zhaoxi
209ba45477
Removes the deprecated `workflow_template` concept entirely across both backend API routers, internal logic handling within the `supervisory_node` and `consciousness_node`, and front-end components. Enables `consciousness_node` to work autonomously. Also refactors core package structure to enforce the "one python package, one Ray Actor" architectural rule. `GlobalWorkflowManager`, `WorkflowRunningEngine`, `PostgresDatabase`, and `WorkerCluster` have been moved to their own top-level decoupled package directories with properly exported `__init__.py` modules. Test suites have been relocated and import paths updated across the system. Co-authored-by: google-labs-jules[bot] <161369871+google-labs-jules[bot]@users.noreply.github.com> Co-authored-by: zhaoxi826 <198742034+zhaoxi826@users.noreply.github.com>
51 lines
2.2 KiB
Python
51 lines
2.2 KiB
Python
# Copyright 2026 zhaoxi826
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from pretor.worker_individual.base_individual import (
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BaseIndividual,
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WorkerIndividualDeps,
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)
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from pretor.utils.logger import get_logger
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logger = get_logger("special_individual")
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class SpecialIndividual(BaseIndividual):
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"""
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特殊子个体：执行特殊任务的 agent，如生成语音、视频等。
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"""
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def __init__(self, agent_config: dict):
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super().__init__(agent_config)
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async def run(self, task_event: dict) -> dict:
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"""执行与 run 相关的核心业务流转操作。
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该方法封装了具体的算法策略或状态控制逻辑，确保操作能够在事务上下文中被原子且一致地执行。
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Args: task_event (dict): 由事件总线或工作流引擎分发过来的事件载荷，封装了触发此次调用的上下文快照与任务目标指令。
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Returns: (dict): 高度聚合的字典结构数据，将多维度的属性特征或统计指标组合后一并返回。"""
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if self.agent is None:
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system_prompt = self.agent_config.get(
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"prompt", "你是一个特殊的AI助手，负责处理特殊类型的任务。"
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)
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await self._init_agent("special_individual", system_prompt)
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deps = WorkerIndividualDeps(task_event=task_event)
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self.agent.retries = 3
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try:
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result = await self.agent.run(f"请执行以下任务：\n{task_event}", deps=deps)
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return {"output": result.data.output}
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except Exception as e:
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logger.exception(f"SpecialIndividual {self.agent_id} 执行失败: {e}")
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raise
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