alicloud-ai-image-qwen-image

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Generate images with Model Studio DashScope SDK using Qwen Image generation models (qwen-image-max, qwen-image-plus-2026-01-09). Use when implementing or documenting image.generate requests/responses, mapping prompt/negative_prompt/size/seed/reference_image, or integrating image generation into the video-agent pipeline.

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Sourcecinience/alicloud-skills

Added on2026-02-27

NPX Install

npx skill4agent add cinience/alicloud-skills alicloud-ai-image-qwen-image

SKILL.md Content

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Category: provider

Model Studio Qwen Image

Build consistent image generation behavior for the video-agent pipeline by standardizing

image.generate

inputs/outputs and using DashScope SDK (Python) with the exact model name.

Prerequisites

Install SDK (recommended in a venv to avoid PEP 668 limits):

bash

python3 -m venv .venv
. .venv/bin/activate
python -m pip install dashscope

Set

DASHSCOPE_API_KEY

in your environment, or add

dashscope_api_key

to

~/.alibabacloud/credentials

(env takes precedence).

Critical model names

Use one of these exact model strings:

```
qwen-image-max
```
```
qwen-image-plus-2026-01-09
```

Normalized interface (image.generate)

Request

```
prompt
```
(string, required)
```
negative_prompt
```
(string, optional)
```
size
```
(string, required) e.g.
```
1024*1024
```
,
```
768*1024
```
```
style
```
(string, optional)
```
seed
```
(int, optional)
```
reference_image
```
(string | bytes, optional)

Response

```
image_url
```
(string)
```
width
```
(int)
```
height
```
(int)
```
seed
```
(int)

Quickstart (normalized request + preview)

Minimal normalized request body:

json

{
  "prompt": "a cinematic portrait of a cyclist at dusk, soft rim light, shallow depth of field",
  "negative_prompt": "blurry, low quality, watermark",
  "size": "1024*1024",
  "seed": 1234
}

Preview workflow (download then open):

bash

curl -L -o output/ai-image-qwen-image/images/preview.png "<IMAGE_URL_FROM_RESPONSE>" && open output/ai-image-qwen-image/images/preview.png

Local helper script (JSON request -> image file):

bash

python skills/ai/image/alicloud-ai-image-qwen-image/scripts/generate_image.py \\
  --request '{"prompt":"a studio product photo of headphones","size":"1024*1024"}' \\
  --output output/ai-image-qwen-image/images/headphones.png \\
  --print-response

Parameters at a glance

Field	Required	Notes
`prompt`	yes	Describe a scene, not just keywords.
`negative_prompt`	no	Best-effort, may be ignored by backend.
`size`	yes	`WxH` format, e.g. `10241024` , `7681024` .
`style`	no	Optional stylistic hint.
`seed`	no	Use for reproducibility when supported.
`reference_image`	no	URL/file/bytes, SDK-specific mapping.

Quick start (Python + DashScope SDK)

Use the DashScope SDK and map the normalized request into the SDK call. Note: For

qwen-image-max

, the DashScope SDK currently succeeds via

ImageGeneration

(messages-based) rather than

ImageSynthesis

. If the SDK version you are using expects a different field name for reference images, adapt the

input

mapping accordingly.

python

import os
from dashscope.aigc.image_generation import ImageGeneration

# Prefer env var for auth: export DASHSCOPE_API_KEY=...
# Or use ~/.alibabacloud/credentials with dashscope_api_key under [default].


def generate_image(req: dict) -> dict:
    messages = [
        {
            "role": "user",
            "content": [{"text": req["prompt"]}],
        }
    ]

    if req.get("reference_image"):
        # Some SDK versions accept {"image": <url|file|bytes>} in messages content.
        messages[0]["content"].insert(0, {"image": req["reference_image"]})

    response = ImageGeneration.call(
        model=req.get("model", "qwen-image-max"),
        messages=messages,
        size=req.get("size", "1024*1024"),
        api_key=os.getenv("DASHSCOPE_API_KEY"),
        # Pass through optional parameters if supported by the backend.
        negative_prompt=req.get("negative_prompt"),
        style=req.get("style"),
        seed=req.get("seed"),
    )

    # Response is a generation-style envelope; extract the first image URL.
    content = response.output["choices"][0]["message"]["content"]
    image_url = None
    for item in content:
        if isinstance(item, dict) and item.get("image"):
            image_url = item["image"]
            break
    return {
        "image_url": image_url,
        "width": response.usage.get("width"),
        "height": response.usage.get("height"),
        "seed": req.get("seed"),
    }

Error handling

Error	Likely cause	Action
401/403	Missing or invalid `DASHSCOPE_API_KEY`	Check env var or `~/.alibabacloud/credentials` , and access policy.
400	Unsupported size or bad request shape	Use common `WxH` and validate fields.
429	Rate limit or quota	Retry with backoff, or reduce concurrency.
5xx	Transient backend errors	Retry with backoff once or twice.

Output location

Default output:
```
output/ai-image-qwen-image/images/
```
Override base dir with
```
OUTPUT_DIR
```
.

Operational guidance

Store the returned image in object storage and persist only the URL in metadata.

Cache results by

(prompt, negative_prompt, size, seed, reference_image hash)

to avoid duplicate costs.

Add retries for transient 429/5xx responses with exponential backoff.
Some backends ignore
```
negative_prompt
```
,
```
style
```
, or
```
seed
```
; treat them as best-effort inputs.
If the response contains no image URL, surface a clear error and retry once with a simplified prompt.

Size notes

Use
```
WxH
```
format (e.g.
```
1024*1024
```
,
```
768*1024
```
).
Prefer common sizes; unsupported sizes can return 400.

Anti-patterns

Do not invent model names or aliases; use official model IDs only.
Do not store large base64 blobs in DB rows; use object storage.
Do not omit user-visible progress for long generations.

References

See
```
references/api_reference.md
```
for a more detailed DashScope SDK mapping and response parsing tips.
See
```
references/prompt-guide.md
```
for prompt patterns and examples.

For edit workflows, use

skills/ai/image/alicloud-ai-image-qwen-image-edit/

.

Source list:
```
references/sources.md
```

alicloud-ai-image-qwen-image

NPX Install

Tags

SKILL.md Content

Model Studio Qwen Image

Prerequisites

Critical model names

Normalized interface (image.generate)

Request

Response

Quickstart (normalized request + preview)

Parameters at a glance

Quick start (Python + DashScope SDK)

Error handling

Output location

Operational guidance

Size notes

Anti-patterns

References