# DSH Reasoning Settings

A [DeepSeek Harness](https://github.com/deepseek-ai/deepseek-harness) Web settings plugin that adds an independent **reasoning effort** (thinking intensity) page for custom `llm-pi-ai` providers. The official UI only exposes effort selection for first-party DeepSeek models; this plugin makes it work for third-party / relay APIs too.

[中文说明](./README.zh-CN.md)

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## Features

- Auto-reads the custom providers and models you already added on the official **Models** page.
- Declares a per-model effort level from `off / minimal / low / medium / high / xhigh / max`.
- Customizes the actual wire value sent to the API for each level.
- Sets a provider-wide default effort, restricted to the levels supported by every model in that provider.
- Configures the reasoning wire format for `openai-completions` providers.
- Writes back to `llm-pi-ai.providers.*` through the official `settings.mutate` API — API keys are never touched.
- Fixes in-process subagents inheriting the Agent's create-time official model instead of the parent's live third-party provider/model selection.
- Makes subagents inherit an explicit parent reasoning effort, or fall back to the target provider's configured default effort.
- Resolves model-only child overrides such as `grok-4.5` against user-configured third-party providers instead of an unrelated official provider.
- Extends the ordinary `subagent` and `subagent_fork` tools with per-call `provider`, `model`, and `reasoning_effort` fields, without replacing their official lifecycle, background, or result behavior.

## Live demo

![Reasoning effort settings page](./assets/reasoning-settings-page.png)

![Model and reasoning effort picker](./assets/model-effort-picker.png)

## Installation

### Prerequisites

- Install [Node.js](https://nodejs.org/). DSH currently supports Node.js 22.19.x or version 24 and newer; Node.js 24 LTS is recommended. Node.js includes `npm` and `npx`.
- Install [Git](https://git-scm.com/) so the plugin can be fetched from its GitHub repository.
- Install pnpm. Both methods require pnpm because `dsh plugin` invokes it in the profile directory to install or remove plugins.
- Your network must reach `registry.npmjs.org` and `github.com`. Configure a working network proxy if npm or GitHub is unavailable or unstable in your region.
- Method 1 does not require a DeepSeek Harness source checkout. Method 2 additionally requires that checkout.

Check the basic environment first:

```powershell
node --version
npx --version
git --version
corepack enable
pnpm --version
```

If `corepack enable` fails with a permission error, run it once from an Administrator PowerShell. Alternatively, use another option from the [pnpm installation guide](https://pnpm.io/installation).

If downloads remain on a spinner or fail with `ECONNRESET`, `ETIMEDOUT`, or a GitHub connection error, set a proxy for the current PowerShell window. Port `7890` is only an example; replace it with your proxy's actual port:

```powershell
$proxy = "http://127.0.0.1:7890"
$env:HTTP_PROXY = $proxy
$env:HTTPS_PROXY = $proxy
$env:npm_config_proxy = $proxy
$env:npm_config_https_proxy = $proxy
```

These variables only affect the current PowerShell window and disappear when it is closed.

### Method 1: npx (recommended for regular users)

This method does not require a DeepSeek Harness source checkout or a global `dsh` installation, but Git and pnpm must already be available. On its first run, `npx` downloads `@deepseek-ai/dsh` and its dependencies, which can take several minutes:

```powershell
npx --yes -p @deepseek-ai/dsh dsh plugin --profile web add github:JuneLearn/dsh-reasoning-settings
```

Start Web through the same package runner after installation:

```powershell
npx --yes -p @deepseek-ai/dsh dsh web
```

### Method 2: pnpm with the Harness source tree (recommended for developers)

Use this method if you already cloned `deepseek-harness` and want to run its source directly. First confirm pnpm is available:

```powershell
pnpm --version
```

Enter the DeepSeek Harness source root. Install its dependencies once, then install the plugin:

```powershell
cd D:\deepseek-harness
pnpm install
pnpm dsh plugin --profile web add github:JuneLearn/dsh-reasoning-settings
```

Start Web from that source directory afterward:

```powershell
cd D:\deepseek-harness
pnpm dsh web
```

The package's `dsh.bundle` declaration adds the plugin to the Web profile automatically. Neither method requires editing `cordis.patch.yml`. Web listens on `http://127.0.0.1:3080` by default; it uses another port only when the default is occupied or you explicitly select one.

