Files
company-ai-platform/app/application/feishu/handlers/rules.py
JiuContinent db751f03b4 ```
refactor(Dockerfile): 使用requirements.txt替代硬编码依赖

将Dockerfile中的硬编码pip包列表替换为通过requirements.txt文件安装,
提高依赖管理的灵活性和可维护性。

feat(scheduling): 移除内置APScheduler,采用独立调度系统

移除app/core/background/scheduler.py中原来的APScheduler实现,
改为使用新的应用级调度系统app.application.scheduling。

refactor(task_queue): 调整任务队列模块结构和导入路径

将任务队列相关常量从app.core.background.task_queue.constants迁移至
app.tasks.constants,并更新所有相关导入路径和引用。

refactor(events): 将事件服务重构为独立的应用层组件

将事件分发逻辑从核心层迁移到应用层,使用app.application.events.EventDispatchService
替代原有的app.modules.events.services.EventService。

feat(ai_memory): 增强AI记忆自动写入的安全策略

新增ai_memory_blocked_content_terms配置项用于阻止敏感内容,
添加TTL过期机制控制自动写入条目的生命周期。

fix(security): 强化生产环境安全验证机制

增加model_validator确保生产环境中数据库连接、API密钥、CORS设置等
关键安全配置符合要求。

feat(risks): 优化风险事件操作动作的外键约束

为RiskEventAction模型的风险事件ID字段添加外键约束,
防止孤立记录并增强数据完整性。

refactor(audit): 优化审计服务方法命名和事务处理

将AuditService的log方法重命名为record以反映其阶段行为,
并调整事务提交时机以提高性能。

feat(events): 增强领域事件并发处理和响应模型

添加事件锁定机制防止重复处理,更新API响应模型以提供
更准确的数据类型定义。
```
2026-07-15 16:36:42 +08:00

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import re
from typing import Any
from fastapi import HTTPException
from sqlalchemy.orm import Session
from app.application.feishu.delivery import send_text_if_configured
from app.application.feishu.results import command_result
from app.core.config import get_settings
from app.modules.ai_memory.constants import AIMemoryStatus
from app.modules.ai_memory.service import AIMemoryService
from app.modules.feishu.constants import FeishuCommandName, FeishuReplyType
from app.modules.feishu.service import FeishuService
RULE_TITLE = "AI 学习规则"
RULE_CREATE_PATTERN = re.compile(r"^学习规则(?:\s+(\d{1,3}))?\s*[:]\s*(.*)$")
MARKET_RULE_CREATE_PATTERN = re.compile(
r"^学习市场规则(?:\s+(\d{1,3}))?\s*[:]\s*(.*)$"
)
RULE_DISABLE_PATTERN = re.compile(r"^停用规则\s+(MEM-[A-Za-z0-9-]+)$", re.IGNORECASE)
RULE_ENABLE_PATTERN = re.compile(r"^启用规则\s+(MEM-[A-Za-z0-9-]+)$", re.IGNORECASE)
RULE_LIST_COMMANDS = {"查看规则", "规则列表", "查看市场规则"}
RULE_COMMAND_PREFIXES = (
"学习市场规则",
"学习规则",
"查看市场规则",
"查看规则",
"规则列表",
"停用规则",
"启用规则",
)
RULE_COMMAND_HELP = (
"规则指令格式:\n"
"学习规则:<规则内容>\n"
"学习规则 80<规则内容>\n"
"学习市场规则 80<仅用于市场分析的规则内容>\n"
"查看规则\n"
"停用规则 <规则编号>\n"
"启用规则 <规则编号>"
)
def handle_rule_command(
db: Session,
feishu: FeishuService,
command_text: str,
chat_id: str | None,
actor: str,
auto_reply: bool,
) -> dict[str, Any] | None:
"""Handle persistent AI rule commands."""
if not command_text.startswith(RULE_COMMAND_PREFIXES):
return None
command = _command_name(command_text)
if command in {
FeishuCommandName.RULE_CREATE,
FeishuCommandName.RULE_DISABLE,
FeishuCommandName.RULE_ENABLE,
} and get_settings().read_only_mode:
return _result(
feishu,
command,
"当前为只读模式,不能新增或修改学习规则。请由管理员启用操作后重试。",
chat_id,
actor,
auto_reply,
)
content = RULE_COMMAND_HELP
try:
command, content = _execute(db, command_text, command, actor)
except HTTPException as exc:
detail = str(exc.detail)
if "secret-like" in detail:
content = "规则疑似包含密码、令牌或其他密钥信息,已拒绝学习。"
elif exc.status_code == 404:
content = "没有找到该规则,请先发送“查看规则”确认规则编号。"
