dsh-jev-adapter

dsh-jev-adapter

English | 中文

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Use the Jev (System One) decision-model paradigm with any OpenAI-compatible LLM — no TypeSafe API key required. Registers a jev_decide tool on DeepSeek Harness (dsh).

Jev (TypeSafe AI) is a decision model: you send a state plus typed questions (choice / score / boolean), it returns calibrated, probability-distributed answers — no text generation. This plugin brings that paradigm to any chat model you already have, and can also talk to the real Jev API if you have a key.

Why

• zhangxaochen/dsh-jev (worth checking out) integrates the official TypeSafe API — great if you have a key and can reach api.typesafe.ai.
• This plugin covers everyone else: any OpenAI-compatible endpoint works — DeepSeek's own API, Ollama, vLLM, OpenRouter, SiliconFlow, LM Studio, or an air-gapped internal gateway.
• Probabilities on the openai channel are the model's self-reported estimates (not mathematically calibrated — every result carries this caveat). On the typesafe channel you get the real thing.

What you get

One tool, jev_decide, callable by the agent:

Question type	You provide	You get back
choice	options map (≤255)	picked option + full probability distribution + confidence
score	ordered levels (2–10)	fractional score + per-level probabilities + confidence
boolean	a statement	P(true)

Ask many questions in one call — 1 and 10 questions cost about the same.

Install

dsh plugin --profile <profile> add github:BetterZflyee/dsh-jev-adapter
# or, once published on npm:
dsh plugin --profile <profile> add dsh-jev-adapter

Then set one environment variable and restart dsh:

# openai channel (default) — point at any OpenAI-compatible endpoint
export JEV_OPENAI_API_KEY="sk-..."
# optional overrides:
# export JEV_BASE_URL="https://api.deepseek.com/v1"   # or Ollama/vLLM/OpenRouter/...
# export JEV_MODEL="deepseek-chat"

Or configure in cordis.patch.yml instead of env vars (see below).

Configure

All settings live in the plugin row in cordis.patch.yml:

- id: dsh-jev-adapter
  name: dsh-jev-adapter
  config:
    channel: openai          # "openai" (default) | "typesafe"
    # ---- openai channel ----
    # baseURL: https://api.deepseek.com/v1     # any OpenAI-compatible endpoint
    # apiKey: sk-...                            # or env JEV_OPENAI_API_KEY / OPENAI_API_KEY
    # model: deepseek-chat
    # ---- typesafe channel (real Jev) ----
    # channel: typesafe
    # apiKey: ...                              # or env JEV_TYPESAFE_API_KEY / TYPESAFE_API_KEY
    # model: jev-latest
    # ---- shared ----
    # maxTokens: 4000
    # timeoutMs: 120000
    # retries: 3

Use

Just talk to your agent — it decides when to call the tool:

Classify these 12 support tickets: department + urgency + customer frustration.

The agent sends all judgements as typed questions in one jev_decide call and gets back a table of probabilities.

Routing on confidence (the whole point of the paradigm):

confidence ≥ 0.85  → act automatically
0.5 – 0.85         → draft, ask a human to confirm
< 0.5              → escalate to a human

Tune thresholds to the risk of the action, and remember the caveat: on the openai channel these are self-reported probabilities, not calibrated ones.

Details worth knowing

• Honesty prompt. The adapter explicitly instructs the model to spread probability when uncertain instead of forcing a fake 1.0 — without this, confidence saturates and the routing signal is lost (validated on real Chinese-language work items; see the prompt in lib/adapter.js).
• Thinking models. Models that leave content empty and answer in reasoning_content are handled.
• Normalisation. Probabilities that don't sum to 1 are renormalised; an all-zero answer degrades to uniform rather than failing.
• Retries. 429/5xx retried with exponential backoff (default 3 attempts).

Relation to other Jev plugins

	zhangxaochen/dsh-jev	this plugin
Real TypeSafe Jev	✅	✅ (typesafe channel)
Any OpenAI-compatible LLM	❌	✅ (default)
Tool pruning / loop guard / safety gate	✅	❌ (different scope)

They are complementary: pick his for the guard suite with a real Jev key, this one for the decision paradigm on any model.

License

MIT

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dsh-jev-adapter（中文）

把 Jev（System One）决策模型范式套在任何 OpenAI 兼容的 LLM 上——不需要 TypeSafe API key。在 DeepSeek Harness (dsh) 上注册一个 jev_decide 工具。

Jev（TypeSafe AI）是决策模型：发一段状态加一组类型化问题（choice / score / boolean），返回带概率分布的结构化答案——不生成文字。本插件把这个范式带到你已有的任意聊天模型上；如果你有 key，也可以直连真 Jev。

为什么做这个

• zhangxaochen/dsh-jev（推荐一看）对接的是 官方 TypeSafe API——有 key 且能访问 api.typesafe.ai 时很好。
• 本插件覆盖其他人：任何 OpenAI 兼容端点都能跑——DeepSeek 官方 API、Ollama、vLLM、OpenRouter、硅基流动、LM Studio、或内网网关。
• openai 通道的概率是模型自述的估计值（非数学校准，每个结果都带此提示）；typesafe 通道给你真货。

你得到什么

一个工具 jev_decide，Agent 可直接调用：

问题类型	你提供	返回
choice	选项映射（≤255 项）	选中的选项 + 完整概率分布 + 置信度
score	有序等级（2–10 级）	分数 + 各等级概率 + 置信度
boolean	一个陈述	P(为真)

一次调用可以并行问多个问题——问 1 个和问 10 个代价几乎一样。

安装

dsh plugin --profile <profile> add github:BetterZflyee/dsh-jev-adapter
# npm 发布后也可以：
dsh plugin --profile <profile> add dsh-jev-adapter

设一个环境变量后重启 dsh：

# openai 通道（默认）—— 指向任意 OpenAI 兼容端点
export JEV_OPENAI_API_KEY="sk-..."
# 可选覆盖：
# export JEV_BASE_URL="https://api.deepseek.com/v1"   # 或 Ollama/vLLM/OpenRouter/...
# export JEV_MODEL="deepseek-chat"

也可以在 cordis.patch.yml 里配置（见英文节的 Configure）。

使用

直接跟 Agent 说话，它自己决定何时调用：

把这 12 条工单分类：部门 + 紧急度 + 客户情绪

Agent 会把所有判断作为类型化问题放进一次 jev_decide 调用，拿到一张概率表。

按置信度路由（这套范式的意义所在）：

confidence ≥ 0.85  → 自动执行
0.5 – 0.85         → 生成草稿，请人确认
< 0.5              → 转人工

阈值按操作风险调；记住提示：openai 通道的概率是自述值，不是校准值。

值得知道的细节

• 诚实性提示词。适配器明确要求模型不确定时如实分散概率、不要硬给 1.0——没有这条，置信度会饱和，路由信号失效（在真实中文工作事项上验证过，见 lib/adapter.js）。
• 思考模型兼容。content 为空、答案在 reasoning_content 的模型已处理。
• 归一化。概率之和不为 1 时重新归一化；全零答案退化为均匀分布而不是报错。
• 重试。429/5xx 指数退避重试（默认 3 次）。

与其他 Jev 插件的关系

	zhangxaochen/dsh-jev	本插件
真 TypeSafe Jev	✅	✅（typesafe 通道）
任意 OpenAI 兼容 LLM	❌	✅（默认）
工具剪枝 / 死循环阻断 / 安全门禁	✅	❌（定位不同）

互补关系：要护栏套件 + 真 Jev 用他的；要在任意模型上用决策范式用本插件。

许可证

MIT