feat(memory): add protected memory config deletion with end-user safeguards
- Add force parameter to delete_config endpoint for controlled deletion of in-use configs - Implement MemoryConfigService.delete_config with protection against deleting default configs - Add validation to prevent deletion of configs with connected end-users unless force=True - Reorganize controller imports to remove duplicates and improve maintainability - Clean up unused database connection management code from memory_storage_controller - Add detailed docstring to delete_config endpoint explaining protection mechanisms - Update error handling with specific BizCode.RESOURCE_IN_USE for configs in active use - Add comprehensive logging for deletion attempts, warnings, and affected users - Refactor ConfigParamsDelete schema usage to use MemoryConfigService directly - Improve API response structure with affected_users count and force_required flag
This commit is contained in:
Ke Sun
@@ -9,28 +9,35 @@
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"""
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import datetime
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import uuid
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from typing import Optional, List, Dict, Any, Tuple, Annotated
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from typing import Annotated, Any, Dict, List, Optional, Tuple
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from fastapi import Depends
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from sqlalchemy import select, func, or_, and_
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from sqlalchemy import and_, func, or_, select
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from sqlalchemy.orm import Session
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from app.core.error_codes import BizCode
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from app.core.exceptions import (
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ResourceNotFoundException,
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BusinessException,
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ResourceNotFoundException,
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)
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from app.core.logging_config import get_business_logger
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from app.core.workflow.validator import WorkflowValidator
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from app.db import get_db
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from app.models import App, AgentConfig, AppRelease, MultiAgentConfig, WorkflowConfig
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from app.models import (
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AgentConfig,
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App,
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AppRelease,
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AppShare,
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MultiAgentConfig,
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WorkflowConfig,
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Workspace,
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)
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from app.models.app_model import AppStatus, AppType
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from app.repositories.app_repository import get_apps_by_id
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from app.repositories.workflow_repository import WorkflowConfigRepository
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from app.schemas import app_schema
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from app.schemas.workflow_schema import WorkflowConfigUpdate
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from app.services.agent_config_converter import AgentConfigConverter
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from app.models import AppShare, Workspace
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from app.services.model_service import ModelApiKeyService
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from app.services.workflow_service import WorkflowService
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from app.utils.app_config_utils import model_parameters_to_dict
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@@ -136,9 +143,10 @@ class AppService:
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return app
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def _check_workflow_config(self, app_id: uuid.UUID):
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from app.models import WorkflowConfig, ModelConfig
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from sqlalchemy import select
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from app.core.exceptions import BusinessException
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from app.models import ModelConfig, WorkflowConfig
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# 2. 获取 Agent 配置
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stmt = select(WorkflowConfig).where(AgentConfig.app_id == app_id)
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agent_cfg = self.db.scalars(stmt).first()
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@@ -154,9 +162,10 @@ class AppService:
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raise BusinessException("模型配置不存在，无法试运行", BizCode.AGENT_CONFIG_MISSING)
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def _check_agent_config(self, app_id: uuid.UUID):
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from app.models import AgentConfig, ModelConfig
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from sqlalchemy import select
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from app.core.exceptions import BusinessException
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from app.models import AgentConfig, ModelConfig
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# 2. 获取 Agent 配置
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stmt = select(AgentConfig).where(AgentConfig.app_id == app_id)
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agent_cfg = self.db.scalars(stmt).first()
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@@ -326,10 +335,10 @@ class AppService:
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"""
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# 将 Dict 转换为 MultiAgentConfigCreate
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from app.schemas.multi_agent_schema import (
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ExecutionConfig,
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MultiAgentConfigCreate,
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SubAgentConfig,
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RoutingRule,
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ExecutionConfig
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SubAgentConfig,
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)
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# 转换 sub_agents
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@@ -1167,6 +1176,138 @@ class AppService:
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return default_config
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# ==================== 记忆配置提取方法 ====================
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def _extract_memory_config_id(
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self,
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app_type: str,
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config: Dict[str, Any]
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) -> Optional[uuid.UUID]:
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"""从发布配置中提取 memory_config_id（根据应用类型分发）
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Args:
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app_type: 应用类型 (agent, workflow, multi_agent)
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config: 发布配置字典
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Returns:
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Optional[uuid.UUID]: 提取的 memory_config_id，如果不存在则返回 None
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"""
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if app_type == AppType.AGENT:
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return self._extract_memory_config_id_from_agent(config)
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elif app_type == AppType.WORKFLOW:
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return self._extract_memory_config_id_from_workflow(config)
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elif app_type == AppType.MULTI_AGENT:
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# Multi-agent 暂不支持记忆配置提取
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logger.debug(f"多智能体应用暂不支持记忆配置提取: app_type={app_type}")
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return None
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else:
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logger.warning(f"不支持的应用类型，无法提取记忆配置: app_type={app_type}")
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return None
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def _extract_memory_config_id_from_agent(
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self,
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config: Dict[str, Any]
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) -> Optional[uuid.UUID]:
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"""从 Agent 应用配置中提取 memory_config_id
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路径: config.memory.memory_content
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Args:
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config: Agent 配置字典
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Returns:
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Optional[uuid.UUID]: 记忆配置ID，如果不存在则返回 None
