@amaster.ai/pi-image-gen

pi-image-gen preview

Pi extension that adds an image_generate tool. Supported providers:

Provider	Model id (alias)	Env var
OpenAI	`gpt-image-2`	`OPENAI_API_KEY`
Google Gemini ("Nano Banana")	`gemini-3-pro-image` (alias `nano-banana-pro`), `gemini-3.1-flash-image` (alias `nano-banana-2`), `gemini-3.1-flash-lite-image` (alias `nano-banana-2-lite`), `gemini-2.5-flash-image` (alias `nano-banana`)	`GEMINI_API_KEY`
Alibaba DashScope (Qwen-Image)	`qwen-image-3.0-pro`, `qwen-image-3.0`, `qwen-image-2.0-pro`, `qwen-image-2.0`	`DASHSCOPE_API_KEY`
Volcengine Ark (ByteDance Seedream)	`doubao-seedream-5-0-pro-260628` (alias `seedream-5-pro`, retired id `doubao-seedream-5-0-pro-260128` still resolves), `doubao-seedream-5-0-260128` (aliases `seedream-5`, `seedream`; the same model also answers to `doubao-seedream-5-0-lite-260128` / `seedream-5-lite`), `doubao-seedream-4-5-251128` (alias `seedream-4-5`), `doubao-seedream-4-0-250828` (alias `seedream-4`)	`ARK_API_KEY`
OpenRouter	any (use `openrouter/<vendor>/<id>`)	`OPENROUTER_API_KEY`
Custom providers	whatever you declare in settings	(your choice, via `$VAR`)

Upstream API docs (handy when debugging gateway behavior or adding new models):

OpenAI gpt-image-2 — developers.openai.com/api/docs/models/gpt-image-2
Google Gemini image generation — ai.google.dev/gemini-api/docs/image-generation
Alibaba Qwen-Image 3.0 (generation & editing) — help.aliyun.com/zh/model-studio/qwen-image-generation-and-editing-api-reference
Alibaba DashScope Qwen-Image 2.0 (text-to-image) — help.aliyun.com/zh/model-studio/qwen-image-api
Alibaba DashScope Qwen-Image-Edit — help.aliyun.com/zh/model-studio/qwen-image-edit-api
Volcengine Ark Seedream — volcengine.com/docs/82379/1824121
OpenRouter image API — openrouter.ai/docs/api/api-reference/images/create-images

The env-var names match pi.dev's provider table — if the agent already has a key set for a provider, this extension will reuse it. You don't need to introduce a new variable.

The active model is fixed in settings.json. The image_generate tool intentionally does not take a model parameter — point your project at one model, get consistent output. To switch models, edit settings and run /image-gen reload.

Install

pnpm add @amaster.ai/pi-image-gen

The package's pi.extensions field auto-registers it with the host pi-coding-agent runtime; no extra wiring needed.

Configure

Settings are read by pi-shared's loadPiSettings, which merges three files (low-to-high priority):

~/.pi/agent/settings.json (global)
$PI_AGENT_HOME/settings.json (agent dir, if PI_AGENT_HOME is set)
<cwd>/.pi/settings.json (trusted project)

Project settings are ignored when project trust is declined. ${ENV_VAR} interpolation is supported in global and agent settings only, so keep environment-backed credentials out of project settings.

All settings live under the pi-image-gen key. The minimum viable config sets defaultModel:

{
  "pi-image-gen": {
    "defaultModel": "nano-banana"
  }
}

…and exports the matching env var:

export GEMINI_API_KEY=sk-...

That's it. From the agent: image_generate({ prompt: "a cyberpunk cat" }).

All settings fields

{
  "pi-image-gen": {
    "defaultModel": "nano-banana",
    "outputDir": ".pi/images",

    "providers": {
      "openai":     { "baseUrl": "https://my-proxy.example.com/v1", "apiKey": "${MY_OPENAI_KEY}" },
      "gemini":     { "headers": { "x-goog-trace": "pi-prod" } },
      "dashscope":  { "baseUrl": "https://dashscope-intl.aliyuncs.com/api/v1" },
      "ark":        { "apiKey": "$ARK_API_KEY" },
      "openrouter": { "apiKey": "$OPENROUTER_API_KEY" }
    },

    "customProviders": {
      "my-stable-diffusion": {
        "api": "openai",
        "baseUrl": "https://api.my-sd.example.com/v1",
        "apiKey": "${MY_SD_KEY}",
        "headers": { "x-tenant": "team-a" },
        "models": [
          { "id": "sd-3-large", "alias": "sd3" },
          "sd-3-medium"
        ]
      }
    }
  }
}

Field	Purpose
`defaultModel`	Model id or alias the tool will use. Required.
`outputDir`	Where to write generated images. Relative paths resolve against the session cwd. Default `.pi/images`.
`providers`	Per-built-in-provider override. Set `apiKey`, `baseUrl`, or `headers` to point at a proxy or non-standard env var.
`customProviders`	User-defined providers — see below.

