Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Developer Tools
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.
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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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Install for OpenClaw
Quick setup
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Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, agents/openai.yaml, references/sources.md, scripts/quickstart.py
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Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.3
Provenance
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- cinience
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Documentation
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
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
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
2 Docs1 Scripts1 Config
- SKILL.md
- references/sources.md
- scripts/quickstart.py
- agents/openai.yaml