def test_create_or_update_skillset_if_unchanged(self, api_key, endpoint,
index_name, **kwargs):
client = SearchIndexerClient(endpoint, AzureKeyCredential(api_key))
s = EntityRecognitionSkill(inputs=[
InputFieldMappingEntry(name="text", source="/document/content")
],
outputs=[
OutputFieldMappingEntry(
name="organizations",
target_name="organizations")
])
ss = client.create_or_update_skillset(name='test-ss',
skills=[s],
description="desc1")
etag = ss.e_tag
client.create_or_update_skillset(name='test-ss',
skills=[s],
description="desc2",
skillset=ss)
assert len(client.get_skillsets()) == 1
ss.e_tag = etag
with pytest.raises(HttpResponseError):
client.create_or_update_skillset(
name='test-ss',
skills=[s],
skillset=ss,
match_condition=MatchConditions.IfNotModified)
def test_create_or_update_skillset_inplace(self, api_key, endpoint,
index_name, **kwargs):
client = SearchIndexerClient(endpoint, AzureKeyCredential(api_key))
s = EntityRecognitionSkill(inputs=[
InputFieldMappingEntry(name="text", source="/document/content")
],
outputs=[
OutputFieldMappingEntry(
name="organizations",
target_name="organizations")
])
ss = client.create_or_update_skillset(name='test-ss',
skills=[s],
description="desc1")
client.create_or_update_skillset(name='test-ss',
skills=[s],
description="desc2",
skillset=ss)
assert len(client.get_skillsets()) == 1
result = client.get_skillset("test-ss")
assert isinstance(result, SearchIndexerSkillset)
assert result.name == "test-ss"
assert result.description == "desc2"
def test_delete_skillset(self, api_key, endpoint, index_name, **kwargs):
client = SearchIndexerClient(endpoint, AzureKeyCredential(api_key))
s = EntityRecognitionSkill(inputs=[
InputFieldMappingEntry(name="text", source="/document/content")
],
outputs=[
OutputFieldMappingEntry(
name="organizations",
target_name="organizations")
])
result = client.create_skillset(name='test-ss',
skills=[s],
description="desc")
assert len(client.get_skillsets()) == 1
client.delete_skillset("test-ss")
assert len(client.get_skillsets()) == 0
def test_get_skillsets(self, api_key, endpoint, index_name, **kwargs):
client = SearchIndexerClient(endpoint, AzureKeyCredential(api_key))
s = EntityRecognitionSkill(inputs=[
InputFieldMappingEntry(name="text", source="/document/content")
],
outputs=[
OutputFieldMappingEntry(
name="organizations",
target_name="organizations")
])
client.create_skillset(name='test-ss-1',
skills=[s],
description="desc1")
client.create_skillset(name='test-ss-2',
skills=[s],
description="desc2")
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) == {"test-ss-1", "test-ss-2"}
def test_create_or_update_skillset_if_unchanged(self, api_key, endpoint,
index_name, **kwargs):
client = SearchIndexerClient(endpoint, AzureKeyCredential(api_key))
s = EntityRecognitionSkill(inputs=[
InputFieldMappingEntry(name="text", source="/document/content")
],
outputs=[
OutputFieldMappingEntry(
name="organizations",
target_name="organizations")
])
skillset1 = SearchIndexerSkillset(name='test-ss',
skills=list([s]),
description="desc1")
ss = client.create_or_update_skillset(skillset1)
etag = ss.e_tag
skillset2 = SearchIndexerSkillset(name='test-ss',
skills=[s],
description="desc2",
skillset=ss)
client.create_or_update_skillset(skillset2)
assert len(client.get_skillsets()) == 1
def test_create_skillset(self, api_key, endpoint, index_name, **kwargs):
client = SearchIndexerClient(endpoint, AzureKeyCredential(api_key))
name = "test-ss"
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 == "test-ss"
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])
