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fix: 修复了字段名bug

This commit is contained in:
朝夕 2026-04-26 21:37:20 +08:00
parent e6bf9e2ce4
commit 913648a071
10 changed files with 43 additions and 84 deletions
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10
docs/problem.md
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@ -1,13 +1,11 @@
待解决问题
---
## 问题栏
#### 🔴 核心缺陷与修复 (Bug Fixes & Stability)
## 待解决问题
## 问题栏
#### 🔴 核心缺陷与修复 (Bug Fixes & Stability)
#### 🛡️ 安全与合规 (Security & Auth)
#### ⚡ 性能与资源优化 (Performance & Scalability)
#### 🏗️ 架构演进 (Architecture & Refactoring)

10
pretor/api/workflow.py
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@ -19,16 +19,16 @@ from fastapi import APIRouter, WebSocket, WebSocketDisconnect
workflow_router = APIRouter(prefix="/api/v1/workflow", tags=["workflow"])
@workflow_router.websocket("/ws/{event_id}")
async def get_workflow(websocket: WebSocket, event_id: str):
@workflow_router.websocket("/ws/{trace_id}")
async def get_workflow(websocket: WebSocket, trace_id: str):
await websocket.accept()
global_state_machine = ray_actor_hook("global_state_machine")
try:
while True:
await websocket.send(await global_state_machine.get_workflow.remote(event_id))
await websocket.send_text(await global_state_machine.get_pending.remote(event_id))
await websocket.send(await global_state_machine.get_workflow.remote(trace_id))
await websocket.send_text(await global_state_machine.get_pending.remote(trace_id))
response = await websocket.receive_text()
await global_state_machine.put_received(event_id, response)
await global_state_machine.put_received(trace_id, response)
except WebSocketDisconnect:
pass
except RuntimeError as e:

10
pretor/core/database/table/individual.py
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@ -13,7 +13,7 @@
# limitations under the License.
from sqlmodel import SQLModel, Field
from typing import List, Dict
from typing import List, Optional
from sqlalchemy import Column, JSON
from enum import Enum
@ -30,8 +30,8 @@ class WorkerIndividual(SQLModel, table=True):
description: str = Field(nullable=False)
provider_title: str
model_id: str
system_prompt: str
output_template: dict = Field(sa_column=Column(JSON),description="输出模板标识")
bound_skill: Dict[str, List[str]] = Field(sa_column=Column(JSON))
workspace: List[str] = Field(sa_column=Column(JSON))
system_prompt: Optional[dict]
output_template: Optional[dict] = Field(sa_column=Column(JSON),description="输出模板标识")
bound_skill: Optional[str] = Field(sa_column=Column(JSON))
workspace: Optional[List[str]] = Field(sa_column=Column(JSON))
owner_id: str

38
pretor/core/global_state_machine/global_state_machine.py
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@ -116,31 +116,31 @@ class GlobalStateMachine:
def add_event(self, event: PretorEvent) -> None:
event.pending_queue = asyncio.Queue()
event.receive_queue = asyncio.Queue()
self.event_dict[event.event_id] = event
self.event_dict[event.trace_id] = event
def delete_event(self, event_id: str) -> None:
del self.event_dict[event_id]
def delete_event(self, trace_id: str) -> None:
del self.event_dict[trace_id]
def get_event(self, event_id: str) -> PretorEvent:
return self.event_dict.get(event_id, None)
def get_event(self, trace_id: str) -> PretorEvent:
return self.event_dict.get(trace_id, None)
def update_attachment(self, event_id: str, attachment: Dict[str, str]) -> None:
self.event_dict[event_id].attachment = attachment
def update_attachment(self, trace_id: str, attachment: Dict[str, str]) -> None:
self.event_dict[trace_id].attachment = attachment
def update_workflow(self, event_id: str, workflow: PretorWorkflow) -> None:
self.event_dict[event_id].workflow = workflow
def update_workflow(self, trace_id: str, workflow: PretorWorkflow) -> None:
self.event_dict[trace_id].workflow = workflow
def get_workflow(self, event_id: str) -> PretorWorkflow:
return self.event_dict[event_id].workflow
def get_workflow(self, trace_id: str) -> PretorWorkflow:
return self.event_dict[trace_id].workflow
async def put_pending(self, event_id, item) -> None:
await self.event_dict[event_id].pending_queue.put(item)
async def put_pending(self, trace_id, item) -> None:
await self.event_dict[trace_id].pending_queue.put(item)
async def get_pending(self, event_id) -> str:
return await self.event_dict[event_id].pending_queue.get()
async def get_pending(self, trace_id) -> str:
return await self.event_dict[trace_id].pending_queue.get()
async def put_received(self, event_id, item) -> None:
await self.event_dict[event_id].receive_queue.put(item)
async def put_received(self, trace_id, item) -> None:
await self.event_dict[trace_id].receive_queue.put(item)
async def get_received(self, event_id) -> str:
return await self.event_dict[event_id].receive_queue.get()
async def get_received(self, trace_id) -> str:
return await self.event_dict[trace_id].receive_queue.get()

