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alicloud-ai-search-opensearch

alicloud-ai-search-opensearch

github.com/cinienceData & databases396276 installsUpdated 11w ago
Repository

About alicloud-ai-search-opensearch

A skill for developers using Alibaba Cloud OpenSearch Vector Search Edition. It covers document updates and HA/SQL searches through the ha3engine SDK, without console instructions.

Key features

  1. 01Push and delete documents through the SDK
  2. 02Run HA vector and keyword searches
  3. 03Query structured data with SQL
  4. 04提供脚本快速启动示例

Use cases

  1. 01Write documents to an OpenSearch data source
  2. 02Check vector and keyword search results
  3. 03Search structured data

Install

Copy the command and run it in a terminal.

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

After installing, type/alicloud-ai-search-opensearchin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

agents/
openai.yaml
references/
sources.md
scripts/
quickstart.py

Details

From the project README

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

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