {
   const result: string[] = [];
   if ((meaning?.explicit_entity_candidates?.length ?? 0) > 0) {
     result.push("counterparty");
     result.push("business_entity");
   }
+  if ((graph?.subject_candidates.length ?? 0) > 0) {
+    result.push("business_entity");
+    for (const axis of requiredAxes) {
+      if (SUBJECT_AXIS_SET.has(axis)) {
+        result.push(axis);
+      }
+    }
+  }
   if (toNonEmptyString(meaning?.explicit_organization_scope)) {
     result.push("organization");
   }
@@ -223,7 +242,7 @@ export function buildAssistantEvidencePlanner(
   const plan = input.discoveryPlan;
   const turnMeaning = plan.turn_meaning_ref;
   const requiredAxes = uniqueStrings(plan.required_axes);
-  const providedAxes = providedAxesFromMeaning(turnMeaning, graph);
+  const providedAxes = providedAxesFromMeaning(turnMeaning, graph, requiredAxes);
   const graphClarificationGaps = uniqueStrings(graph?.clarification_gaps ?? []);
   const additionalAxisGaps = uniqueStrings(input.additionalMissingAxes ?? []).filter(
     (axis) => !providedAxes.includes(axis) && (requiredAxes.includes(axis) || USER_ACTIONABLE_AXIS_SET.has(axis)),

llm_normalizer/backend/src/services/assistantMcpDiscoveryDataNeedGraph.ts

@@ -267,6 +267,31 @@ function hasOpenScopeOneSidedValueTotalHintUtf8Safe(rawUtterance: string, action
   return false;
 }
 
+function inferredOpenScopeOneSidedValueAction(rawUtterance: string): "turnover" | "payout" | null {
+  if (
+    hasOpenScopeOneSidedValueTotalHintUtf8Safe(rawUtterance, "turnover") ||
+    hasOpenScopeOneSidedValueTotalHint(rawUtterance, "turnover")
+  ) {
+    return "turnover";
+  }
+  if (
+    hasOpenScopeOneSidedValueTotalHintUtf8Safe(rawUtterance, "payout") ||
+    hasOpenScopeOneSidedValueTotalHint(rawUtterance, "payout")
+  ) {
+    return "payout";
+  }
+  return null;
+}
+
+function hasDetailedBusinessOverviewMoneyBreakdownHint(rawUtterance: string): boolean {
+  if (!rawUtterance) {
+    return false;
+  }
+  return /(?:\u0440\u0430\u0441\u043a\u0440\u043e\p{L}*|\u043f\u043e\u0434\u0440\u043e\u0431\p{L}*|\u0440\u0430\u0437\u0431\u0435\p{L}*|\u0440\u0430\u0437\u0432\u0435\u0440\u043d\p{L}*|\u043a\u0442\u043e\s+\u0433\u043b\u0430\u0432\p{L}*|\u0433\u043b\u0430\u0432\p{L}*\s+\u043a\u043b\u0438\u0435\u043d\p{L}*|\u0433\u043b\u0430\u0432\p{L}*\s+\u043f\u043e\u0441\u0442\u0430\u0432\p{L}*|\u0447\u0438\u0441\u0442\p{L}*\s+\u0434\u0435\u043d\u0435\u0436\p{L}*\s+\u043f\u043e\u0442\u043e\p{L}*|\u043f\u043e\u043b\u0443\u0447\p{L}*[\s\S]{0,80}\u0437\u0430\u043f\u043b\u0430\u0442\p{L}*|\u0432\u0445\u043e\u0434\p{L}*[\s\S]{0,80}\u0438\u0441\u0445\u043e\u0434\p{L}*|detail|breakdown|drill\s*down|main\s+customer|main\s+supplier)/iu.test(
+    rawUtterance
+  );
+}
+
 function supportsOrganizationScopedOpenTotal(action: string): boolean {
   return action === "turnover" || action === "payout";
 }
@@ -522,7 +547,7 @@ export function buildAssistantMcpDiscoveryDataNeedGraph(
   const semanticDataNeed = lower(input.semanticDataNeed);
   const turnMeaning = input.turnMeaning ?? null;
   const domain = lower(turnMeaning?.asked_domain_family);
-  const action = lower(turnMeaning?.asked_action_family);
+  const rawAction = lower(turnMeaning?.asked_action_family);
   const unsupported = lower(turnMeaning?.unsupported_but_understood_family);
   const rawUtterance = lower(input.rawUtterance);
   const rawQuestionSignal = lower([input.rawUtterance, turnMeaning?.raw_message, turnMeaning?.effective_message].join(" "));
@@ -535,12 +560,20 @@ export function buildAssistantMcpDiscoveryDataNeedGraph(
   const subjectCandidates = (turnMeaning?.explicit_entity_candidates ?? [])
     .map((item) => toNonEmptyString(item))
     .filter((item): item is string => Boolean(item));
-  const businessFactFamily = businessFactFamilyFor({
+  const initialBusinessFactFamily = businessFactFamilyFor({
     semanticDataNeed,
     domain,
-    action,
+    action: rawAction,
     unsupported
   });
+  const oneSidedValueAction = inferredOpenScopeOneSidedValueAction(rawQuestionSignal);
+  const detailedBusinessOverviewMoneyBreakdownHint = hasDetailedBusinessOverviewMoneyBreakdownHint(rawQuestionSignal);
+  const oneSidedBusinessOverviewValueFlowOverride =
+    initialBusinessFactFamily === "business_overview" &&
+    Boolean(oneSidedValueAction) &&
+    !detailedBusinessOverviewMoneyBreakdownHint;
+  const action = oneSidedBusinessOverviewValueFlowOverride ? oneSidedValueAction! : rawAction;
+  const businessFactFamily = oneSidedBusinessOverviewValueFlowOverride ? "value_flow" : initialBusinessFactFamily;
   const aggregationNeed = aggregationNeedFor(aggregationAxis);
   const comparisonNeed = comparisonNeedFor(action);
   const allTimeScopeHint = hasAllTimeScopeHint(rawUtterance);
@@ -669,6 +702,9 @@ export function buildAssistantMcpDiscoveryDataNeedGraph(
   if (directBusinessOverviewMoneyAnswerHint) {
     pushReason(reasonCodes, "data_need_graph_business_overview_direct_money_answer");
   }
+  if (oneSidedBusinessOverviewValueFlowOverride) {
+    pushReason(reasonCodes, "data_need_graph_business_overview_one_sided_money_total_routed_to_value_flow");
+  }
   if (clarificationGaps.includes("organization")) {
     pushReason(reasonCodes, "data_need_graph_open_scope_total_needs_organization");
   }
@@ -683,7 +719,7 @@ export function buildAssistantMcpDiscoveryDataNeedGraph(
     metadata_scope_hint: metadataScopeHint,
     subject_resolution_optional: subjectResolutionOptional || undefined,
     business_fact_family: businessFactFamily,
-    action_family: toNonEmptyString(turnMeaning?.asked_action_family),
+    action_family: toNonEmptyString(action),
     aggregation_need: aggregationNeed,
     time_scope_need: timeScopeNeed,
     comparison_need: comparisonNeed,