5
pretor/core/individual/control_node/control_node.py
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@ -68,9 +68,8 @@ class ControlNode:
prompt += (
f"=== 当前任务步骤上下文 ===\n"
f"- 步骤名称 (Name): {ctx.deps.workflow_step.name}\n"
f"- 步骤目标/描述 (Description): {ctx.deps.workflow_step.description}\n"
f"- 前置步骤结果参考 (Previous Results): {ctx.deps.workflow_step.precondition}\n"
f"- 可用工具 (Available Tools): {ctx.deps.current_tools}\n"
f"- 步骤目标/描述 (Description): {ctx.deps.workflow_step.desc}\n"
f"- 前置输入（input）: {ctx.deps.workflow_step.input}\n"
)
return prompt

2
pretor/core/individual/supervisory_node/template.py
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@ -23,7 +23,7 @@ class ForUser(SupervisoryNodeResponse):
context: str = Field(..., description="对用户的回复，应当使用和蔼的语气进行回复。用于直接解答简单问题或返回最终报告。")
class ForConsciousnessNode(SupervisoryNodeResponse):
orkflow_template: str = Field(..., description="选择的工作流模板的名称，用于处理复杂任务。")
workflow_template: str = Field(..., description="选择的工作流模板的名称，用于处理复杂任务。")
reasoning: str = Field(..., description="选择将任务移交意识节点并选用该模板的简短原因。")
class TerminationMessage(BaseModel):

5
pretor/core/workflow/workflow.py
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@ -14,7 +14,6 @@
from typing import List, Optional, Union, Literal, Dict, Any
from pydantic import BaseModel, Field, model_validator
from pretor.utils.demand_protocol import DemandProtocol
from pretor.utils.logger import get_logger
logger = get_logger('workflow')
@ -33,6 +32,7 @@ class LogicGate(BaseModel):
class WorkStep(BaseModel):
step: int = Field(..., gt=0, description="步骤序号，严格自增")
name: str = Field(..., description="步骤名称")
node: NodeType = Field(..., description="负责执行的节点类型")
action: str = Field(..., description="执行的原子动作")
desc: str = Field(..., description="动作细节的自然语言描述，包含人工规范指导")
@ -56,7 +56,6 @@ class WorkflowStatus(BaseModel):
default="waiting_llm_working",
description="当前系统调度状态"
)
demand: DemandProtocol = Field(default=None, description="需要的资源或插件调用请求")
class PretorWorkflow(BaseModel):
title: str = Field(..., description="工作流的标题")
@ -68,7 +67,7 @@ class PretorWorkflow(BaseModel):
command: Optional[str] = Field(default=None, description="触发此工作流的原始命令")
output: Dict[str, Any] = Field(default_factory=dict, description="工作流最终产出结果")
status: WorkflowStatus = Field(default_factory=WorkflowStatus, description="运行时状态对象")
event_info: EventInfo | None = Field(default_factory=None)
event_info: EventInfo | None = Field(default=None)
context_memory: Dict[str, Any] = Field(default_factory=dict)
@model_validator(mode='after')

2
pretor/core/workflow/workflow_runner.py
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@ -210,7 +210,7 @@ class WorkflowEngine:
agent_id = input_data.get("agent_id")
task_event = {
"action": step.action,
"description": step.description,
"description": step.desc,
"input_data": input_data,
"context_memory": self.workflow.context_memory
}

8
pretor/plugin/tool_plugin/approval/approval.py
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@ -23,17 +23,17 @@ class ApprovalToolData(BaseToolData):
config_args: Dict[str, str] = {}
async def approval(message: str, event_id: str) -> str:
async def approval(message: str, trace_id: str) -> str:
"""
当任务存在某些高风险操作或者计划需要让用户审批，发送请求给用户等待用户审批
Args:
message: 发送给用户的请求
event_id:
trace_id:
Returns:
用户的审批结果
"""
actor_list = ray_actor_hook("global_state_machine")
await actor_list.global_state_machine.put_pending.remote(event_id, message)
reply = await actor_list.global_state_machine.get_received.remote(event_id)
await actor_list.global_state_machine.put_pending.remote(trace_id, message)
reply = await actor_list.global_state_machine.get_received.remote(trace_id)
return reply

37
pretor/utils/demand_protocol.py
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@ -1,37 +0,0 @@
# Copyright 2026 zhaoxi826
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import Dict, Any, Literal
from pydantic import BaseModel, Field
# --- 1. 给 Individual (LLM/Agent) 的具体需求 ---
class IndividualDemand(BaseModel):
role_prompt: str = Field(..., description="赋予该个体的角色定义")
task_goal: str = Field(..., description="该个体的具体执行目标")
expected_output: str = Field(..., description="期望产出的数据结构或格式描述")
# --- 2. 给 Tool (插件/函数调用) 的具体需求 ---
class ToolDemand(BaseModel):
method: str = Field(..., description="插件调用的具体方法名")
args: Dict[str, Any] = Field(default_factory=dict, description="传递给插件的参数")
# --- 3. 给 System (系统/物理资源) 的具体需求 ---
class SystemDemand(BaseModel):
operation: Literal["allocate_resource", "docker_manage", "file_io", "network"]
params: Dict[str, Any] = Field(..., description="操作所需的物理参数，如 GPU 核心数、路径等")
# --- 4. 统一需求入口 (裁判官协议体) ---
class DemandProtocol(BaseModel):
variety: Literal["individual", "tool", "system"]
name: str = Field(..., description="目标名称（如：python_expert, pytest_tool, docker_engine）")