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# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
import pytest
from azure.core import MatchConditions
from azure.core.exceptions import HttpResponseError
from azure.core.credentials import AzureKeyCredential
from devtools_testutils import AzureRecordedTestCase, recorded_by_proxy, get_credential
from search_service_preparer import SearchEnvVarPreparer, search_decorator
from azure.search.documents.indexes.models import (
EntityLinkingSkill,
EntityRecognitionSkill,
EntityRecognitionSkillVersion,
InputFieldMappingEntry,
OutputFieldMappingEntry,
SearchIndexerSkillset,
SentimentSkill,
SentimentSkillVersion,
)
from azure.search.documents.indexes import SearchIndexerClient
class TestSearchSkillset(AzureRecordedTestCase):
@pytest.mark.skip("The skills are deprecated")
@SearchEnvVarPreparer()
@search_decorator(schema="hotel_schema.json", index_batch="hotel_small.json")
@recorded_by_proxy
def test_skillset_crud(self, endpoint):
client = SearchIndexerClient(endpoint, get_credential(), retry_backoff_factor=60)
self._test_create_skillset_validation()
self._test_create_skillset(client)
self._test_get_skillset(client)
self._test_get_skillsets(client)
self._test_create_or_update_skillset(client)
self._test_create_or_update_skillset_if_unchanged(client)
self._test_create_or_update_skillset_inplace(client)
self._test_delete_skillset_if_unchanged(client)
self._test_delete_skillset(client)
def _test_create_skillset_validation(self):
name = "test-ss-validation"
with pytest.raises(ValueError) as err:
client = SearchIndexerClient("fake_endpoint", AzureKeyCredential("fake_key"))
s1 = EntityRecognitionSkill(
inputs=[InputFieldMappingEntry(name="text", source="/document/content")],
outputs=[OutputFieldMappingEntry(name="organizations", target_name="organizationsS1")],
description="Skill Version 1",
model_version="1",
include_typeless_entities=True,
)
s2 = EntityRecognitionSkill(
inputs=[InputFieldMappingEntry(name="text", source="/document/content")],
outputs=[OutputFieldMappingEntry(name="organizations", target_name="organizationsS2")],
skill_version=EntityRecognitionSkillVersion.LATEST,
description="Skill Version 3",
model_version="3",
include_typeless_entities=True,
)
s3 = SentimentSkill(
inputs=[InputFieldMappingEntry(name="text", source="/document/content")],
outputs=[OutputFieldMappingEntry(name="score", target_name="scoreS3")],
skill_version=SentimentSkillVersion.V1,
description="Sentiment V1",
include_opinion_mining=True,
)
skillset = SearchIndexerSkillset(name=name, skills=list([s1, s2, s3]), description="desc")
client.create_skillset(skillset)
assert "include_typeless_entities" in str(err.value)
assert "model_version" in str(err.value)
assert "include_opinion_mining" in str(err.value)
def _test_create_skillset(self, client):
name = "test-ss-create"
s1 = EntityRecognitionSkill(
name="skill1",
inputs=[InputFieldMappingEntry(name="text", source="/document/content")],
outputs=[OutputFieldMappingEntry(name="organizations", target_name="organizationsS1")],
description="Skill Version 1",
include_typeless_entities=True,
)
s2 = EntityRecognitionSkill(
name="skill2",
inputs=[InputFieldMappingEntry(name="text", source="/document/content")],
outputs=[OutputFieldMappingEntry(name="organizations", target_name="organizationsS2")],
skill_version=EntityRecognitionSkillVersion.LATEST,
description="Skill Version 3",
model_version="3",
)
s3 = SentimentSkill(
name="skill3",
inputs=[InputFieldMappingEntry(name="text", source="/document/content")],
outputs=[OutputFieldMappingEntry(name="score", target_name="scoreS3")],
skill_version=SentimentSkillVersion.V1,
description="Sentiment V1",
)
s4 = SentimentSkill(
name="skill4",
inputs=[InputFieldMappingEntry(name="text", source="/document/content")],
outputs=[OutputFieldMappingEntry(name="confidenceScores", target_name="scoreS4")],
skill_version=SentimentSkillVersion.V3,
description="Sentiment V3",
include_opinion_mining=True,
)
s5 = EntityLinkingSkill(
name="skill5",
inputs=[InputFieldMappingEntry(name="text", source="/document/content")],
outputs=[OutputFieldMappingEntry(name="entities", target_name="entitiesS5")],
minimum_precision=0.5,
)
skillset = SearchIndexerSkillset(name=name, skills=list([s1, s2, s3, s4, s5]), description="desc")
dict_skills = [skill.as_dict() for skill in skillset.skills]
skillset.skills = dict_skills
result = client.create_skillset(skillset)
assert isinstance(result, SearchIndexerSkillset)
assert result.name == name
assert result.description == "desc"
assert result.e_tag
assert len(result.skills) == 5
assert isinstance(result.skills[0], EntityRecognitionSkill)
assert result.skills[0].skill_version == EntityRecognitionSkillVersion.V1
assert isinstance(result.skills[1], EntityRecognitionSkill)
assert result.skills[1].skill_version == EntityRecognitionSkillVersion.V3
