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在 Deep Agents 中实现人工审批工作流,使用 interruptOn 参数对敏感工具操作进行人工干预。
Passed 21 of 22 test cases with the skill, and 9 of 22 without it.
and 14 more in the full report
12 fixed9 passed either way1 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 12 test cases the skill fixed. Same model, same prompt, with and without the skill.
Write the configuration object for createDeepAgent where write_file allows full edit/approve/reject (boolean true), deploy allows only approve/reject, and search_db is completely unblocked.
| Checked | Without skill | With skill |
|---|---|---|
| Sets write_file to true and search_db to false in interruptOn. | Missed | Passed |
| Sets deploy to an object with allowedDecisions array containing approve and reject in interruptOn. | Missed | Passed |
The instructions your model reads when the skill loads.
HITL 中间件为工具调用添加人工监督。执行暂停以等待人工决策:批准、编辑或拒绝。
需要 checkpointer 在中断期间保存状态。
import { createDeepAgent } from "deepagents";
import { MemorySaver } from "@langchain/langgraph";
const agent = await createDeepAgent({
interruptOn: {
write_file: true, // 允许所有决策
execute_sql: { allowedDecisions: ["approve", "reject"] }, // 不允许编辑
read_file: false, // 无中断
},
checkpointer: new MemorySaver() // 必需
});
| 工具类型 | 配置 | 决策 | 使用场景 |
|---|---|---|---|
| 破坏性 | true | 批准/编辑/拒绝 | write_file、delete |
| 关键 | {allowedDecisions: [...]} | 仅批准/拒绝 | deploy、SQL |
| 安全 | false | 无 | read_file |
import { createDeepAgent } from "deepagents";
import { MemorySaver } from "@langchain/langgraph";
import { Command } from "@langchain/langgraph";
test cases passed, vs 9 / 22 without
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