In global and agent settings, apiKey, baseUrl, and headers values support $VAR and ${VAR} environment interpolation. Fallbacks require the braced form (for example, ${FOO:-default}); $FOO:-default is not supported. Project settings keep all of these placeholders literal.

Built-in setup walkthrough

1. OpenAI (`gpt-image-2`)

export OPENAI_API_KEY=sk-...

{ "pi-image-gen": { "defaultModel": "gpt-image-2" } }

2. Google Gemini "Nano Banana"

export GEMINI_API_KEY=...

{ "pi-image-gen": { "defaultModel": "nano-banana" } }

3. Alibaba DashScope (Qwen-Image)

export DASHSCOPE_API_KEY=...

{ "pi-image-gen": { "defaultModel": "qwen-image-2.0" } }

For the international DashScope endpoint, override the base URL:

{
  "pi-image-gen": {
    "defaultModel": "qwen-image-2.0",
    "providers": {
      "dashscope": { "baseUrl": "https://dashscope-intl.aliyuncs.com/api/v1" }
    }
  }
}

4. Volcengine Ark (ByteDance Seedream)

export ARK_API_KEY=...

{ "pi-image-gen": { "defaultModel": "seedream" } }

Supported size values are model-dependent, and the tool schema tells the agent the exact form for the active model: a tier token (1K/1.5K/2K/3K/4K — the list differs per model) or an explicit "<w>x<h>" pixel string, never mixed. Seedream 5.0 / 4.5 enforce a 2K pixel floor (1024x1024 fails with InvalidParameter); 5.0 pro accepts 1K/1.5K/2K down to 921,600 px; 4.0 accepts 1K. Full sizing matrix in the official docs. Seedream has no n parameter — the API generates one image per request (multi-image is the sequential_image_generation mechanism, not exposed here), so n is hidden for these models.

The default base URL is https://ark.cn-beijing.volces.com/api/v3. To use a different region (e.g. ap-southeast), override it:

{
  "pi-image-gen": {
    "defaultModel": "seedream",
    "providers": {
      "ark": { "baseUrl": "https://ark.ap-southeast.bytepluses.com/api/v3" }
    }
  }
}

5. OpenRouter (one key, many models)

export OPENROUTER_API_KEY=...

{ "pi-image-gen": { "defaultModel": "openrouter/bytedance-seed/seedream-4.5" } }

The string after openrouter/ is the OpenRouter model slug; pass any image model OpenRouter supports (google/gemini-3.1-flash-image, openai/gpt-image-2, bytedance-seed/seedream-4.5, …).

OpenRouter's image API is not OpenAI-compatible despite the family name — it lives at POST /api/v1/images (no /generations suffix) and uses JSON input_references for image-to-image. The extension targets the right endpoint automatically; no wire-shape config needed.

Custom providers

Use customProviders for anything not built in: a self-hosted Stable Diffusion, an internal corp gateway, a third-party image API. The shape mirrors pi.dev's custom-provider docs.

Each custom provider declares:

Field	Required	Notes
`api`	yes	One of `openai`, `gemini`, `dashscope`, `openrouter`, `ark`. Picks the image-API wire shape.
`baseUrl`	yes	API endpoint URL. `$VAR` syntax supported.
`apiKey`	usually	API key string. `$VAR` syntax supported.
`name`	no	Display name shown in `/image-gen list`.
`headers`	no	Extra headers merged into every request.
`models`	no	Optional model id/alias list. Omit to make this a catch-all — the provider will accept any unknown model id (passed through as the remote id). Provide a list only when you want aliases or want to route specific ids elsewhere. Each entry is a string or `{ id, alias?, name?, capabilities? }`.

A custom model whose id names a built-in model inherits that model's capability contract (size form, n ceiling, reference-image rules) so the tool schema stays accurate when you route a known model through your own gateway. Declare capabilities on the entry to override individual fields; anything undeclared falls back to the built-in entry, then to a conservative generic contract. Catch-all routes and unknown ids get no contract — the schema stays fully generic, as before.

