bdf3d3dd9c
- Introduce WorkflowAgentStage to manage agent stage configurations and enhance interaction with the workflow engine. - Implement WorkflowEdgeEvaluator for priority-aware edge evaluation, improving routing decisions based on conditions and user turns. - Update WorkflowBrain to handle user turns and routing more effectively, ensuring agents cannot have only one default path. - Enhance CallEndCoordinator to track speech events and manage call termination based on queued speech. - Add new models and output handling for workflow interactions, improving clarity and maintainability. - Update tests to validate the new routing logic and agent behavior under various scenarios.
98 lines
3.4 KiB
Python
98 lines
3.4 KiB
Python
"""Priority-aware Workflow edge evaluation."""
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from __future__ import annotations
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from collections.abc import Callable
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from services.runtime_variables import DynamicVariableStore
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from services.workflow.models import EdgeEvaluation, RouteStatus
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from services.workflow_engine import WorkflowEngine
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from services.workflow_router import WorkflowLLMRouter
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class WorkflowEdgeEvaluator:
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"""Evaluate one node's paths without changing runtime state."""
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def __init__(
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self,
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engine: WorkflowEngine,
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store: DynamicVariableStore,
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router_for_node: Callable[[str], WorkflowLLMRouter],
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) -> None:
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self._engine = engine
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self._store = store
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self._router_for_node = router_for_node
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async def evaluate(self, node_id: str) -> EdgeEvaluation:
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"""Select the first matching conditional path, then the default path."""
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outgoing = self._engine.outgoing(node_id)
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expression_edge = self._engine.deterministic_edge(
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node_id,
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self._store,
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include_default=False,
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)
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default_edge = next(
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(
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edge
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for edge in outgoing
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if self._engine.edge_mode(edge) == "always"
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),
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None,
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)
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llm_edges = [
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edge for edge in outgoing if self._engine.edge_mode(edge) == "llm"
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]
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# A matching expression is a priority boundary. A later LLM condition
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# cannot bypass it, while an earlier LLM condition still gets one chance.
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if expression_edge:
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expression_index = outgoing.index(expression_edge)
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llm_edges = [
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edge
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for edge in llm_edges
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if outgoing.index(edge) < expression_index
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]
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if not llm_edges:
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return self._matched_or_no_match(expression_edge or default_edge)
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result = await self._router_for_node(node_id).select_edge(
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node_name=self._engine.name(node_id),
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node_prompt=self._engine.routing_prompt(node_id, self._store),
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edges=llm_edges,
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history=self._store.history,
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variables={
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key: value
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for key, value in self._store.values.items()
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if not key.startswith(("system__", "secret__"))
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},
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edge_name=self._engine.edge_fn_name,
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edge_description=self._engine.edge_description,
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)
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if result.status == RouteStatus.ERROR:
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return EdgeEvaluation(status=RouteStatus.ERROR, error=result.error)
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if result.status == RouteStatus.NO_MATCH:
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return self._matched_or_no_match(expression_edge or default_edge)
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selected = next(
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(
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edge
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for edge in llm_edges
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if self._engine.edge_fn_name(edge) == result.function_name
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),
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None,
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)
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if selected is None:
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return EdgeEvaluation(
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status=RouteStatus.ERROR,
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error="路由模型返回了不属于当前节点的连接",
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)
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return EdgeEvaluation(status=RouteStatus.MATCHED, edge=selected)
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@staticmethod
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def _matched_or_no_match(edge: dict | None) -> EdgeEvaluation:
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if edge is None:
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return EdgeEvaluation(status=RouteStatus.NO_MATCH)
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return EdgeEvaluation(status=RouteStatus.MATCHED, edge=edge)
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