置信度門控路由

把置信度當作第二條軸。答案告訴你該做什麼；置信度告訴你該不該做。

TypeSafe 最強大的特性之一，是置信度。只要你有意識地把決策門控在置信度上，就能構建出既可靠又安全的系統。

示例：語音銀行指令

設想你要做一個語音銀行介面，讓使用者能口頭操作自己的賬戶。解讀使用者意圖時，你當然希望始終有說得過去的置信度，但有些操作比另一些風險更高，因而需要更高的置信度閾值。

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flowchart LR
    command["voice banking command"]

    subgraph req["TypeSafe evaluates<br/>the question"]
        intent["<b>Choice:</b> intent"]
    end

    command -- "one request<br/>command + intent<br/>question" --> req
    req -- "one response<br/>intent answer +<br/>confidence" --> gate{"<b>confidence high enough?</b><br/>your code"}
    gate -- "below 0.6<br/>or other intent" --> human["send to a support agent"]
    gate -- "check_balance<br/>at least 0.6" --> balance["show the balance"]
    gate -- "approve_transfer<br/>0.6 to 0.85" --> confirm["ask the user to confirm"]
    gate -- "approve_transfer<br/>above 0.85" --> approve["approve the transfer"]

第 1 步：判斷使用者意圖

{
  "intent": {
    "type": "choice",
    "instructions": "What action is the user requesting?",
    "criteria": {
      "check_balance": "Check the balance of an account",
      "approve_transfer": "Approve the pending transfer request",
      "other": "Something else"
    }
  }
}

第 2 步：置信度門控路由

action = response.answers["intent"]

# Below 0.6 confidence on any action, route to a human
if action.confidence < 0.6:
    route_to_support_agent(account_id)

elif action.choice == "check_balance":
    # Low stakes. 0.6 confidence is sufficient.
    show_balance(account_id)

elif action.choice == "approve_transfer":
    if action.confidence > 0.85:
        # High stakes, but high confidence. Safe to act automatically.
        approve_transfer(account_id)
    else:
        # High stakes, moderate confidence. Verify intent first.
        ask_user_to_confirm("Just to confirm: you would like to approve this transfer, is that correct?")

else:
    route_to_support_agent(account_id)

0.6 這條底線，兜住的是模型確實拿不準的部分。底線之上，每種操作各自有閾值，取決於分類錯了還要照做會有什麼後果。以 0.6 的置信度去查餘額沒問題，因為最壞的情況不過是使用者聽一遍餘額播報。但批准一筆轉賬需要很高的置信度（>0.85），否則系統就該請使用者先確認一下。

想更詳細地瞭解在系統裡該如何看待置信度，見置信度。