{
  "pi-image-gen": {
    "defaultModel": "qwen-image-3.0",
    "customProviders": {
      "corp-gateway": {
        "api": "dashscope",
        "baseUrl": "https://gateway.corp.example/api/v1",
        "apiKey": "$GW_KEY",
        "models": [
          "qwen-image-3.0",
          { "id": "my-finetune", "capabilities": { "nMax": 4, "maxReferenceImages": 2 } }
        ]
      }
    }
  }
}

Note: pi.dev custom providers also have an api field, but its values (openai-completions, anthropic-messages, …) are LLM streaming formats that don't apply to image generation. The values here (openai, gemini, dashscope, openrouter, ark) are image-API wire shapes — same field name, different namespace.

Example: self-hosted Stable Diffusion (OpenAI-compatible)

export SD_KEY=local-secret

{
  "pi-image-gen": {
    "defaultModel": "sd3",
    "customProviders": {
      "my-sd": {
        "api": "openai",
        "baseUrl": "http://localhost:8000/v1",
        "apiKey": "$SD_KEY",
        "models": [{ "id": "sd-3-large", "alias": "sd3" }]
      }
    }
  }
}

The agent calls image_generate({prompt: ...}); the extension sees defaultModel: "sd3", finds it under my-sd, and POSTs to http://localhost:8000/v1/images/generations with Bearer $SD_KEY.

Example: Volcengine Doubao image API (OpenAI-compatible)

{
  "pi-image-gen": {
    "defaultModel": "doubao-seed-image",
    "customProviders": {
      "doubao": {
        "api": "openai",
        "baseUrl": "https://ark.cn-beijing.volces.com/api/v3",
        "apiKey": "${ARK_API_KEY}",
        "models": [{ "id": "doubao-seedream-4-0-250828", "alias": "doubao-seed-image" }]
      }
    }
  }
}

Example: a Gemini-shape proxy

If your provider speaks the Google Generative Language wire format:

{
  "pi-image-gen": {
    "defaultModel": "internal-banana",
    "customProviders": {
      "internal": {
        "api": "gemini",
        "baseUrl": "https://gemini-proxy.corp.example/v1beta",
        "apiKey": "$INTERNAL_GEMINI_KEY",
        "models": [{ "id": "gemini-2.5-flash-image", "alias": "internal-banana" }]
      }
    }
  }
}

Direct addressing without an alias

If a custom provider has no models list, you can still address it with <providerName>/<remoteId>:

{
  "pi-image-gen": {
    "defaultModel": "my-sd/sd-3-large",
    "customProviders": {
      "my-sd": { "api": "openai", "baseUrl": "http://localhost:8000/v1", "apiKey": "$SD_KEY" }
    }
  }
}

Tool: `image_generate`

image_generate({
  prompt: string,                  // required — what to draw or how to edit
  image?: string[],                // optional — array of file paths or http(s) URLs
  n?: number,                      // per-model ceiling (qwen 1–6, gpt-image-2 1–10); hidden for Seedream
  size?: string,                   // per-model form (see below); hidden for Gemini models
  aspectRatio?: string,            // Gemini models only — enum from the model's vocabulary
  imageSize?: string,              // Gemini models only — tier enum ("1K"/"2K"/"4K"), when the model has tiers
  quality?: 'low'|'medium'|'high'|'auto', // present only for a built-in gpt-image route (see below)
  filename?: string,               // filename prefix (no extension)
  outputDir?: string,              // override settings.outputDir for this call
})

Returns the absolute file path(s) of saved images. Files land in outputDir (default <cwd>/.pi/images), filename pattern <filename or model-UTC-stamp>.<ext>.

The schema is model-aware. Every built-in model carries a capability contract sourced from the official API docs, and the tool is registered with parameters shaped by that contract (on session start, and again after /image-gen reload) — so the agent sees exactly the knobs the active model honors, with the documented values in enums and descriptions. The contract is advice, not a gate: numeric limits (size ranges, n ceilings, reference-image counts and byte ceilings) are stated in the descriptions but never hard-enforced client-side — a self-hosted deployment or gateway may legitimately diverge from the cloud platform's documented limits, and the provider's own error is the backstop. The only client-side rejections are parameter combinations the adapters would silently drop (a pixel size sent to a Gemini model, or aspectRatio sent to a pixel-size model — the provider never sees those, so it can't complain).