assert isinstance(result.skills[2], SentimentSkill)
assert result.skills[2].skill_version == SentimentSkillVersion.V1
assert isinstance(result.skills[3], SentimentSkill)
assert result.skills[3].skill_version == SentimentSkillVersion.V3
assert isinstance(result.skills[4], EntityLinkingSkill)
assert result.skills[4].minimum_precision == 0.5
assert len(client.get_skillsets()) == 1
client.reset_skills(result, [x.name for x in result.skills])
def _test_get_skillset(self, client):
name = "test-ss-get"
s = EntityRecognitionSkill(
inputs=[InputFieldMappingEntry(name="text", source="/document/content")],
outputs=[OutputFieldMappingEntry(name="organizations", target_name="organizations")],
)
skillset = SearchIndexerSkillset(name=name, skills=list([s]), description="desc")
client.create_skillset(skillset)
result = client.get_skillset(name)
assert isinstance(result, SearchIndexerSkillset)
assert result.name == name
assert result.description == "desc"
assert result.e_tag
assert len(result.skills) == 1
assert isinstance(result.skills[0], EntityRecognitionSkill)
def _test_get_skillsets(self, client):
name1 = "test-ss-list-1"
name2 = "test-ss-list-2"
s = EntityRecognitionSkill(
inputs=[InputFieldMappingEntry(name="text", source="/document/content")],
outputs=[OutputFieldMappingEntry(name="organizations", target_name="organizations")],
)
skillset1 = SearchIndexerSkillset(name=name1, skills=list([s]), description="desc1")
client.create_skillset(skillset1)
skillset2 = SearchIndexerSkillset(name=name2, skills=list([s]), description="desc2")
client.create_skillset(skillset2)
result = client.get_skillsets()
assert isinstance(result, list)
assert all(isinstance(x, SearchIndexerSkillset) for x in result)
assert set(x.name for x in result).intersection([name1, name2]) == set([name1, name2])
def _test_create_or_update_skillset(self, client):
name = "test-ss-create-or-update"
s = EntityRecognitionSkill(
inputs=[InputFieldMappingEntry(name="text", source="/document/content")],
outputs=[OutputFieldMappingEntry(name="organizations", target_name="organizations")],
)
skillset1 = SearchIndexerSkillset(name=name, skills=list([s]), description="desc1")
client.create_or_update_skillset(skillset1)
expected_count = len(client.get_skillsets())
skillset2 = SearchIndexerSkillset(name=name, skills=list([s]), description="desc2")
client.create_or_update_skillset(skillset2)
assert len(client.get_skillsets()) == expected_count
result = client.get_skillset(name)
assert isinstance(result, SearchIndexerSkillset)
assert result.name == name
assert result.description == "desc2"
def _test_create_or_update_skillset_inplace(self, client):
name = "test-ss-create-or-update-inplace"
s = EntityRecognitionSkill(
inputs=[InputFieldMappingEntry(name="text", source="/document/content")],
outputs=[OutputFieldMappingEntry(name="organizations", target_name="organizations")],
)
skillset1 = SearchIndexerSkillset(name=name, skills=list([s]), description="desc1")
ss = client.create_or_update_skillset(skillset1)
expected_count = len(client.get_skillsets())
skillset2 = SearchIndexerSkillset(name=name, skills=[s], description="desc2", skillset=ss)
client.create_or_update_skillset(skillset2)
assert len(client.get_skillsets()) == expected_count
result = client.get_skillset(name)
assert isinstance(result, SearchIndexerSkillset)
assert result.name == name
assert result.description == "desc2"
def _test_create_or_update_skillset_if_unchanged(self, client):
name = "test-ss-create-or-update-unchanged"
s = EntityRecognitionSkill(
inputs=[InputFieldMappingEntry(name="text", source="/document/content")],
outputs=[OutputFieldMappingEntry(name="organizations", target_name="organizations")],
)
skillset1 = SearchIndexerSkillset(name=name, skills=list([s]), description="desc1")
ss = client.create_or_update_skillset(skillset1)
ss.e_tag = "changed_etag"
with pytest.raises(HttpResponseError):
client.create_or_update_skillset(ss, match_condition=MatchConditions.IfNotModified)
def _test_delete_skillset_if_unchanged(self, client):
name = "test-ss-deleted-unchanged"
s = EntityRecognitionSkill(
inputs=[InputFieldMappingEntry(name="text", source="/document/content")],
outputs=[OutputFieldMappingEntry(name="organizations", target_name="organizations")],
)
skillset = SearchIndexerSkillset(name=name, skills=list([s]), description="desc")
result = client.create_skillset(skillset)
etag = result.e_tag
skillset = SearchIndexerSkillset(name=name, skills=list([s]), description="updated")
updated = client.create_or_update_skillset(skillset)
updated.e_tag = etag
with pytest.raises(HttpResponseError):
client.delete_skillset(updated, match_condition=MatchConditions.IfNotModified)
def _test_delete_skillset(self, client):
for skillset in client.get_skillset_names():
client.delete_skillset(skillset)
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