3881c50ad5
Introduces a full test suite under the tests/ directory, including API, service, connector, and utility tests, along with fixtures and documentation. Expands Makefile with granular test commands for unit, integration, API, service, connector, coverage, and quick tests. Adds configuration files for pytest and coverage reporting, and provides a quickstart guide for testing workflow.
141 lines
4.1 KiB
Python
141 lines
4.1 KiB
Python
"""
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OpenSearch fixtures for testing.
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These fixtures provide real or test OpenSearch clients and test data.
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"""
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import pytest
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from opensearchpy import AsyncOpenSearch
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from typing import AsyncGenerator
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@pytest.fixture
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async def opensearch_client() -> AsyncGenerator[AsyncOpenSearch, None]:
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"""
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Provide a real OpenSearch client for integration tests.
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This connects to the actual OpenSearch instance running in Docker.
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"""
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client = AsyncOpenSearch(
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hosts=[{"host": "localhost", "port": 9200}],
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http_auth=("admin", "admin"),
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use_ssl=True,
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verify_certs=False,
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ssl_show_warn=False,
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)
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yield client
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await client.close()
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@pytest.fixture
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async def opensearch_test_index(opensearch_client: AsyncOpenSearch) -> AsyncGenerator[str, None]:
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"""
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Create a test index in OpenSearch and clean it up after the test.
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"""
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index_name = "test_documents"
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# Create index
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if await opensearch_client.indices.exists(index=index_name):
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await opensearch_client.indices.delete(index=index_name)
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await opensearch_client.indices.create(
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index=index_name,
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body={
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"mappings": {
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"properties": {
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"filename": {"type": "text"},
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"content": {"type": "text"},
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"embedding": {
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"type": "knn_vector",
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"dimension": 768,
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},
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"metadata": {"type": "object"},
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"created_at": {"type": "date"},
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}
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}
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},
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)
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yield index_name
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# Cleanup
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if await opensearch_client.indices.exists(index=index_name):
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await opensearch_client.indices.delete(index=index_name)
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@pytest.fixture
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async def populated_opensearch_index(
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opensearch_client: AsyncOpenSearch,
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opensearch_test_index: str,
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test_documents_batch: list,
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) -> str:
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"""
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Create and populate a test index with sample documents.
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"""
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# Index documents
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for doc in test_documents_batch:
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await opensearch_client.index(
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index=opensearch_test_index,
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id=doc["id"],
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body=doc,
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refresh=True,
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)
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return opensearch_test_index
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@pytest.fixture
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def opensearch_document_mapping() -> dict:
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"""Provide the document index mapping schema."""
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return {
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"mappings": {
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"properties": {
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"filename": {"type": "text"},
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"filepath": {"type": "keyword"},
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"content": {"type": "text"},
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"embedding": {
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"type": "knn_vector",
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"dimension": 768,
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},
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"metadata": {
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"properties": {
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"source": {"type": "keyword"},
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"uploaded_by": {"type": "keyword"},
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"file_size": {"type": "long"},
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"mime_type": {"type": "keyword"},
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"created_at": {"type": "date"},
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"updated_at": {"type": "date"},
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}
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},
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"chunks": {
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"type": "nested",
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"properties": {
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"text": {"type": "text"},
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"embedding": {
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"type": "knn_vector",
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"dimension": 768,
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},
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"chunk_index": {"type": "integer"},
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},
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},
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}
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}
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}
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@pytest.fixture
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def opensearch_knowledge_filter_mapping() -> dict:
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"""Provide the knowledge filter index mapping schema."""
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return {
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"mappings": {
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"properties": {
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"name": {"type": "text"},
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"description": {"type": "text"},
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"query": {"type": "text"},
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"document_ids": {"type": "keyword"},
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"created_by": {"type": "keyword"},
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"created_at": {"type": "date"},
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"updated_at": {"type": "date"},
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}
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}
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}
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