| name | aliyun-qwen-generation |
| description | Use when generating or reasoning over text with Alibaba Cloud Model Studio Qwen flagship text models (`qwen3-max`, `qwen3.5-plus`, `qwen3.5-flash`, snapshots, and compatible open-source variants). Use when building chat, agent, tool-calling, or long-context text generation workflows on Model Studio. |
| version | 1.0.0 |
Category: provider
Model Studio Qwen Text Generation
Validation
mkdir -p output/aliyun-qwen-generation
python -m py_compile skills/ai/text/aliyun-qwen-generation/scripts/prepare_generation_request.py && echo "py_compile_ok" > output/aliyun-qwen-generation/validate.txt
Pass criteria: command exits 0 and output/aliyun-qwen-generation/validate.txt is generated.
Output And Evidence
- Save prompt templates, normalized request payloads, and response summaries under
output/aliyun-qwen-generation/.
- Keep one reproducible request example with model name, region, and key parameters.
Use this skill for general text generation, reasoning, tool-calling, and long-context chat on Alibaba Cloud Model Studio.
Critical model names
Prefer the current flagship families:
qwen3-max
qwen3-max-2026-01-23
qwen3.5-plus
qwen3.5-plus-2026-02-15
qwen3.5-flash
qwen3.5-flash-2026-02-23
Common related variants listed in the official model catalog:
qwen3.5-397b-a17b
qwen3.5-122b-a10b
qwen3.5-35b-a3b
qwen3.5-27b
Prerequisites
- Install SDK in a virtual environment:
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.
Normalized interface (text.generate)
Request
messages (array, required): standard chat turns.
model (string, optional): default qwen3.5-plus.
temperature (number, optional)
top_p (number, optional)
max_tokens (int, optional)
enable_thinking (bool, optional)
tools (array, optional)
response_format (object, optional)
stream (bool, optional)
Response
text (string): assistant output.
finish_reason (string, optional)
usage (object, optional)
raw (object, optional)
Quick start (OpenAI-compatible endpoint)
curl -sS https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen3.5-plus",
"messages": [
{"role": "system", "content": "You are a concise assistant."},
{"role": "user", "content": "Summarize why object storage helps media pipelines."}
],
"stream": false
}'
Local helper script
python skills/ai/text/aliyun-qwen-generation/scripts/prepare_generation_request.py \
--prompt "Draft a concise architecture summary for a media ingestion pipeline." \
--model qwen3.5-plus
Operational guidance
- Use snapshot IDs when reproducibility matters.
- Prefer
qwen3.5-flash for lower-latency simple tasks and qwen3-max for harder multi-step tasks.
- Keep tool schemas minimal and explicit when enabling tool calls.
- For multimodal input, route to dedicated VL or Omni skills unless the task is primarily text-centric.
Output location
- Default output:
output/aliyun-qwen-generation/requests/
- Override base dir with
OUTPUT_DIR.
References