aliyun-qwen-deep-research

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🇺🇸

Original

English

🇨🇳

Translation

Chinese

Category: provider

分类：provider

Model Studio Qwen Deep Research

Validation

验证

bash

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.

bash

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

通过标准：命令退出码为0，且成功生成

output/aliyun-qwen-deep-research/validate.txt

文件。

Output And Evidence

输出与证据

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.

所有调研目标、确认回复、标准化请求载荷和最终报告快照均保存至
```
output/aliyun-qwen-deep-research/
```
目录下。
每次运行的记录需要保留所使用的精确模型名称、区域和
```
enable_feedback
```
配置项。

当用户需要深度、多阶段的调研工作流而非单次对话补全时，请使用此技能。

Critical model names

关键模型名称

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.

请使用以下精确模型字符串之一：

```
qwen-deep-research
```
```
qwen-deep-research-2025-12-15
```

选型指南：

如需使用当前主线版本模型，请选择
```
qwen-deep-research
```
。
当你需要支持MCP工具调用且可复现性更强的快照版本时，请选择
```
qwen-deep-research-2025-12-15
```
。

Prerequisites

前置条件

Install SDK in a virtual environment:

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

~/.alibabacloud/credentials

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

在虚拟环境中安装SDK：

bash

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

在环境变量中设置

DASHSCOPE_API_KEY

，或者在

~/.alibabacloud/credentials

文件中添加

dashscope_api_key

配置。

该模型目前仅适用于中国大陆（北京）区域，使用其自有API形态，不兼容OpenAI兼容模式。

Normalized interface (research.run)

标准化接口（research.run）

Request

请求参数

```
topic
```
(string, required)
```
model
```
(string, optional): default
```
qwen-deep-research
```
```
messages
```
(array<object>, optional)
```
enable_feedback
```
(bool, optional): default
```
true
```
```
stream
```
(bool, optional): must be
```
true
```
```
attachments
```
(array<object>, optional): image URLs and related context

```
topic
```
（字符串，必填）
```
model
```
（字符串，选填）：默认值为
```
qwen-deep-research
```
```
messages
```
（对象数组，选填）
```
enable_feedback
```
（布尔值，选填）：默认值为
```
true
```
```
stream
```
（布尔值，选填）：必须设为
```
true
```
```
attachments
```
（对象数组，选填）：图片URL及相关上下文

Response

响应参数

```
status
```
(string): stage status such as
```
thinking
```
,
```
researching
```
, or
```
finished
```
```
text
```
(string, optional): streamed content chunk
```
report
```
(string, optional): final structured research report
```
raw
```
(object, optional)

```
status
```
（字符串）：阶段状态，例如
```
thinking
```
（思考中）、
```
researching
```
（调研中）或
```
finished
```
（已完成）
```
text
```
（字符串，选填）：流式输出内容块
```
report
```
（字符串，选填）：最终的结构化调研报告
```
raw
```
（对象，选填）

Quick start

快速开始

bash

python skills/ai/research/aliyun-qwen-deep-research/scripts/prepare_deep_research_request.py \
  --topic "Compare cloud video generation model trade-offs for marketing automation." \
  --disable-feedback

bash

python skills/ai/research/aliyun-qwen-deep-research/scripts/prepare_deep_research_request.py \
  --topic "Compare cloud video generation model trade-offs for marketing automation." \
  --disable-feedback

Operational guidance

使用指南

Expect streaming output only.
Keep the initial topic concrete and bounded; broad topics can trigger long iterative search plans.
If the model asks follow-up questions and you already know the constraints, answer them explicitly to avoid wasted rounds.
Use the snapshot model when you need stable evaluation runs or MCP tool-calling support.

仅支持流式输出。
初始主题需具体、边界清晰；宽泛的主题会触发耗时较长的迭代搜索计划。
如果模型提出追问，而你已经知晓约束条件，请明确回复，避免无意义的交互轮次。
当你需要稳定的评估运行或MCP工具调用支持时，请使用快照版本模型。

Output location

输出位置

Default output:

output/aliyun-qwen-deep-research/requests/

Override base dir with
```
OUTPUT_DIR
```
.

默认输出路径：

output/aliyun-qwen-deep-research/requests/

可通过
```
OUTPUT_DIR
```
环境变量覆盖基础目录。

References

参考资料

```
references/sources.md
```

```
references/sources.md
```