Category: provider

Model Studio Qwen Deep Research

Validation

mkdir -p output/aliyun-qwen-deep-research
python -m py_compile skills/ai/research/aliyun-qwen-deep-research/scripts/prepare_deep_research_request.py && echo "py_compile_ok" > output/aliyun-qwen-deep-research/validate.txt

Pass criteria: command exits 0 and output/aliyun-qwen-deep-research/validate.txt is generated.

Output And Evidence

• Save research goals, confirmation answers, normalized request payloads, and final report snapshots under output/aliyun-qwen-deep-research/.
• Keep the exact model, region, and enable_feedback setting with each saved run.

Use this skill when the user wants a deep, multi-stage research workflow rather than a single chat completion.

Critical model names

Use one of these exact model strings:

• qwen-deep-research
• qwen-deep-research-2025-12-15

Selection guidance:

• Use qwen-deep-research for the current mainline model.
• Use qwen-deep-research-2025-12-15 when you need the snapshot with MCP tool-calling support and stronger reproducibility.

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.
• This model currently applies to the China mainland (Beijing) region and uses its own API shape rather than OpenAI-compatible mode.

Normalized interface (research.run)

Request

• topic (string, required)
• model (string, optional): default qwen-deep-research
• messages (array