dsh-image-generation (tool-image-generation)

1. 安装并启动 DeepSeek Harness：npx @deepseek-ai/dsh web
2. 在终端执行上面的安装命令（CLI 会解析插件并核验来源）
3. 用 dsh plugins list 确认已安装，必要时重启 Harness 生效

插件以当前 dsh 进程的权限运行，安装时可能执行代码。请先通读仓库源码与许可证，确认无破坏性命令与越权访问；本站只做索引，不对第三方插件安全性作担保。

事实信息来自公开插件目录快照（2026-10-01），介绍文案由本站再加工。

以下为插件仓库 README 全文（原始内容，由公开目录抓取整理）。

# dsh-image-generation

English | [中文](README.zh.md)

Give your DeepSeek Harness agent a **paintbrush**. `dsh-image-generation` is an image-generation plugin for [DeepSeek Harness](https://github.com/deepseek-ai/deepseek-harness): the agent describes an image in text, a settings-selected generation channel produces it through a **pluggable backend**, and the file paths are written to disk — all outside the model, so **no image-capable model is required**.

## Compatibility

This revision requires DeepSeek Harness core `0.1.2-alpha.5` or later within the `0.1.x` line. It uses the Settings service API introduced in that core release.

## Why you want it

- **DeepSeek can't draw — now it can.** The harness model has no image output. This plugin runs the whole "create" outside the model and returns real file paths the agent can hand over (or verify).
- **Multi-channel by design.** The `generate_image` tool is decoupled from generation backends. The `gpt-image-2` channel ships ready to use; adding Gemini, FLUX, or a local model is **one `generate()` implementation + one registry line** — the tool schema never changes.
- **Normalized parameters.** `count`, `aspect_ratio`, and `quality` are standardized across every channel; channel-specific knobs stay in the per-channel defaults of the settings section.
- **Generated, then verified.** Images are decoded to disk under `generated/` and returned as paths; pair with `analyze_image` (the [dsh-client-vision](https://github.com/ankye/dsh-client-vision) plugin) for generate-then-inspect workflows.
- **Secret-safe.** The API key lives in the harness `credentials` store (`GENERATION_OPENAI_API_KEY`) — never in settings files, logs, or the conversation transcript.
- **Every preset, out of the box.** Mounted on the host plane, so `code`, `standard`, `cordis`, `minimal` — every agent can generate.
- **Sensible defaults.** Default aspect ratio, quality, count, and output directory are configurable; the tool respects per-call overrides.
- **Ready to ship.** Prebuilt bundles included; three install paths (drop into the monorepo / `pnpm publish` / tarball).

## Capabilities

### Tool

| Tool | What it does |
|---|---|
| `generate_image` | Generate 1–10 images from a text prompt through the configured channel. Parameters: `prompt` (required), `count`, `aspect_ratio` (`1:1`…`2:3`), `quality` (`low`/`medium`/`high`/`auto`), `output_dir`. Returns the written file paths + MIME types. |

### Settings (`generation` namespace)

Configured in **Settings → Plugins → Plugin configuration → Image Generation**:

| Field | Meaning |
|---|---|
| Endpoint (`baseUrl`) | Domain + optional path prefix; `/images/generations` is appended. e.g. `https://api.example.com/v1` |
| Channel | The active generation backend (currently `gpt-image-2`). |
| Model | `gpt-image-2` |
| Output directory | Where images are written; empty uses `/generated`. |
| Default aspect ratio / quality / count | Used when the tool passes no per-call value. |
| API key | Stored through the harness `credentials` service as `GENERATION_OPENAI_API_KEY`; the literal never leaves your machine. |

### Multi-channel architecture

```
model → generate_image(prompt, count?, aspect_ratio?, quality?)
          │  reads generation.channel
          ▼
  channels//generate()        ← one implementation per backend
          │
  gpt-image-2:  POST {baseUrl}/images/generations   (b64_json / url)
  gemini / flux / local: …       ← add yours here
          │
          ▼
  output.ts → decode + write to disk → {path, mime}[]
```

Adding a channel is deliberately small:

```ts
// src/channels//index.ts
export async function myGenerate(ctx, call): Promise {
  // call.prompt, call.count, call.aspectRatio, call.quality, call.config, call.signal
  return await fetchYourGenerationApi(...)
}
```

```ts
// src/channels/index.ts — one registry line
export const channels = {
  'gpt-image-2': { label: 'GPT Image', generate: gptImageGenerate, maxCount: 10, ... },
  myChannel: { label: 'My Channel', generate: myGenerate },
}
```

The `generate_image` tool and its schema never change.