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"""
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try:
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memory_content = config.get("memory", {}).get("memory_content")
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if memory_content:
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# 处理字符串和 UUID 两种情况
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if isinstance(memory_content, str):
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return uuid.UUID(memory_content)
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elif isinstance(memory_content, uuid.UUID):
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return memory_content
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else:
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logger.warning(
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f"Agent 配置中 memory_content 格式无效: type={type(memory_content)}, "
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f"value={memory_content}"
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)
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return None
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except (ValueError, TypeError) as e:
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logger.warning(
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f"Agent 配置中 memory_content 格式无效: error={str(e)}, "
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f"memory_content={memory_content}"
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)
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return None
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def _extract_memory_config_id_from_workflow(
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self,
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config: Dict[str, Any]
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) -> Optional[uuid.UUID]:
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"""从 Workflow 应用配置中提取 memory_config_id
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扫描工作流节点，查找 MemoryRead 或 MemoryWrite 节点。
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返回第一个找到的记忆节点的 config_id。
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Args:
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config: Workflow 配置字典
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Returns:
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Optional[uuid.UUID]: 记忆配置ID，如果不存在则返回 None
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"""
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nodes = config.get("nodes", [])
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for node in nodes:
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node_type = node.get("type", "")
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# 检查是否为记忆节点
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if node_type in ["MemoryRead", "MemoryWrite"]:
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config_id = node.get("config", {}).get("config_id")
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if config_id:
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try:
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# 处理字符串和 UUID 两种情况
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if isinstance(config_id, str):
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return uuid.UUID(config_id)
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elif isinstance(config_id, uuid.UUID):
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return config_id
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else:
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logger.warning(
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f"工作流记忆节点 config_id 格式无效: node_id={node.get('id')}, "
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f"node_type={node_type}, type={type(config_id)}"
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)
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except (ValueError, TypeError) as e:
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logger.warning(
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f"工作流记忆节点 config_id 格式无效: node_id={node.get('id')}, "
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f"node_type={node_type}, error={str(e)}"
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)
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logger.debug("工作流配置中未找到记忆节点")
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return None
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def _update_endusers_memory_config(
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self,
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app_id: uuid.UUID,
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memory_config_id: uuid.UUID
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) -> int:
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"""批量更新应用下所有终端用户的 memory_config_id
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Args:
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app_id: 应用ID
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memory_config_id: 新的记忆配置ID
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Returns:
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int: 更新的终端用户数量
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"""
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from app.repositories.end_user_repository import EndUserRepository
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repo = EndUserRepository(self.db)
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updated_count = repo.batch_update_memory_config_id(
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app_id=app_id,
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memory_config_id=memory_config_id
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)
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return updated_count
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# ==================== 应用发布管理 ====================
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def publish(
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@@ -1309,6 +1450,15 @@ class AppService:
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self.db.add(release)
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self.db.flush() # 先 flush，确保 release 已插入数据库
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# 提取记忆配置ID并更新终端用户
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memory_config_id = self._extract_memory_config_id(app.type, config)
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if memory_config_id:
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updated_count = self._update_endusers_memory_config(app_id, memory_config_id)
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logger.info(
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f"发布时更新终端用户记忆配置: app_id={app_id}, "
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f"memory_config_id={memory_config_id}, updated_count={updated_count}"
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)
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# 更新当前发布版本指针
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app.current_release_id = release.id
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app.status = AppStatus.ACTIVE
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@@ -1424,6 +1574,15 @@ class AppService:
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)
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raise ResourceNotFoundException("发布版本", f"app_id={app_id}, version={version}")
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# 提取记忆配置ID并更新终端用户
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memory_config_id = self._extract_memory_config_id(release.type, release.config)
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if memory_config_id:
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updated_count = self._update_endusers_memory_config(app_id, memory_config_id)
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logger.info(
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f"回滚时更新终端用户记忆配置: app_id={app_id}, version={version}, "
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f"memory_config_id={memory_config_id}, updated_count={updated_count}"
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)
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app.current_release_id = release.id
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app.updated_at = datetime.datetime.now()
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@@ -1839,8 +1998,8 @@ class AppService:
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Returns:
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Dict: 对比结果
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"""
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from app.services.draft_run_service import DraftRunService
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from app.models import ModelConfig
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from app.services.draft_run_service import DraftRunService
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logger.info(
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"多模型对比试运行",
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@@ -1938,8 +2097,8 @@ class AppService:
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Yields:
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str: SSE 格式的事件数据
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"""
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from app.services.draft_run_service import DraftRunService
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from app.models import ModelConfig
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from app.services.draft_run_service import DraftRunService
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logger.info(
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"多模型对比流式试运行",
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