llm_normalizer/backend/src/services/assistantMcpDiscoveryPlanner.ts

@@ -253,10 +253,20 @@ function aggregationAxis(meaning: AssistantMcpDiscoveryTurnMeaningRef | null | u
   return toNonEmptyString(meaning?.asked_aggregation_axis)?.toLowerCase() ?? null;
 }
 
-function addScopeAxes(axes: string[], meaning: AssistantMcpDiscoveryTurnMeaningRef | null | undefined): void {
+function addScopeAxes(
+  axes: string[],
+  meaning: AssistantMcpDiscoveryTurnMeaningRef | null | undefined,
+  graph: AssistantMcpDiscoveryDataNeedGraphContract | null | undefined
+): void {
   if (hasEntity(meaning)) {
     pushUnique(axes, "counterparty");
   }
+  if (hasSubjectCandidates(graph)) {
+    const factFamily = lower(graph?.business_fact_family);
+    if (factFamily === "value_flow" || factFamily === "activity_lifecycle") {
+      pushUnique(axes, "counterparty");
+    }
+  }
   if (toNonEmptyString(meaning?.explicit_organization_scope)) {
     pushUnique(axes, "organization");
   }
@@ -741,7 +751,7 @@ function recipeFor(input: AssistantMcpDiscoveryPlannerInput): PlannerRecipe {
   const combined = `${domain} ${action} ${unsupported}`.trim();
   const axes: string[] = [];
   const requestedAggregationAxis = aggregationAxis(meaning);
-  addScopeAxes(axes, meaning);
+  addScopeAxes(axes, meaning, dataNeedGraph);
   addMetadataScopeAxis(axes, meaning);
   addTimeScopeAxes(axes, dataNeedGraph);
 