### Upgrade

Run the corresponding install command again to upgrade. No uninstall or profile-patch maintenance is required.

npx method:

```powershell
npx --yes -p @deepseek-ai/dsh dsh plugin --profile web add github:JuneLearn/dsh-reasoning-settings
```

pnpm source method:

```powershell
cd D:\deepseek-harness
pnpm dsh plugin --profile web add github:JuneLearn/dsh-reasoning-settings
```

### Uninstall

npx method:

```powershell
npx --yes -p @deepseek-ai/dsh dsh plugin --profile web remove dsh-reasoning-settings
```

pnpm source method:

```powershell
cd D:\deepseek-harness
pnpm dsh plugin --profile web remove dsh-reasoning-settings
```

DSH removes both the dependency and its bundle layer. Restart `dsh web`; the **Reasoning effort** settings page is removed.

## Usage

1. Add your custom provider and models on the official **Models** page first.
2. Open **Settings > Reasoning effort**.
3. Pick the supported levels for each model and set the provider default effort.
4. Click **Save** under that provider.
5. Start a new session and choose the model and reasoning effort in the model picker.

The plugin only declares which effort levels Harness may select and send. Whether the relay API actually honors a value is up to the relay: if a request comes back with HTTP 400, uncheck the levels that model does not support or adjust their wire values.

## Subagent routing and reasoning

The server entry fixes model inheritance for Harness `0.1.0-rc.5` in-process `subagent`, `subagent_fork`, and Workflow children:

1. An explicit child `provider + model` route remains authoritative when it differs from the parent's create-time route.
2. A model-only override is resolved against user-configured third-party providers; duplicate model ids prefer the parent's current provider.
3. With no child override, the child inherits the parent's live provider/model instead of its create-time official default.
4. An explicit child effort remains authoritative; otherwise the parent's effort is inherited only for the same target route.
5. With no explicit effort, the plugin leaves it absent so `llm-pi-ai` applies the target provider's `reasoning` default.

The plugin also augments the existing model-facing `subagent` and `subagent_fork` tools for each live Agent. Their original arguments remain available, with three optional fields added:

- `provider`: exact configured Provider id;
- `model`: exact model id owned by that Provider;
- `reasoning_effort`: optional `off / minimal / low / medium / high / xhigh / max` level.

`provider` and `model` must be supplied together. Omitting both preserves normal inheritance. Omitting `reasoning_effort` after selecting a different route uses that Provider/model's configured default. The tool descriptions enumerate exact configured pairs and instruct the parent model to delegate instead of answering directly when a user requests another Provider/model.

Do not use shorthand such as “the 5.6 model” when multiple exact ids exist. For example, if a Provider contains both `gpt-5.6-sol` and `gpt-5.6-terra`, ask for one exact pair:

```text
Use subagent with provider=wpironman-gpt, model=gpt-5.6-terra,
reasoning_effort=max to write a 100-character random essay.
```

If the requested pair equals the current route, the child still uses that same route, so the result will naturally look like the parent model. The structured tool-call arguments and the child's durable `request/header` are the reliable verification points.

Per-call targeting affects local in-process children only. Codex, Claude Code, and ACP subagents run in separate processes and retain their own model configuration. Workflow retains its own structured `provider`/`model` phase fields and still benefits from the inheritance correction when no phase target is supplied.

All switches default to `true` and may be changed in the plugin mount:

```yaml
- insert:
    - id: ui-settings-reasoning
      name: dsh-reasoning-settings
      config:
        subagentRouting: true
        inheritRoute: true
        resolveModelOnly: true
        inheritReasoning: true
```

Set `subagentRouting: false` to disable the entire server-side correction.

## Development

```powershell
pnpm test   # or: node tests/plugin.test.mjs
```

## Compatibility

Built against the public dual-end plugin, settings-slot, `settings.mutate`, agent-scoped tool shadowing, Agent lifecycle, and `agent/request` waterfall interfaces of DeepSeek Harness `0.1.0-rc.5`. Harness is still in Developer Preview; if the plugin stops loading or subagent routing changes after an upgrade, check those interfaces and the subagent session metadata.

## License

[MIT](./LICENSE)