size follows the model's documented form:
- Qwen (qwen-image-*): "<width>*<height>" (asterisk, e.g. "2048*2048"), total pixels 512²–2048²; 3.0 models additionally cap aspect ratio at 1:8–8:1. The x-form is normalized automatically as a safety net.
- Seedream (doubao-seedream-*): a tier token from the model's list (1K/1.5K/2K/3K/4K) or an explicit "<w>x<h>" within the model's pixel window (2K floor on 5.0/4.5).
- gpt-image-2: "auto" or "<w>x<h>" — arbitrary sizes allowed (both edges divisible by 16, ratio ≤ 3:1, 655,360–8,294,400 px, longest edge ≤ 3840), beyond the standard 1024x1024/1536x1024/1024x1536.
- Omit size to use the model's own default (qwen-image-3.0 auto-picks from the prompt).
aspectRatio / imageSize replace size for Gemini models (they have no pixel-size knob): aspectRatio is an enum from the model's vocabulary (10–14 values), imageSize an enum of the model's tiers (1K/2K/4K; hidden when the model is fixed at one tier, as gemini-3.1-flash-lite-image and gemini-2.5-flash-image are).
n carries the model's documented ceiling in its description (qwen 6, gpt-image-2 10) and is hidden for Seedream — that API has no count parameter, so n would be silently dropped.
image spells out the active model's documented reference-image contract in its description (formats, max count, per-image byte ceiling, dimension advice): qwen documents ≤ 3 images (JPG/JPEG/PNG/BMP/TIFF/WEBP/GIF, ≤ 10MB each), Seedream ≤ 10–14 (incl. HEIC/HEIF, ≤ 30MB), gpt-image-2 ≤ 16 (png/webp/jpg, ≤ 50MB), Gemini ≤ 3–14 (≤ 20MB). These are descriptions of the cloud platform's limits, not client-side gates — the provider enforces its own rules.
quality appears only for a built-in gpt-image route — the built-in OpenAI provider on gpt-image-*, or an OpenRouter route whose model id is gpt-image (e.g. openrouter/openai/gpt-image-2). Only there is it constrained to the enum low/medium/high/auto (the vocabulary those APIs document). It is omitted from the schema entirely for:
- Gemini, DashScope/Qwen, and Ark/Seedream — their image APIs have no quality field (Seedream varies quality by size resolution tier instead);
- non-gpt-image routes on the OpenAI/OpenRouter wire — e.g. built-in openai/dall-e-3 (which uses standard/hd) or an OpenRouter route to a non-OpenAI model like Seedream — because the enum above is gpt-image's vocabulary, not the wire format's; and
- any custom provider, including OpenAI-compatible ones — a self-hosted or third-party model may use a different quality vocabulary (e.g. DALL·E 3's standard/hd) or none at all, so the OpenAI wire format alone does not imply the four values above. Passing an unsupported value would only surface as a provider-side 400.
If defaultModel is unset or misconfigured, quality stays present (the tool remains fully featured and execute surfaces a friendly config error). Use "low" for fast drafts and a higher level for final assets or dense text.

Because the schema is fixed at registration, switching models via /image-gen reload re-registers the tool so the parameter set tracks the new provider.

Non-destructive writes: a saved file never overwrites an existing one. Two calls with filename: "hero" produce hero.png then hero-v2.png, so an earlier result is preserved rather than clobbered. Path reservation is atomic (O_EXCL): even many concurrent calls with the same filename each claim a distinct path — no two clobber each other.

Tool result format

The tool's text result is shaped as ready-to-paste markdown the model can copy verbatim into its reply, so the UI renders the image inline:

Generated 1 image(s) via amaster (custom) (qwen-image-2.0). Show each one to the user as inline markdown — copy the lines below verbatim into your reply:

![white](/Users/.../white.png)

The alt text is the filename without its extension — i.e. whatever you passed as filename, or <model>-<UTC-stamp> if you didn't. When OpenAI returns a revised_prompt, it appears as a quote line under the image:

![beaver](/Users/.../beaver.png)
> revised prompt: a cute beaver, photorealistic, water droplets

The markdown URL is platform-shaped so any CommonMark host (desktop, TUI, CLI) keeps it intact: on macOS/Linux a bare absolute path — byte-identical unless it contains markdown-unsafe characters (whitespace, #, ?, %, (), <>), which are percent-escaped; on Windows a percent-encoded file:///… URL (![result](file:///C:/Users/.../result.png)) — sanitizers such as react-markdown's defaultUrlTransform read C: as an unknown URI scheme and strip the img src. Independently of the markdown, details.images[].path always carries the raw filesystem path.