## Installation (official — no repo modification)

`dsh plugin add` installs the packages into your profile; each package declares `dsh.bundle`, so the rows mount automatically — no patch rows, no repo edits.

### Prerequisites

- DeepSeek Harness core `0.1.2-alpha.5` or later within the `0.1.x` line, plus `dsh` and `pnpm` on PATH.

### 1. Get the packages (pick one)

**a. From this repository (recommended until published to npm):**

```sh
dsh plugin --profile web add \
  file:/path/to/dsh-image-generation/packages/tool-image-generation \
  file:/path/to/dsh-image-generation/packages/ui-image-generation
```

**b. Tarball:**

```sh
cd packages/tool-image-generation && npm pack
cd packages/ui-image-generation   && npm pack
dsh plugin --profile web add file:/path/to/deepseek-ai-dsh-tool-image-generation-0.1.0-rc.7.tgz \
                            file:/path/to/deepseek-ai-dsh-client-ui-image-generation-0.1.0-rc.7.tgz
```

**c. npm registry (after publishing):**

```sh
dsh plugin --profile web add @deepseek-ai/dsh-tool-image-generation @deepseek-ai/dsh-client-ui-image-generation
```

> A `[WARN] Issues with peer dependencies` message is expected and safe to ignore — the peers come from your deployment's own bundles at runtime.

### 2. Verify

```sh
node -e "console.log(JSON.stringify(require(process.env.HOME + '/.dsh/profiles/web/package.json').dsh.profile.bundles))"
# should list dsh-tool-image-generation and dsh-client-ui-image-generation
```

### 3. Restart + configure

Restart the harness, then **Settings → Plugins → Plugin configuration → Image Generation**: set the endpoint, model, defaults, output directory, and your own API key (`GENERATION_OPENAI_API_KEY`), save.

### 4. Verify

Ask the agent to "generate an image of a …" — it should call `generate_image` and return written file paths under `generated/`.

### Uninstall

```sh
dsh plugin --profile web remove @deepseek-ai/dsh-tool-image-generation @deepseek-ai/dsh-client-ui-image-generation
```

## Alternative: build inside a harness fork

If you run a **fork** of deepseek-harness (not the official deployment), you can drop the packages into the monorepo instead:

```sh
cp -R packages/tool-image-generation /packages/vision/tool-image-generation
cp -R packages/ui-image-generation   /packages/client/ui-image-generation
```

Then add both to `apps/cli/package.json` (`workspace:^`), add `./packages/vision/tool-image-generation` to `tsconfig.host.json` and `./packages/client/ui-image-generation` to `tsconfig.client.json`, `pnpm install`, build (`tsdown` host + client passes), and restart.

## Parameters

| Parameter | Meaning | Default |
|---|---|---|
| `prompt` | Text describing the image to generate (required). | — |
| `count` | How many images to generate (1–10). | `1` |
| `aspect_ratio` | `1:1` / `4:3` / `3:4` / `16:9` / `9:16` / `3:2` / `2:3` — mapped to OpenAI pixel sizes. | `1:1` |
| `quality` | `low` / `medium` / `high` / `auto`. | `auto` |
| `output_dir` | Directory for the written files; relative paths resolve against the session workspace. | `generated/` |

Unsupported aspect ratios, qualities, or out-of-range counts fail loudly with a
message naming the supported values — the tool never silently substitutes.

## Quick start

1. Restart the harness.
2. The tool catalog now includes `generate_image`.
3. Open **Settings → Plugins → Plugin configuration → Image Generation**, set the endpoint, model, and your own API key, and save.
4. Ask the agent to "generate an image of a …" — it returns the written file paths.

## Development

- This repository is a **source distribution**: the peer packages (`@deepseek-ai/dsh-tools`, …) resolve from your deployment. `lib/` ships prebuilt, so `npm pack` works immediately.
- The `tsconfig.json` files are standalone; the harness monorepo's build pipeline (including the client-bundle `tsdown.config.ts`) applies in Option A.
- **Never commit secrets.** The API key stays in each machine's `.credentials.yaml`.

## License

MIT