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Qwen Image Generation — Execution Guide

Fallback paths when the bundled script (Path 1) fails or is unavailable.

Path 0 · Environment Fix

When the script fails due to environment issues (not API errors):

1. python3 not found: Try python --version or py -3 --version. Use whichever returns 3.9+. If none work, help the user install Python 3.9+ from https://www.python.org/downloads/. 2. Version too low (Python 3.9+ required or SyntaxError): Install Python 3.9+ alongside existing Python, then use python3.9 or python3.11 explicitly. 3. SSL errors (CERTIFICATE_VERIFY_FAILED): On macOS, run /Applications/Python\ 3.x/Install\ Certificates.command. On Linux/Windows, set SSL_CERT_FILE to point to your CA bundle. 4. Proxy: Set HTTPS_PROXY=http://proxy:port before running the script.

After fixing, retry the script (Path 1). If the environment is unfixable, fall through to Path 2 (curl) below — curl is available on most systems without Python.

Path 2 · Direct API Call (curl)

Sync mode (wan2.6, recommended)

Step 1 — Generate image:

curl -sS -X POST "https://dashscope.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation" \
  -H "Authorization: Bearer $DASHSCOPE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "wan2.6-t2i",
    "input": {
      "messages": [{"role": "user", "content": [{"text": "A cozy flower shop with wooden door"}]}]
    },
    "parameters": {
      "size": "1280*1280",
      "prompt_extend": true,
      "n": 1
    }
  }'

Step 2 — Extract image URL from output.results[0].url:

{
  "output": {
    "results": [{"url": "https://dashscope-result-...oss-cn-beijing.aliyuncs.com/..."}]
  },
  "usage": {"image_count": 1}
}

Step 3 — Download the image (URL valid 24 hours):

curl -o image.png "IMAGE_URL_FROM_STEP_2"

Async mode (wan2.5 and older models)

Step 1 — Submit task:

curl -sS -X POST "https://dashscope.aliyuncs.com/api/v1/services/aigc/image-generation/generation" \
  -H "Authorization: Bearer $DASHSCOPE_API_KEY" \
  -H "Content-Type: application/json" \
  -H "X-DashScope-Async: enable" \
  -d '{
    "model": "wan2.5-t2i-preview",
    "input": {
      "prompt": "A cozy flower shop with wooden door",
      "negative_prompt": "blurry, low quality"
    },
    "parameters": {
      "size": "1280*1280",
      "n": 1
    }
  }'

Extract output.task_id from response.

Step 2 — Poll until done (repeat every 5–10s):

curl -sS "https://dashscope.aliyuncs.com/api/v1/tasks/TASK_ID" \
  -H "Authorization: Bearer $DASHSCOPE_API_KEY"

Wait until output.task_status is SUCCEEDED (or FAILED).

Step 3 — Download from output.results[0].url:

curl -o image.png "IMAGE_URL_FROM_POLL_RESPONSE"

Region endpoints (replace base URL as needed):

| Region | Base URL | |--------|----------| | Beijing (default) | https://dashscope.aliyuncs.com/api/v1 |

wan2.7-image-pro: Text-to-image with thinking mode (sync)

Step 1 — Generate image:

curl -sS -X POST "https://dashscope.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation" \
  -H "Authorization: Bearer $DASHSCOPE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "wan2.7-image-pro",
    "input": {
      "messages": [{"role": "user", "content": [{"text": "A cozy flower shop with delicate wooden door and morning sunlight"}]}]
    },
    "parameters": {
      "size": "4K",
      "n": 1,
      "thinking_mode": true,
      "watermark": false
    }
  }'

Step 2 — Extract image URL from output.choices[0].message.content[0].image, then download.

wan2.7-image-pro: Sequential multi-image (sync)

curl -sS -X POST "https://dashscope.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation" \
  -H "Authorization: Bearer $DASHSCOPE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "wan2.7-image-pro",
    "input": {
      "messages": [{"role": "user", "content": [{"text": "A stray orange cat through four seasons"}]}]
    },
    "parameters": {
      "size": "2K",
      "enable_sequential": true,
      "n": 4,
      "watermark": false
    }
  }'

Multiple images returned in output.choices[0].message.content[].image.

wan2.7-image-pro: Image editing with references (sync)

curl -sS -X POST "https://dashscope.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation" \
  -H "Authorization: Bearer $DASHSCOPE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "wan2.7-image-pro",
    "input": {
      "messages": [{"role": "user", "content": [
        {"text": "Apply the graffiti from image 2 onto the car in image 1"},
        {"image": "https://img.alicdn.com/imgextra/i1/NotRealJustExample/car.jpg"},
        {"image": "https://img.alicdn.com/imgextra/i1/NotRealJustExample/graffiti.jpg"}
      ]}]
    },
    "parameters": {
      "size": "2K",
      "n": 1,
      "watermark": false
    }
  }'

