← 返回 Skills 市场

Aliyun Qwen Text Embedding

Name: Aliyun Qwen Text Embedding
Author: cinience

作者 cinience · GitHub ↗ · v1.0.0 · MIT-0

cross-platform ✓ 安全检测通过

120

总下载

当前安装

版本数

在 OpenClaw 中安装

/install aliyun-qwen-text-embedding

功能描述

Use when text embeddings are needed from Alibaba Cloud Model Studio models for semantic search, retrieval-augmented generation, clustering, or offline vector...

使用说明 (SKILL.md)

Category: provider

Model Studio Text Embedding

Validation

mkdir -p output/aliyun-qwen-text-embedding
python -m py_compile skills/ai/search/aliyun-qwen-text-embedding/scripts/prepare_embedding_request.py && echo "py_compile_ok" > output/aliyun-qwen-text-embedding/validate.txt

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

Critical model names

Use one of these exact model strings as needed:

text-embedding-v4
text-embedding-v3
text-embedding-v2
text-embedding-v1
qwen3-embedding-8b
qwen3-embedding-4b
qwen3-embedding-0.6b

Quick start

python skills/ai/search/aliyun-qwen-text-embedding/scripts/prepare_embedding_request.py \
  --text "Alibaba Cloud Model Studio" \
  --output output/aliyun-qwen-text-embedding/request.json

Notes

Pair this skill with skills/ai/search/aliyun-dashvector-search/ or other vector-store skills.
For image or multimodal embeddings, add dedicated multimodal embedding coverage separately.

References

references/sources.md

安全使用建议

This skill is small and coherent: it only generates a local JSON request payload for Alibaba Cloud Model Studio embeddings. Before using in production, verify the source (unknown homepage) and the model names listed match the target API version you intend to call. The skill does not perform the API call itself, so you'll need to supply appropriate Alibaba Cloud credentials and a separate client/integration to send the generated request — review that integration for credential handling. Note the agents/openai.yaml default_prompt references "$alicloud-ai-search-text-embedding" which is a minor naming inconsistency (harmless but check prompts/variable names when wiring into agents).

功能分析

Type: OpenClaw Skill Name: aliyun-qwen-text-embedding Version: 1.0.0 The skill bundle is a straightforward utility for generating JSON request payloads for Alibaba Cloud Model Studio text embedding models. The primary script, scripts/prepare_embedding_request.py, performs basic string formatting and file writing without any network access, environment variable retrieval, or shell execution, and the SKILL.md instructions are strictly aligned with the stated purpose.

能力评估

✓ Purpose & Capability

Name, description, and included script align: the script builds a minimal payload for Model Studio embedding models and SKILL.md documents the correct model names and usage. The agent interface text references Alibaba Cloud embedding functionality (minor naming mismatch noted below) but otherwise matches purpose.

✓ Instruction Scope

Runtime instructions only compile and run a small Python script to write a local request.json; they do not read unrelated files, access network endpoints, or reference credentials. The instructions stay within the stated task of preparing embedding requests.

✓ Install Mechanism

No install spec is provided (instruction-only), so nothing is downloaded or installed. This minimizes disk/execute risk.

✓ Credentials

The skill declares no required environment variables, no primary credential, and no config paths. That is proportionate because the included script only creates a local JSON payload and does not call external APIs.

✓ Persistence & Privilege

No 'always' privilege is requested, the skill is user-invocable only, and it does not modify system or other skills' configuration. It writes only to its own output path when run.

如何使用

确保已安装 OpenClaw（本地或 Docker 部署）
在对话框中输入安装命令：/install aliyun-qwen-text-embedding
安装完成后，直接呼叫该 Skill 的名称或使用 /aliyun-qwen-text-embedding 触发
根据 Skill 的参数说明提供必要输入，即可获得结构化输出

版本历史

v1.0.0

- Initial release of aliyun-qwen-text-embedding (v1.0.0). - Provides access to Alibaba Cloud Model Studio text embedding models. - Supports use cases like semantic search, retrieval-augmented generation, clustering, and offline vectorization. - Lists validated model names for easy selection. - Includes guidance on quick start and integration with vector store skills.

元数据

Slug aliyun-qwen-text-embedding

版本 1.0.0

许可证 MIT-0

累计安装 0

当前安装数 0

历史版本数 1

常见问题