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 &&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 Confirm user intent, region, identifiers, and whether the operation is read-only or mutating. Run one minimal read-only query first to verify connectivity and permissions. Execute the target operation with explicit parameters and bounded scope. 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