Extract image URL from output.choices[0].message.content[0].image, then download.

wan2.6-image: Image editing (sync)

Step 1 — Generate edited image:

curl -sS -X POST "https://dashscope.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation" \
  -H "Authorization: Bearer $DASHSCOPE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "wan2.6-image",
    "input": {
      "messages": [{"role": "user", "content": [
        {"text": "Apply watercolor painting style to this photo"},
        {"image": "https://img.alicdn.com/imgextra/i1/NotRealJustExample/photo.jpg"}
      ]}]
    },
    "parameters": {
      "size": "1K",
      "n": 1,
      "prompt_extend": true,
      "enable_interleave": false,
      "watermark": false
    }
  }'

Step 2 — Extract image URL from output.choices[0].message.content[0].image:

{
  "output": {
    "choices": [{"finish_reason": "stop", "message": {"role": "assistant", "content": [{"image": "https://...", "type": "image"}]}}],
    "finished": true
  },
  "usage": {"image_count": 1, "size": "1376*768"}
}

Step 3 — Download the image (URL valid 24 hours):

curl -o edited.png "IMAGE_URL_FROM_STEP_2"

wan2.6-image: Multi-image composition (sync)

curl -sS -X POST "https://dashscope.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation" \
  -H "Authorization: Bearer $DASHSCOPE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "wan2.6-image",
    "input": {
      "messages": [{"role": "user", "content": [
        {"text": "Generate a sunset scene based on the style of image 1 and the background of image 2"},
        {"image": "https://img.alicdn.com/imgextra/i1/NotRealJustExample/style.jpg"},
        {"image": "https://img.alicdn.com/imgextra/i1/NotRealJustExample/background.jpg"}
      ]}]
    },
    "parameters": {"size": "1K", "n": 1, "prompt_extend": true, "enable_interleave": false}
  }'

wan2.6-image: Interleaved text-image output (async)

Step 1 — Submit task:

curl -sS -X POST "https://dashscope.aliyuncs.com/api/v1/services/aigc/image-generation/generation" \
  -H "Authorization: Bearer $DASHSCOPE_API_KEY" \
  -H "Content-Type: application/json" \
  -H "X-DashScope-Async: enable" \
  -d '{
    "model": "wan2.6-image",
    "input": {
      "messages": [{"role": "user", "content": [
        {"text": "Give me a three-image tutorial for making latte art"}
      ]}]
    },
    "parameters": {"enable_interleave": true, "max_images": 3, "size": "1280*1280"}
  }'

Extract output.task_id from the response.

Step 2 — Poll until done (repeat every 10s):

curl -sS "https://dashscope.aliyuncs.com/api/v1/tasks/TASK_ID" \
  -H "Authorization: Bearer $DASHSCOPE_API_KEY"

Wait until output.task_status is SUCCEEDED. The response output.choices[0].message.content contains interleaved {type: "text", text: "..."} and {type: "image", image: "URL"} items.

Step 3 — Download images from the interleaved content:

Download each image URL from the interleaved content

curl -o image_1.png "IMAGE_URL_1"
curl -o image_2.png "IMAGE_URL_2"
curl -o image_3.png "IMAGE_URL_3"

wan2.5-i2i-preview: Single-image editing (async-only)

Step 1 — Submit task:

curl -sS -X POST "https://dashscope.aliyuncs.com/api/v1/services/aigc/image2image/image-synthesis" \
  -H "Authorization: Bearer $DASHSCOPE_API_KEY" \
  -H "Content-Type: application/json" \
  -H "X-DashScope-Async: enable" \
  -d '{
    "model": "wan2.5-i2i-preview",
    "input": {
      "prompt": "Change the dress to a vintage lace long dress with embroidery details",
      "images": ["https://img.alicdn.com/imgextra/i3/O1CN0157XGE51l6iL9441yX_!!6000000004770-49-tps-1104-1472.webp"]
    },
    "parameters": {"prompt_extend": true, "n": 1}
  }'

Extract output.task_id from response.

Step 2 — Poll until done (repeat every 5–10s):

curl -sS "https://dashscope.aliyuncs.com/api/v1/tasks/TASK_ID" \
  -H "Authorization: Bearer $DASHSCOPE_API_KEY"

Wait until output.task_status is SUCCEEDED.

