Files
company-ai-platform/app/modules/ai_agent/constants.py
JiuContinent ae5990eaef ```
feat(core): 添加API认证主体配置和安全验证

- 在Settings中添加api_actor字段,用于标识API调用方身份
- 创建ApiPrincipal数据类来表示服务主体
- 修改require_api_key函数返回认证的服务主体信息
- 更新配置文件引入ActorValue常量

feat(ai_agent): 增强OpenClaw工具调用的安全性检查

- 实现_openclaw_allowed_tools和openclaw_allowed_actions配置项
- 添加CSV列表解析验证器
- 实现工具和操作权限检查方法_ensure_tool_allowed
- 在工具调用前验证允许的工具和操作类型

feat(security): 强化API密钥认证和审计安全性

- 更新require_api_key函数在缺少API_KEY时抛出异常
- 在AI代理、审批、飞书等模块的路由中统一使用ApiPrincipal获取调用方信息
- 替换硬编码的ActorValue.API为动态的principal.actor

feat(audit): 实现安全审计负载脱敏处理

- 添加敏感键名集合AI_AUDIT_SENSITIVE_KEYS
- 实现审计安全负载处理函数_audit_safe_payload
- 支持深度遍历、文本截断、序列限制和敏感信息脱敏
- 在AI服务的审计日志中应用安全负载处理

feat(approval): 完善审批流程的申请人身份验证

- 更新审批创建接口使用认证主体作为申请人
- 使用utc_now替换datetime.utcnow确保时间一致性
- 修复审批逻辑中的条件判断问题

feat(business): 加强业务领域高风险操作的审批控制

- 为高风险域创建统一的审批验证方法_ensure_approved
- 在创建和更新操作中强制要求审批票证
- 为项目同步功能添加认证主体参数

feat(config): 统一时间处理使用UTC时间函数

- 创建并使用utc_now函数替代datetime.utcnow
- 在审批、审计、业务、遗留数据等模块中更新时间戳处理

feat(constants): 扩展风险事件类型和报告指标

- 添加新风险事件类型到GENERATED_RISK_EVENT_TYPES
- 为报告模块添加外部开放和高风险事件指标

refactor(feishu): 增强飞书验证令牌安全检查

- 确保飞书验证令牌配置存在时才接受请求
- 修正令牌验证逻辑以提高安全性
```
2026-07-06 00:11:44 +08:00

150 lines
3.6 KiB
Python

from enum import StrEnum
class AIProviderName(StrEnum):
NOOP = "noop"
OPENCLAW = "openclaw"
HERMES = "hermes"
OPENCLAW_HERMES = "openclaw_hermes"
OPENCLAW_HERMES_DASH = "openclaw-hermes"
HYBRID = "hybrid"
DIRECT_LLM = "direct_llm"
class AIResponseKey(StrEnum):
PROVIDER = "provider"
ANSWER = "answer"
RAW = "raw"
RESULT = "result"
OK = "ok"
ERROR = "error"
MESSAGE = "message"
TYPE = "type"
BASE_URL = "base_url"
HEALTH = "health"
HEALTHZ = "healthz"
READYZ = "readyz"
DATA = "data"
STATUS_CODE = "status_code"
TEXT = "text"
PIPELINE = "pipeline"
HERMES_RECALL = "hermes_recall"
HERMES_ANSWER = "hermes_answer"
HERMES_REMEMBER = "hermes_remember"
OPENCLAW = "openclaw"
TOOL = "tool"
TOOL_INVOKED = "tool_invoked"
TOOL_ERROR = "tool_error"
class AIRequestKey(StrEnum):
PROMPT = "prompt"
CONTEXT = "context"
class AIContextKey(StrEnum):
OPENCLAW_TOOL = "openclaw_tool"
OPENCLAW_ACTION = "openclaw_action"
OPENCLAW_ARGS = "openclaw_args"
OPENCLAW_SESSION_KEY = "openclaw_session_key"
AGENT_PIPELINE = "agent_pipeline"
HERMES_MEMORY = "hermes_memory"
OPENCLAW = "openclaw"
MODE = "mode"
USER_PROMPT = "user_prompt"
REQUEST_CONTEXT = "request_context"
ASSISTANT_ANSWER = "assistant_answer"
class AIMemoryMode(StrEnum):
RECALL = "memory_recall"
WRITE = "memory_write"
class AIHttpPath(StrEnum):
CHAT_COMPLETIONS = "/chat/completions"
HEALTH = "/health"
HEALTHZ = "/healthz"
READYZ = "/readyz"
TOOLS_INVOKE = "/tools/invoke"
V1 = "/v1"
class AIHttpHeader(StrEnum):
AUTHORIZATION = "Authorization"
HERMES_SESSION_ID = "X-Hermes-Session-Id"
class AIHttpPayloadKey(StrEnum):
MODEL = "model"
MESSAGES = "messages"
ROLE = "role"
CONTENT = "content"
STREAM = "stream"
TOOL = "tool"
ACTION = "action"
ARGS = "args"
SESSION_KEY = "sessionKey"
CHOICES = "choices"
MESSAGE = "message"
class AIChatRole(StrEnum):
SYSTEM = "system"
USER = "user"
class AIDefault(StrEnum):
ACTION_JSON = "json"
SESSION_KEY_MAIN = "main"
class AIRiskPreference(StrEnum):
BALANCED = "balanced"
class AIErrorKey(StrEnum):
OPENCLAW = "openclaw_error"
HERMES = "hermes_error"
DIRECT_LLM = "llm_error"
OPENCLAW_HERMES_PIPELINE = (
"hermes_recall -> openclaw_gateway -> hermes_answer -> hermes_remember"
)
COMPANY_MANAGEMENT_SYSTEM_INSTRUCTIONS = (
"You are a company management AI. Be concise, cite data from context, "
"and never approve payments, performance changes, or trades automatically."
)
CHAT_USER_CONTENT_TEMPLATE = "Context:\n{context}\n\nTask:\n{task}"
AUTHORIZATION_BEARER_TEMPLATE = "Bearer {token}"
NOOP_PROVIDER_ANSWER = (
"AI provider is not configured yet. This is a deterministic placeholder. "
"Set MODEL_PROVIDER to openclaw_hermes, openclaw, hermes, or direct_llm "
"after credentials are ready."
)
OPENCLAW_TOOL_COMPLETED_ANSWER = "OpenClaw tool invocation completed."
DIRECT_LLM_API_KEY_MISSING = "DIRECT_LLM_API_KEY is not configured"
UNEXPECTED_HERMES_RESPONSE = "Unexpected chat completion response"
AI_AUDIT_REDACTED_VALUE = "[REDACTED]"
AI_AUDIT_TRUNCATED_VALUE = "[TRUNCATED]"
AI_AUDIT_MAX_TEXT_LENGTH = 1000
AI_AUDIT_MAX_SEQUENCE_ITEMS = 20
AI_AUDIT_MAX_DEPTH = 4
AI_AUDIT_SENSITIVE_KEYS = frozenset(
{
"authorization",
"api_key",
"apikey",
"access_token",
"tenant_access_token",
"token",
"secret",
"password",
"openclaw_gateway_token",
"hermes_api_key",
"direct_llm_api_key",
}
)