llm_normalizer/backend/tests/assistantMcpDiscoveryDataNeedGraph.test.ts

@@ -336,6 +336,37 @@ describe("assistant MCP discovery data need graph", () => {
     ]);
     expect(result.reason_codes).toContain("data_need_graph_open_scope_total_without_subject");
   });
+
+  it("routes broad-overview one-sided incoming totals to value-flow instead of company overview", () => {
+    const result = buildAssistantMcpDiscoveryDataNeedGraph({
+      semanticDataNeed: "business overview evidence with bounded analyst interpretation",
+      rawUtterance:
+        "А всего сколько денег пришло в ООО Альтернатива Плюс за 2020, без топов и без контрагентов?",
+      turnMeaning: {
+        asked_domain_family: "business_overview",
+        asked_action_family: "broad_evaluation",
+        unsupported_but_understood_family: "broad_business_evaluation",
+        explicit_date_scope: "2020",
+        explicit_organization_scope: "ООО Альтернатива Плюс"
+      }
+    });
+
+    expect(result.business_fact_family).toBe("value_flow");
+    expect(result.action_family).toBe("turnover");
+    expect(result.comparison_need).toBeNull();
+    expect(result.ranking_need).toBeNull();
+    expect(result.clarification_gaps).toEqual([]);
+    expect(result.decomposition_candidates).toEqual([
+      "collect_scoped_movements",
+      "aggregate_checked_amounts",
+      "probe_coverage"
+    ]);
+    expect(result.reason_codes).toContain("data_need_graph_open_scope_total_without_subject");
+    expect(result.reason_codes).toContain(
+      "data_need_graph_business_overview_one_sided_money_total_routed_to_value_flow"
+    );
+  });
+
   it("treats a generic incoming total as an understood open-scope ask that still needs organization", () => {
     const result = buildAssistantMcpDiscoveryDataNeedGraph({
       semanticDataNeed: "counterparty value-flow evidence",

llm_normalizer/backend/tests/assistantMcpDiscoveryPlanner.test.ts

@@ -157,6 +157,68 @@ describe("assistant MCP discovery planner", () => {
     expect(result.evidence_plan.evidence_axes.missing_axes).not.toContain("all_time_scope");
   });
 
+  it("uses graph subject candidates to satisfy the selected subject evidence axis", () => {
+    const result = planAssistantMcpDiscovery({
+      dataNeedGraph: {
+        schema_version: "assistant_data_need_graph_v1",
+        policy_owner: "assistantMcpDiscoveryDataNeedGraph",
+        subject_candidates: ["SVK"],
+        business_fact_family: "value_flow",
+        action_family: "net_value_flow",
+        aggregation_need: null,
+        time_scope_need: "explicit_period",
+        comparison_need: "incoming_vs_outgoing",
+        ranking_need: null,
+        proof_expectation: "coverage_checked_fact",
+        clarification_gaps: [],
+        decomposition_candidates: [],
+        forbidden_overclaim_flags: ["no_raw_model_claims"],
+        reason_codes: ["data_need_graph_built"]
+      },
+      turnMeaning: {
+        asked_action_family: "net_value_flow",
+        explicit_date_scope: "2020"
+      }
+    });
+
+    expect(result.selected_chain_id).toBe("value_flow_comparison");
+    expect(result.evidence_plan.evidence_axes.required_axes).toContain("counterparty");
+    expect(result.evidence_plan.evidence_axes.provided_axes).toContain("business_entity");
+    expect(result.evidence_plan.evidence_axes.provided_axes).toContain("counterparty");
+    expect(result.evidence_plan.evidence_axes.missing_axes).not.toContain("counterparty");
+  });
+
+  it("does not coerce inventory item subjects into counterparty evidence axes", () => {
+    const result = planAssistantMcpDiscovery({
+      dataNeedGraph: {
+        schema_version: "assistant_data_need_graph_v1",
+        policy_owner: "assistantMcpDiscoveryDataNeedGraph",
+        subject_candidates: ["Столешница 600"],
+        business_fact_family: "inventory_purchase_provenance",
+        action_family: "purchase_provenance",
+        aggregation_need: null,
+        time_scope_need: null,
+        comparison_need: null,
+        ranking_need: null,
+        proof_expectation: "coverage_checked_fact",
+        clarification_gaps: [],
+        decomposition_candidates: [],
+        forbidden_overclaim_flags: ["no_raw_model_claims"],
+        reason_codes: ["data_need_graph_built"]
+      },
+      turnMeaning: {
+        asked_action_family: "purchase_provenance"
+      }
+    });
+
+    expect(result.selected_chain_id).toBe("inventory_purchase_provenance");
+    expect(result.evidence_plan.evidence_axes.required_axes).toContain("item");
+    expect(result.evidence_plan.evidence_axes.provided_axes).toContain("business_entity");
+    expect(result.evidence_plan.evidence_axes.provided_axes).toContain("item");
+    expect(result.evidence_plan.evidence_axes.provided_axes).not.toContain("counterparty");
+    expect(result.evidence_plan.evidence_axes.missing_axes).not.toContain("item");
+  });
+
   it("keeps representative graph-selected chains aligned with top catalog template matches", () => {
     const graph = (
       businessFactFamily: string,