refactor(api): move llm quota deduction to app graph layer (#32786)

api/core/app/workflow/layers/__init__.py

@@ -1,9 +1,11 @@
 """Workflow-level GraphEngine layers that depend on outer infrastructure."""
 
+from .llm_quota import LLMQuotaLayer
 from .observability import ObservabilityLayer
 from .persistence import PersistenceWorkflowInfo, WorkflowPersistenceLayer
 
 __all__ = [
+    "LLMQuotaLayer",
     "ObservabilityLayer",
     "PersistenceWorkflowInfo",
     "WorkflowPersistenceLayer",

api/core/app/workflow/layers/llm_quota.py

@@ -0,0 +1,128 @@
+"""
+LLM quota deduction layer for GraphEngine.
+
+This layer centralizes model-quota deduction outside node implementations.
+"""
+
+import logging
+from typing import TYPE_CHECKING, cast, final
+
+from typing_extensions import override
+
+from core.app.llm import deduct_llm_quota, ensure_llm_quota_available
+from core.errors.error import QuotaExceededError
+from core.model_manager import ModelInstance
+from core.workflow.enums import NodeType
+from core.workflow.graph_engine.entities.commands import AbortCommand, CommandType
+from core.workflow.graph_engine.layers.base import GraphEngineLayer
+from core.workflow.graph_events import GraphEngineEvent, GraphNodeEventBase
+from core.workflow.graph_events.node import NodeRunSucceededEvent
+from core.workflow.nodes.base.node import Node
+
+if TYPE_CHECKING:
+    from core.workflow.nodes.llm.node import LLMNode
+    from core.workflow.nodes.parameter_extractor.parameter_extractor_node import ParameterExtractorNode
+    from core.workflow.nodes.question_classifier.question_classifier_node import QuestionClassifierNode
+
+logger = logging.getLogger(__name__)
+
+
+@final
+class LLMQuotaLayer(GraphEngineLayer):
+    """Graph layer that applies LLM quota deduction after node execution."""
+
+    def __init__(self) -> None:
+        super().__init__()
+        self._abort_sent = False
+
+    @override
+    def on_graph_start(self) -> None:
+        self._abort_sent = False
+
+    @override
+    def on_event(self, event: GraphEngineEvent) -> None:
+        _ = event
+
+    @override
+    def on_graph_end(self, error: Exception | None) -> None:
+        _ = error
+
+    @override
+    def on_node_run_start(self, node: Node) -> None:
+        if self._abort_sent:
+            return
+
+        model_instance = self._extract_model_instance(node)
+        if model_instance is None:
+            return
+
+        try:
+            ensure_llm_quota_available(model_instance=model_instance)
+        except QuotaExceededError as exc:
+            self._set_stop_event(node)
+            self._send_abort_command(reason=str(exc))
+            logger.warning("LLM quota check failed, node_id=%s, error=%s", node.id, exc)
+
+    @override
+    def on_node_run_end(
+        self, node: Node, error: Exception | None, result_event: GraphNodeEventBase | None = None
+    ) -> None:
+        if error is not None or not isinstance(result_event, NodeRunSucceededEvent):
+            return
+
+        model_instance = self._extract_model_instance(node)
+        if model_instance is None:
+            return
+
+        try:
+            deduct_llm_quota(
+                tenant_id=node.tenant_id,
+                model_instance=model_instance,
+                usage=result_event.node_run_result.llm_usage,
+            )
+        except QuotaExceededError as exc:
+            self._set_stop_event(node)
+            self._send_abort_command(reason=str(exc))
+            logger.warning("LLM quota deduction exceeded, node_id=%s, error=%s", node.id, exc)
+        except Exception:
+            logger.exception("LLM quota deduction failed, node_id=%s", node.id)
+
+    @staticmethod
+    def _set_stop_event(node: Node) -> None:
+        stop_event = getattr(node.graph_runtime_state, "stop_event", None)
+        if stop_event is not None:
+            stop_event.set()
+
+    def _send_abort_command(self, *, reason: str) -> None:
+        if not self.command_channel or self._abort_sent:
+            return
+
+        try:
+            self.command_channel.send_command(
+                AbortCommand(
+                    command_type=CommandType.ABORT,
+                    reason=reason,
+                )
+            )
+            self._abort_sent = True
+        except Exception:
+            logger.exception("Failed to send quota abort command")
+
+    @staticmethod
+    def _extract_model_instance(node: Node) -> ModelInstance | None:
+        try:
+            match node.node_type:
+                case NodeType.LLM:
+                    return cast("LLMNode", node).model_instance
+                case NodeType.PARAMETER_EXTRACTOR:
+                    return cast("ParameterExtractorNode", node).model_instance
+                case NodeType.QUESTION_CLASSIFIER:
+                    return cast("QuestionClassifierNode", node).model_instance
+                case _:
+                    return None
+        except AttributeError:
+            logger.warning(
+                "LLMQuotaLayer skipped quota deduction because node does not expose a model instance, node_id=%s",
+                node.id,
+            )
+            return None