Step 3 — Download from output.results[0].url:

curl -o edited.png "IMAGE_URL_FROM_POLL_RESPONSE"

wan2.5-i2i-preview: Multi-image fusion (async-only)

curl -sS -X POST "https://dashscope.aliyuncs.com/api/v1/services/aigc/image2image/image-synthesis" \
  -H "Authorization: Bearer $DASHSCOPE_API_KEY" \
  -H "Content-Type: application/json" \
  -H "X-DashScope-Async: enable" \
  -d '{
    "model": "wan2.5-i2i-preview",
    "input": {
      "prompt": "Place the alarm clock from Image 1 next to the vase on the table in Image 2",
      "images": [
        "https://img.alicdn.com/imgextra/i3/O1CN0157XGE51l6iL9441yX_!!6000000004770-49-tps-1104-1472.webp",
        "https://img.alicdn.com/imgextra/i3/O1CN01SfG4J41UYn9WNt4X1_!!6000000002530-49-tps-1696-960.webp"
      ]
    },
    "parameters": {"prompt_extend": true, "n": 1}
  }'

Then poll and download as in the single-image case above.

qwen-image-2.0-pro: Image editing (sync)

Step 1 — Generate edited image:

curl -sS -X POST "https://dashscope.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation" \
  -H "Authorization: Bearer $DASHSCOPE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen-image-2.0-pro",
    "input": {
      "messages": [{"role": "user", "content": [
        {"image": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20250925/thtclx/input1.png"},
        {"image": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20250925/iclsnx/input2.png"},
        {"text": "Make the girl from Image 1 wear the black dress from Image 2"}
      ]}]
    },
    "parameters": {
      "size": "1024*1536",
      "n": 2,
      "prompt_extend": true,
      "watermark": false
    }
  }'

Step 2 — Extract image URLs from output.choices[0].message.content[].image:

{
  "output": {
    "choices": [{"finish_reason": "stop", "message": {"role": "assistant", "content": [{"image": "https://...", "type": "image"}, {"image": "https://...", "type": "image"}]}}]
  }
}

Step 3 — Download the images (URLs valid 24 hours):

curl -o edited_1.png "IMAGE_URL_1"
curl -o edited_2.png "IMAGE_URL_2"

qwen-image-2.0-pro: Pure text-to-image (sync)

curl -sS -X POST "https://dashscope.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation" \
  -H "Authorization: Bearer $DASHSCOPE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen-image-2.0-pro",
    "input": {
      "messages": [{"role": "user", "content": [
        {"text": "A vintage coffee shop poster with elegant calligraphy: Open Daily 7AM-9PM"}
      ]}]
    },
    "parameters": {"size": "1024*1536", "n": 1, "prompt_extend": true}
  }'

Extract image URL from output.choices[0].message.content[0].image, then download.

qwen-image-plus / qwen-image-max: Text-to-image (async)

Step 1 — Submit task:

curl -sS -X POST "https://dashscope.aliyuncs.com/api/v1/services/aigc/text2image/image-synthesis" \
  -H "Authorization: Bearer $DASHSCOPE_API_KEY" \
  -H "Content-Type: application/json" \
  -H "X-DashScope-Async: enable" \
  -d '{
    "model": "qwen-image-plus",
    "input": {
      "prompt": "A healing-style hand-drawn poster featuring three puppies playing with a ball on green grass"
    },
    "parameters": {"size": "1664*928", "n": 1, "prompt_extend": true, "watermark": false}
  }'

Extract output.task_id from response.

Step 2 — Poll until done (repeat every 5–10s):

curl -sS "https://dashscope.aliyuncs.com/api/v1/tasks/TASK_ID" \
  -H "Authorization: Bearer $DASHSCOPE_API_KEY"

Wait until output.task_status is SUCCEEDED.

Step 3 — Download from output.results[0].url:

curl -o image.png "IMAGE_URL_FROM_POLL_RESPONSE"

Valid sizes for qwen-image-plus/max: 1664928 (16:9), 14721104 (4:3), 13281328 (1:1), 11041472 (3:4), 928*1664 (9:16)

Paths 3–5 · Fallback Cascade

When agent-executed paths (1–2) fail or shell is restricted:

Path 3 — Generate Python script: Read scripts/image.py to understand the API logic (sync/async, file upload, download, image editing, interleaved output). Write a self-contained Python script (stdlib urllib) tailored to the user's task. Present it for the user to save and run. Use os.environ["DASHSCOPE_API_KEY"] — never hardcode or expose the key.

Path 4 — Generate curl commands: Customize the curl templates from Path 2 with the user's specific parameters. Present as ready-to-copy commands.

Path 5 — Autonomous resolution: Read scripts/image.py source and references/*.md to understand the full API contract. Reason about alternative approaches and implement.

For local file references (e.g. reference_images pointing to local paths), Path 1 is strongly preferred — the script auto-uploads to DashScope temp storage and injects the oss:// URL.

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