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Taizi Alicloud Ai Image

v1.0.0

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 doc...

0· 238· 1 versions· 1 current· 1 all-time· Updated 22h ago· MIT-0

Install

openclaw skills install taizi-alicloud-ai-image

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):
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:

{
  "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):

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):

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

FieldRequiredNotes
promptyesDescribe a scene, not just keywords.
negative_promptnoBest-effort, may be ignored by backend.
sizeyesWxH format, e.g. 1024*1024, 768*1024.
stylenoOptional stylistic hint.
seednoUse for reproducibility when supported.
reference_imagenoURL/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.

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

ErrorLikely causeAction
401/403Missing or invalid DASHSCOPE_API_KEYCheck env var or ~/.alibabacloud/credentials, and access policy.
400Unsupported size or bad request shapeUse common WxH and validate fields.
429Rate limit or quotaRetry with backoff, or reduce concurrency.
5xxTransient backend errorsRetry 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.

Telegram / channel delivery

When the user requests image generation via Telegram (or other channels), after generating and saving the image to workspace output/ai-image-qwen-image/images/, use the message tool to send the image: action=send, target=telegram, media=<file:// URL>. Always pass explicit target when the session may have mixed sources (e.g. control-ui): extract sender_id from Conversation info metadata in user messages and use target: "<sender_id>" (e.g. target: "6869266119") to ensure delivery to the correct Telegram DM and avoid "bot is not a member of the channel chat" errors. Use file:// absolute paths (e.g. file:///Users/fresh/.openclaw/workspace/output/ai-image-qwen-image/images/xxx.png). Do not use ~/ paths.

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

Version tags

latestvk97dfm2qfpawwshh4cx889ytsx8313kp