elif "priority" in detail:
content = "规则优先级必须在 1 到 100 之间。"
else:
content = "规则未保存,请检查指令内容后重试。"
return _result(feishu, command, content, chat_id, actor, auto_reply)
def _execute(
db: Session,
command_text: str,
command: FeishuCommandName,
actor: str,
) -> tuple[FeishuCommandName, str]:
market_create_match = MARKET_RULE_CREATE_PATTERN.fullmatch(command_text)
create_match = market_create_match or RULE_CREATE_PATTERN.fullmatch(command_text)
disable_match = RULE_DISABLE_PATTERN.fullmatch(command_text)
enable_match = RULE_ENABLE_PATTERN.fullmatch(command_text)
memory = AIMemoryService(db)
if create_match:
return command, _create_rule(memory, create_match, market_create_match is not None, actor)
if command_text in RULE_LIST_COMMANDS:
return FeishuCommandName.RULE_LIST, _list_rules(memory, command_text)
if disable_match or enable_match:
enabled = enable_match is not None
match = enable_match or disable_match
rule = memory.update_rule(
code=match.group(1),
content=None,
priority=None,
tags=None,
enabled=enabled,
actor=actor,
)
state = "已启用" if enabled else "已停用"
return (
FeishuCommandName.RULE_ENABLE if enabled else FeishuCommandName.RULE_DISABLE,
f"规则{state}\n"
f"编号:{rule['code']}\n"
f"优先级:{rule['importance']}\n"
f"范围:{rule['scope']} / {rule['subject']}\n"
f"状态:{state}",
)
return command, RULE_COMMAND_HELP
def _create_rule(
memory: AIMemoryService,
match: re.Match[str],
market_rule: bool,
actor: str,
) -> str:
priority = int(match.group(1) or 50)
content = match.group(2).strip()
if not content:
return f"规则内容不能为空。\n\n{RULE_COMMAND_HELP}"
if not 1 <= priority <= 100:
return "规则优先级必须在 1 到 100 之间。"
rule = memory.create_rule(
content=content,
scope="market" if market_rule else "global",
subject="market" if market_rule else "company",
priority=priority,
tags=["feishu", *(["market"] if market_rule else [])],
actor=actor,
)
return (
"规则已学习。\n"
f"编号:{rule['code']}\n"
f"优先级:{rule['importance']}\n"
f"范围:{rule['scope']} / {rule['subject']}\n"
"状态:已启用"
)
def _list_rules(memory: AIMemoryService, command_text: str) -> str:
rules = memory.list_rules(
scope="market" if command_text == "查看市场规则" else None,
status_filter=AIMemoryStatus.ACTIVE,
limit=20,
)
if not rules:
return "当前没有已启用的学习规则。"
lines = ["当前已启用的学习规则:"]
for rule in rules:
rule_text = str(rule["content"])
if len(rule_text) > 80:
rule_text = f"{rule_text[:80]}"
lines.append(
f"{rule['code']}|优先级 {rule['importance']}"
f"{rule['scope']}/{rule['subject']}\n{rule_text}"
)
return "\n\n".join(lines)
def _command_name(command_text: str) -> FeishuCommandName:
if command_text.startswith("停用规则"):
return FeishuCommandName.RULE_DISABLE
if command_text.startswith("启用规则"):
return FeishuCommandName.RULE_ENABLE
if command_text.startswith(("查看市场规则", "查看规则", "规则列表")):
return FeishuCommandName.RULE_LIST
return FeishuCommandName.RULE_CREATE
def _result(
feishu: FeishuService,
command: FeishuCommandName,
content: str,
chat_id: str | None,
actor: str,
auto_reply: bool,
) -> dict[str, Any]:
response = send_text_if_configured(feishu, chat_id, content, actor) if auto_reply else None
return command_result(command, FeishuReplyType.TEXT, RULE_TITLE, content, response)