推測性扇出

在一次呼叫裡傳送許多問題（包括推測性的），由你的程式碼決定哪些真正相關。

因為 TypeSafe 支援在單次 API 呼叫裡傳送多個問題，我們建議把系統需要的所有問題都放進同一個請求，事後再用程式碼決定哪些相關。所有問題都是並行求值的，所以多問幾個通常對響應時間沒什麼影響。

示例：支援工單分流

設想你在做一個支援系統，需要給支援工單分流。你要先把工單歸到一個類別。如果是 bug 報告，還要判斷 bug 的嚴重程度。

與其先問類別、再發一次呼叫問嚴重程度，你可以在同一次裡把兩個都問出來。如果工單不是 bug 報告，直接忽略 bug 嚴重程度那個問題的結果就行。

%%{init: {"fontFamily": "Inter, sans-serif", "flowchart": {"rankSpacing": 35, "wrappingWidth": 300, "subGraphTitleMargin": {"top": 8, "bottom": 60}}}}%%
flowchart LR
    t["support ticket"]

    subgraph req["TypeSafe AI model<br/>evaluates each question<br/>against the ticket in parallel"]
        direction TB
        c["<b>Choice:</b> category"]
        b["<b>Score:</b> bug severity"]
        r["<b>Noul:</b> reproducible steps?"]
        f["<b>Noul:</b> refund requested?"]
        s["<b>Score:</b> frustration"]
        %% invisible links: without an edge these share a rank and sit side by side
        c ~~~ b ~~~ r ~~~ f ~~~ s
    end

    t -- "one request<br/>ticket + 5 questions" --> req
    req -- "one response: 5 answers<br/>decisions + probabilities" --> route{"<b>filter, combine, and route</b><br/>in your code"}
    route -- "bug_report" --> eng["read severity + repro steps<br/>escalate or backlog"]
    route -- "billing" --> bill["refund requested<br/>send to billing"]
    route -- "feature_request" --> feat["log it<br/>sent to devs"]

第 1 步：推測性扇出

{
  "category": {
    "type": "choice",
    "instructions": "Determine the broad category of this support ticket",
    "criteria": {
      "bug_report": "The user is reporting something that is broken or producing errors",
      "billing": "Charges, invoices, refunds, subscriptions",
      "feature_request": "The user is requesting new functionality",
      "account": "Login, permissions, profile, security"
    }
  },
  "bug_severity": {
    "type": "score",
    "instructions": "How severe is the reported issue",
    "criteria": [
      "Cosmetic; no impact to functionality",
      "Broken or degraded feature; workaround exists",
      "Blocking issue; no workaround exists"
    ]
  },
  "has_reproducible_steps": {
    "type": "noul",
    "instructions": "The user describes specific steps to reproduce the issue"
  },
  "refund_requested": {
    "type": "noul",
    "instructions": "The user is explicitly asking for a refund or credit"
  },
  "frustration": {
    "type": "score",
    "instructions": "How frustrated the user appears",
    "criteria": [
      "Calm, matter-of-fact",
      "Frustrated but civil",
      "Very angry"
    ]
  }
}

第 2 步：用程式碼路由

你的程式碼根據分類結果決定哪些相關：

triage.py

category = response.answers["category"]
bug_severity = response.answers["bug_severity"]
bug_repro = response.answers["has_reproducible_steps"]
refund = response.answers["refund_requested"]
frustration = response.answers["frustration"]

if category.choice == "bug_report":
    if bug_severity.score > 1.5 and bug_repro.noul > 0.6:
        escalate_to_engineering(ticket_id, severity="high")
    else:
        add_to_bug_backlog(ticket_id)

elif category.choice == "billing":
    if refund.noul > 0.7:
        route_to_billing_with_flag(ticket_id, refund_likely=True)
    else:
        route_to_billing(ticket_id)

elif category.choice == "feature_request":
    log_feature_request(ticket_id)

# Frustration is useful regardless of category
if frustration.score > 1.5:
    flag_for_priority_response(ticket_id)

整棵決策樹所需的一切都來自一次呼叫。推測性問題在不相關時被忽略，在相關時則省下了一次往返。