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cinience/alicloud-skills276 installs

alicloud-ai-search-opensearch

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.

How do I install this agent skill?

npx skills add https://github.com/cinience/alicloud-skills --skill alicloud-ai-search-opensearch
view source ↗

Is this agent skill safe to install?

  • Gen Agent Trust Hubpass

    The skill provides a standard integration for Alibaba Cloud OpenSearch using the official SDK. It correctly uses environment variables for credentials and configuration, following security best practices for cloud integrations. No malicious patterns or vulnerabilities were identified.

  • Socketpass

    No alerts

  • Snykpass

    Risk: LOW · No issues

  • Runlayerwarn

    3/4 files flagged

What does this agent skill do?

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):
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)

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

python skills/ai/search/alicloud-ai-search-opensearch/scripts/quickstart.py

Environment variables:

  • OPENSEARCH_ENDPOINT
  • OPENSEARCH_INSTANCE_ID
  • OPENSEARCH_USERNAME
  • OPENSEARCH_PASSWORD
  • OPENSEARCH_DATASOURCE
  • OPENSEARCH_PK_FIELD (optional, default id)
  • OPENSEARCH_CLUSTER (optional, default general)

Optional args: --cluster, --hit, --query.

SQL-style search

from alibabacloud_ha3engine import models

sql = "select * from <indexTableName>&&kvpair=trace:INFO;formatType:json"
sql_query = models.SearchQuery(sql=sql)
req = models.SearchRequestModel({}, sql_query)
resp = ha3.search(req)
print(resp)

Notes for Claude Code/Codex

  • Use push_documents for add/delete updates.
  • Large query strings (>30KB) should use the RESTful search API.
  • HA queries are fast and flexible for vector + keyword retrieval; SQL is helpful for structured data.

Error handling

  • Auth errors: verify username/password and instance access.
  • 4xx on push: check schema fields and pk_field alignment.
  • 5xx: retry with backoff.

Validation

mkdir -p output/alicloud-ai-search-opensearch
for f in skills/ai/search/alicloud-ai-search-opensearch/scripts/*.py; do
  python3 -m py_compile "$f"
done
echo "py_compile_ok" > output/alicloud-ai-search-opensearch/validate.txt

Pass criteria: command exits 0 and output/alicloud-ai-search-opensearch/validate.txt is generated.

Output And Evidence

  • Save artifacts, command outputs, and API response summaries under output/alicloud-ai-search-opensearch/.
  • Include key parameters (region/resource id/time range) in evidence files for reproducibility.

Workflow

  1. Confirm user intent, region, identifiers, and whether the operation is read-only or mutating.
  2. Run one minimal read-only query first to verify connectivity and permissions.
  3. Execute the target operation with explicit parameters and bounded scope.
  4. Verify results and save output/evidence files.

References

  • SDK package: alibabacloud-ha3engine

  • Demos: data push and HA/SQL search demos in OpenSearch docs

  • Source list: references/sources.md

Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.

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