Overview
- Skill Key
- cinience/alicloud-ai-search-opensearch
- Author
- cinience
- Source Repo
- openclaw/skills
- Version
- 1.0.0
- Source Path
- skills/cinience/alicloud-ai-search-opensearch
- Latest Commit SHA
- e0f4db948cc46fe37a553f2224146ad0814470fd
Use OpenSearch vector search edition via the Python SDK (ha3engine) to push documents and run HA/SQL searches. Ideal for RAG and vector retrieval pipelines in Claude Code/Codex.
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Status
ACTIVE
Visibility
PUBLIC
直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 alicloud-ai-search-opensearch 技能。 若已安装,则直接安装 alicloud-ai-search-opensearch 技能。
Category: provider
# OpenSearch Vector Search Edition
Use the ha3engine SDK to push documents and execute HA/SQL searches. This skill focuses on API/SDK usage only (no console steps).
## Prerequisites
- Install SDK (recommended in a venv to avoid PEP 668 limits):
```bash
python3 -m venv .venv
. .venv/bin/activate
python -m pip install alibabacloud-ha3engine
```
- Provide connection config via environment variables:
- `OPENSEARCH_ENDPOINT` (API domain)
- `OPENSEARCH_INSTANCE_ID`
- `OPENSEARCH_USERNAME`
- `OPENSEARCH_PASSWORD`
- `OPENSEARCH_DATASOURCE` (data source name)
- `OPENSEARCH_PK_FIELD` (primary key field name)
## Quickstart (push + search)
```python
import os
from alibabacloud_ha3engine import models, client
from Tea.exceptions import TeaException, RetryError
cfg = models.Config(
endpoint=os.getenv("OPENSEARCH_ENDPOINT"),
instance_id=os.getenv("OPENSEARCH_INSTANCE_ID"),
protocol="http",
access_user_name=os.getenv("OPENSEARCH_USERNAME"),
access_pass_word=os.getenv("OPENSEARCH_PASSWORD"),
)
ha3 = client.Client(cfg)
def push_docs():
data_source = os.getenv("OPENSEARCH_DATASOURCE")
pk_field = os.getenv("OPENSEARCH_PK_FIELD", "id")
documents = [
{"fields": {"id": 1, "title": "hello", "content": "world"}, "cmd": "add"},
{"fields": {"id": 2, "title": "faq", "content": "vector search"}, "cmd": "add"},
]
req = models.PushDocumentsRequestModel({}, documents)
return ha3.push_documents(data_source, pk_field, req)
def search_ha():
# HA query example. Replace cluster/table names as needed.
query_str = (
"config=hit:5,format:json,qrs_chain:search"
"&&query=title:hello"
"&&cluster=general"
)
ha_query = models.SearchQuery(query=query_str)
req = models.SearchRequestModel({}, ha_query)
return ha3.search(req)
try:
print(push_docs().body)
print(search_ha())
except (TeaException, RetryError) as e:
print(e)
```
## Script quickstart
```ba...
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