Build lightweight AI agent admin

2026-06-08 18:14:59 +08:00
commit e164840f43
2530 changed files with 435693 additions and 0 deletions
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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+工作流执行任务 - 供定时任务调度器调用
+"""
+import logging
+
+logger = logging.getLogger(__name__)
+
+
+async def execute_workflow_task(
+    job_code: str = None,
+    workflow_code: str = None,
+    inputs: dict = None,
+    **kwargs
+):
+    """
+    执行工作流任务
+
+    在定时任务中调用已发布的数据处理/自动化工作流。
+
+    Args:
+        job_code: 任务编码（由调度器自动传入）
+        workflow_code: 要执行的工作流编码（必填）
+        inputs: 工作流输入变量
+        **kwargs: 其他参数（包含 task_logger）
+
+    Returns:
+        dict: 执行结果
+    """
+    if not workflow_code:
+        raise ValueError("workflow_code 参数不能为空，请在 task_kwargs 中配置")
+
+    inputs = inputs or {}
+    inputs['job_code'] = job_code
+
+    from app.database import AsyncSessionLocal
+    from ai_platform.services.workflow_service import AIWorkflowService
+    from ai_platform.models.workflow import AIWorkflow
+    from sqlalchemy import select
+    from scheduler.task_utils import TaskLoggerWrapper
+
+    log = TaskLoggerWrapper(job_code, kwargs.get('task_logger'))
+    await log.info(f"开始执行工作流: {workflow_code}")
+
+    async with AsyncSessionLocal() as db:
+        result = await db.execute(
+            select(AIWorkflow).where(
+                AIWorkflow.code == workflow_code,
+                AIWorkflow.is_deleted == False
+            )
+        )
+        workflow = result.scalar_one_or_none()
+
+        if not workflow:
+            raise ValueError(f"工作流不存在: {workflow_code}")
+
+        if workflow.workflow_type not in ('data_process', 'automation'):
+            raise ValueError(
+                f"工作流类型不支持定时执行: {workflow.workflow_type}，"
+                f"仅支持 data_process 和 automation 类型"
+            )
+
+        if workflow.status != 'published':
+            raise ValueError(f"工作流未发布: {workflow_code}")
+
+        await log.info(
+            f"工作流类型: {workflow.workflow_type}, "
+            f"工作流名称: {workflow.name}, "
+            f"输入变量: {list(inputs.keys())}"
+        )
+
+        service = AIWorkflowService(db)
+        run = await service.run_workflow(
+            workflow_id=str(workflow.id),
+            inputs=inputs,
+            trigger_type='api',
+        )
+
+        await log.info(
+            f"工作流执行完成: status={run.status}, "
+            f"elapsed_time={run.elapsed_time}ms, "
+            f"total_steps={run.total_steps}"
+        )
+
+        if run.status == 'failed':
+            raise RuntimeError(f"工作流执行失败: {run.error_message}")
+
+        return {
+            'run_id': str(run.id),
+            'workflow_code': workflow_code,
+            'workflow_name': workflow.name,
+            'status': run.status,
+            'elapsed_time': run.elapsed_time,
+            'total_steps': run.total_steps,
+            'total_tokens': run.total_tokens,
+            'outputs': run.outputs,
+        }