Image-to-image / edit

image is always an array — pass ["path"] for a single image, ["a", "b"] for multi-image conditioning. Each entry must be:

Local file path — a regular png/jpeg/gif/webp/bmp/tiff/heic/heif file inside the session cwd (the active model's accepted formats may be narrower — the image parameter description lists them). Paths may be absolute or relative, but symlinks and paths outside cwd are rejected.
Public http(s) URL — private, loopback, link-local, metadata, credentialed, and unsafe redirect destinations are rejected.

Base64 strings and data: URIs are intentionally rejected — tool arguments don't survive megabyte-sized strings cleanly. If you have raw image bytes, write them to a file under the session cwd and pass that path.

Iterating on a previous result: pass the previous output path back. The next image is conditioned on the last one:

image_generate({ prompt: "a beaver chewing wood", filename: "beaver" })
  → /Users/.../.pi/images/beaver.png

image_generate({ prompt: "now in watercolor style", image: ["/Users/.../.pi/images/beaver.png"] })
  → /Users/.../.pi/images/gpt-image-2-20260605-...png  (edited)

Provider behavior:

Provider	Image input route
OpenAI (`gpt-image-2`)	`POST /v1/images/edits` (multipart). Supports multi-image.
Gemini (`gemini-3-pro-image`, `gemini-3.1-flash-image`, `gemini-3.1-flash-lite-image`, `gemini-2.5-flash-image`)	`inline_data` parts prepended to the user message. Supports multi-image.
DashScope (`qwen-image-3.0-pro`, `qwen-image-3.0`, `qwen-image-2.0-pro`, `qwen-image-2.0`)	`image` parts in `messages[].content`. Up to 3 images.
OpenRouter	`POST /api/v1/images` with `input_references` JSON. Supports multi-image.

There is intentionally no model parameter on the tool — the active model is fixed by pi-image-gen.defaultModel in settings.

Slash commands

/image-gen list — show the active model, which provider it routes to, whether the key is set, configured providers, and the catalog of built-in model ids.
/image-gen reload — re-read settings from disk and re-register the tool so its schema (e.g. whether quality is exposed) tracks the newly selected model.
/image-gen generate <prompt> — generate an image directly from the command line using the active model. Reports the saved file path(s) as a plain-text notification (the command uses ctx.ui.notify, which shows a status line, not rendered Markdown — so unlike the tool result it does not emit an inline ![](…) image). Use the image_generate tool from the agent when you want the image rendered inline.

Use /image-gen list to verify your config — it will tell you when defaultModel is unset, points at a provider with no API key, or names an unknown id.

Bundled skill

This package ships an image-gen skill (skills/image-gen/SKILL.md) that Pi loads on demand. It carries the prompting playbook the one-line tool guidance can't hold: when to use raster generation vs repo-native SVG/CSS, generate-vs-edit intent, n-is-variants-not-assets, multi-image role labeling, edit invariants, text-in-image handling, and the labeled prompt schema. The tool works without it; the skill makes the model use the tool well.

@amaster.ai/pi-image-gen

Signals

Download trend

README

@amaster.ai/pi-image-gen

Install

Configure

All settings fields

Built-in setup walkthrough

1. OpenAI (`gpt-image-2`)

2. Google Gemini "Nano Banana"

3. Alibaba DashScope (Qwen-Image)

4. Volcengine Ark (ByteDance Seedream)

5. OpenRouter (one key, many models)

Custom providers

Example: self-hosted Stable Diffusion (OpenAI-compatible)

Example: Volcengine Doubao image API (OpenAI-compatible)

Example: a Gemini-shape proxy

Direct addressing without an alias

Tool: `image_generate`

Tool result format

Image-to-image / edit

Slash commands

Bundled skill

Signals

Download trend

README

@amaster.ai/pi-image-gen

Install

Configure

All settings fields

Built-in setup walkthrough

1. OpenAI (gpt-image-2)

2. Google Gemini "Nano Banana"

3. Alibaba DashScope (Qwen-Image)

4. Volcengine Ark (ByteDance Seedream)

5. OpenRouter (one key, many models)

Custom providers

Example: self-hosted Stable Diffusion (OpenAI-compatible)

Example: Volcengine Doubao image API (OpenAI-compatible)

Example: a Gemini-shape proxy

Direct addressing without an alias

Tool: image_generate

Tool result format

Image-to-image / edit

Slash commands

Bundled skill

1. OpenAI (`gpt-image-2`)

Tool: `image_generate`