mirror of
https://github.com/langgenius/dify.git
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adadf1ec5f
Changes: - Change TelemetryEvent.name from str to TraceTaskName enum for type safety - Remove hardcoded trace_task_name_map from facade (no mapping needed) - Add centralized enterprise-only filter in TelemetryFacade.emit() - Rename is_telemetry_enabled() to is_enterprise_telemetry_enabled() - Update all 11 call sites to pass TraceTaskName enum values - Remove redundant enterprise guard from draft_trace.py - Add unit tests for TelemetryFacade.emit() routing (6 tests) - Add unit tests for TraceQueueManager telemetry guard (5 tests) - Fix test fixture scoping issue for full test suite compatibility - Fix tenant_id handling in agent tool callback handler Benefits: - 100% type-safe: basedpyright catches errors at compile time - No string literals: eliminates entire class of typo bugs - Single point of control: centralized filtering in facade - All guards removed except facade - Zero regressions: 4887 tests passing Verification: - make lint: PASS - make type-check: PASS (0 errors, 0 warnings) - pytest: 4887 passed, 8 skipped
77 lines
3.0 KiB
Python
77 lines
3.0 KiB
Python
from __future__ import annotations
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from collections.abc import Mapping
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from typing import Any
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from core.telemetry import TelemetryContext, TelemetryEvent, TelemetryFacade, TraceTaskName
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from core.workflow.enums import WorkflowNodeExecutionMetadataKey
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from models.workflow import WorkflowNodeExecutionModel
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def enqueue_draft_node_execution_trace(
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*,
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execution: WorkflowNodeExecutionModel,
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outputs: Mapping[str, Any] | None,
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workflow_execution_id: str | None,
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user_id: str,
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) -> None:
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node_data = _build_node_execution_data(
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execution=execution,
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outputs=outputs,
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workflow_execution_id=workflow_execution_id,
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)
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TelemetryFacade.emit(
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TelemetryEvent(
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name=TraceTaskName.DRAFT_NODE_EXECUTION_TRACE,
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context=TelemetryContext(
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tenant_id=execution.tenant_id,
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user_id=user_id,
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app_id=execution.app_id,
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),
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payload={"node_execution_data": node_data},
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)
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)
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def _build_node_execution_data(
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*,
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execution: WorkflowNodeExecutionModel,
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outputs: Mapping[str, Any] | None,
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workflow_execution_id: str | None,
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) -> dict[str, Any]:
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metadata = execution.execution_metadata_dict
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node_outputs = outputs if outputs is not None else execution.outputs_dict
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execution_id = workflow_execution_id or execution.workflow_run_id or execution.id
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return {
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"workflow_id": execution.workflow_id,
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"workflow_execution_id": execution_id,
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"tenant_id": execution.tenant_id,
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"app_id": execution.app_id,
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"node_execution_id": execution.id,
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"node_id": execution.node_id,
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"node_type": execution.node_type,
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"title": execution.title,
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"status": execution.status,
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"error": execution.error,
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"elapsed_time": execution.elapsed_time,
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"index": execution.index,
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"predecessor_node_id": execution.predecessor_node_id,
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"created_at": execution.created_at,
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"finished_at": execution.finished_at,
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"total_tokens": metadata.get(WorkflowNodeExecutionMetadataKey.TOTAL_TOKENS, 0),
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"total_price": metadata.get(WorkflowNodeExecutionMetadataKey.TOTAL_PRICE, 0.0),
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"currency": metadata.get(WorkflowNodeExecutionMetadataKey.CURRENCY),
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"tool_name": (metadata.get(WorkflowNodeExecutionMetadataKey.TOOL_INFO) or {}).get("tool_name")
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if isinstance(metadata.get(WorkflowNodeExecutionMetadataKey.TOOL_INFO), dict)
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else None,
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"iteration_id": metadata.get(WorkflowNodeExecutionMetadataKey.ITERATION_ID),
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"iteration_index": metadata.get(WorkflowNodeExecutionMetadataKey.ITERATION_INDEX),
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"loop_id": metadata.get(WorkflowNodeExecutionMetadataKey.LOOP_ID),
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"loop_index": metadata.get(WorkflowNodeExecutionMetadataKey.LOOP_INDEX),
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"parallel_id": metadata.get(WorkflowNodeExecutionMetadataKey.PARALLEL_ID),
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"node_inputs": execution.inputs_dict,
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"node_outputs": node_outputs,
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"process_data": execution.process_data_dict,
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}
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