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Aliyun Qwen Text Embedding

by cinience · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install aliyun-qwen-text-embedding
Description
Use when text embeddings are needed from Alibaba Cloud Model Studio models for semantic search, retrieval-augmented generation, clustering, or offline vector...
README (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
Usage Guidance
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).
Capability Analysis
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.
Capability Assessment
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.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install aliyun-qwen-text-embedding
  3. After installation, invoke the skill by name or use /aliyun-qwen-text-embedding
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
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.
Metadata
Slug aliyun-qwen-text-embedding
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Aliyun Qwen Text Embedding?

Use when text embeddings are needed from Alibaba Cloud Model Studio models for semantic search, retrieval-augmented generation, clustering, or offline vector... It is an AI Agent Skill for Claude Code / OpenClaw, with 120 downloads so far.

How do I install Aliyun Qwen Text Embedding?

Run "/install aliyun-qwen-text-embedding" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Aliyun Qwen Text Embedding free?

Yes, Aliyun Qwen Text Embedding is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Aliyun Qwen Text Embedding support?

Aliyun Qwen Text Embedding is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Aliyun Qwen Text Embedding?

It is built and maintained by cinience (@cinience); the current version is v1.0.0.

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