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Venice Image Generate

skill-veniceai-skills-venice-image-generate · by veniceai

Generate images with Venice. Covers POST /image/generate (Venice-native), POST /images/generations (OpenAI-compatible), GET /image/styles (style presets), request fields (prompt, dimensions, cfg_scale, seed, variants, style_preset, aspect_ratio, resolution, safe_mode, watermark), and response formats.

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Install

$ agentstack add skill-veniceai-skills-venice-image-generate

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Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access Used
  • Filesystem access Used
  • Shell / process execution No
  • Environment & secrets Used
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

Venice Image Generation

Two text-to-image endpoints:

  1. POST /api/v1/image/generate — Venice-native, full control (negative prompts, CFG, seed, up to 4 variants).
  2. POST /api/v1/images/generations — OpenAI-compatible, fewer knobs but drop-in for the OpenAI SDK.

Plus:

  • GET /api/v1/image/styles — list of style preset names for style_preset.

For editing / upscaling / multi-image / background removal, see [venice-image-edit](../venice-image-edit/SKILL.md).

Use when

  • You need to generate images from text prompts.
  • You need multiple variants in one call.
  • You're porting from OpenAI's images.generate and want a zero-change SDK swap.
  • You want to browse style presets before committing to one.

/image/generate — Venice-native

Request

curl https://api.venice.ai/api/v1/image/generate \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "z-image-turbo",
    "prompt": "A beautiful sunset over a mountain range",
    "width": 1024,
    "height": 1024,
    "cfg_scale": 7.5,
    "steps": 8,
    "seed": 123456789,
    "variants": 1,
    "format": "webp",
    "style_preset": "3D Model",
    "safe_mode": true
  }'

Fields

| Field | Type | Default | Notes | |---|---|---|---| | model | string | — | Required. Image model ID. GET /models?type=image. | | prompt | string | — | Required. Max promptCharacterLimit from the model's model_spec.constraints (typically 1500–7500). | | negative_prompt | string | — | Describe what not to show. Same character cap as prompt. | | width, height | int | 1024, 1024 | ≤ 1280 each. Must be divisible by constraints.widthHeightDivisor on the model's model_spec. | | aspect_ratio | string | — | "1:1", "16:9", "9:16", … — used by models like Nano Banana instead of width/height. | | resolution | string | — | "1K", "2K", "4K" — used by resolution-driven models. | | cfg_scale | number | model default | 0 ", ""], "timing": {...}, "request": {...} }


With `return_binary: true`, response is raw `image/webp` (or `png`/`jpeg`) with matching `Content-Type`.

## `/images/generations` — OpenAI-compatible

Use this if you're already on the OpenAI SDK. Field names match `openai.images.generate()`.

```ts
import OpenAI from 'openai'

const client = new OpenAI({
  apiKey: process.env.VENICE_API_KEY,
  baseURL: 'https://api.venice.ai/api/v1',
})

const res = await client.images.generate({
  model: 'z-image-turbo',
  prompt: 'A beautiful sunset over mountain ranges',
  size: '1024x1024',
  response_format: 'b64_json',
})

const b64 = res.data[0].b64_json

Mapped fields

| Field | Values | Notes | |---|---|---| | model | string, default "default" | Unknown model IDs fall back to Venice's default. | | prompt | string, ≤ 1500 chars | Required. | | size | auto, 256x256, 512x512, 1024x1024, 1536x1024, 1024x1536, 1792x1024, 1024x1792 | — | | output_format | jpeg / png / webp | Defaults to png. | | response_format | b64_json / url | url returns a data: URL (not a hosted URL). | | moderation | auto (safe mode on) / low (safe mode off) | — | | n | 1 | Venice only supports a single image per call here. | | quality, style (vivid/natural), background, output_compression, user | — | Accepted for OpenAI compat, not used by Venice. |

If you need variants, seed, negative_prompt, cfg_scale, or style_preset, switch to /image/generate.

/image/styles — list presets

curl https://api.venice.ai/api/v1/image/styles \
  -H "Authorization: Bearer $VENICE_API_KEY"

Returns a list of styles[], each with a name you can pass to style_preset. Cache this — it's small and stable.

Choosing a model

curl "https://api.venice.ai/api/v1/models?type=image" \
  -H "Authorization: Bearer $VENICE_API_KEY"

Inspect per-model model_spec:

  • constraints.widthHeightDivisorwidth and height must both be divisible by this.
  • constraints.aspectRatios[] + defaultAspectRatio — if present, the model supports aspect-ratio-driven sizing.
  • constraints.resolutions[] + defaultResolution — if present, the model supports resolution (1K/2K/4K).
  • constraints.steps.{default,max} — step bounds (some models ignore steps entirely).
  • constraints.promptCharacterLimit — max prompt length (also applies to negative_prompt).
  • pricing.generation.usd — flat USD per image, or pricing.resolutions[].usd for resolution-tiered models.

Pick a model that matches the feature + size combo you plan to use.

Common patterns

Fixed-seed A/B test

{"model": "z-image-turbo", "prompt": "...", "seed": 42, "variants": 4}

Aspect-ratio-driven model (Nano Banana family)

{"model": "nano-banana-2", "prompt": "...", "aspect_ratio": "16:9", "resolution": "2K"}

(Other nano-banana variants: nano-banana-pro. Always verify the current ID via GET /models?type=image.)

Style preset + negative

{
  "model": "z-image-turbo",
  "prompt": "a red sports car in a parking lot",
  "negative_prompt": "blurry, people, clouds",
  "style_preset": "3D Model"
}

Stream binary to disk (Node)

const res = await fetch('https://api.venice.ai/api/v1/image/generate', {
  method: 'POST',
  headers: { Authorization: `Bearer ${process.env.VENICE_API_KEY}`, 'Content-Type': 'application/json' },
  body: JSON.stringify({ model: 'z-image-turbo', prompt: '...', return_binary: true }),
})
if (!res.ok) throw new Error(await res.text())
const buf = Buffer.from(await res.arrayBuffer())
await fs.writeFile('out.webp', buf)

Errors

| Code | Meaning | |---|---| | 400 | Bad params (e.g. dimensions not divisible by widthHeightDivisor, prompt too long, variants>1 with return_binary). | | 401 | Auth or Pro-only model. | | 402 | Insufficient balance. Bearer: plain { "error": "Insufficient balance" }; x402: PAYMENT_REQUIRED body + PAYMENT-REQUIRED header. | | 415 | Wrong Content-Type (send application/json for this endpoint). | | 429 | Rate limited. | | 500 / 503 | Inference or capacity issue — retry with jitter. |

(Content-policy violations on /image/generate come back as 400 with an error string, not 422 — the 422 shape is specific to audio generation paths.)

Gotchas

  • Each model picks one sizing idiom: either width/height, aspect_ratio + resolution, or (OpenAI-compat) size. Match the model's constraints.
  • variants > 1 requires return_binary: false (JSON with base64 array).
  • steps is ignored by fast/turbo models; they hardcode step count internally.
  • hide_watermark: true is advisory — Venice may still watermark content flagged by safety classifiers.
  • Old inpaint field is deprecated; don't use it.
  • For OpenAI-compat, response_format: "url" returns a data URL, not a hosted URL — plan for that if you're saving to storage.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.