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])
async def test_create_skillset(self, api_key, endpoint, index_name, **kwargs):
client = SearchIndexerClient(endpoint, AzureKeyCredential(api_key))
name = "test-ss"
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)
s4 = SentimentSkill(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(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")
result = await 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(await client.get_skillsets()) == 1
async 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 = await client.create_skillset(skillset)
etag = result.e_tag
skillset1 = SearchIndexerSkillset(name=name,
skills=list([s]),
description="updated")
updated = await client.create_or_update_skillset(skillset1)
updated.e_tag = etag
with pytest.raises(HttpResponseError):
await client.delete_skillset(
updated, match_condition=MatchConditions.IfNotModified)
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)
async def test_delete_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")
])
skillset = SearchIndexerSkillset(name='test-ss',
skills=list([s]),
description="desc")
result = await client.create_skillset(skillset)
etag = result.e_tag
skillset1 = SearchIndexerSkillset(name='test-ss',
skills=list([s]),
description="updated")
updated = await client.create_or_update_skillset(skillset1)
updated.e_tag = etag
with pytest.raises(HttpResponseError):
await client.delete_skillset(
updated, 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"
async 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 = await client.create_or_update_skillset(skillset1)
expected_count = len(await client.get_skillsets())
skillset2 = SearchIndexerSkillset(name=name,
skills=[s],
description="desc2",
skillset=ss)
await client.create_or_update_skillset(skillset2)
assert len(await client.get_skillsets()) == expected_count
result = await client.get_skillset(name)
assert isinstance(result, SearchIndexerSkillset)
assert result.name == name
assert result.description == "desc2"
async def test_create_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")
])
skillset = SearchIndexerSkillset(name='test-ss',
skills=list([s]),
description="desc")
result = await 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) == 1
assert isinstance(result.skills[0], EntityRecognitionSkill)
assert len(await client.get_skillsets()) == 1
async 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")
await client.create_skillset(skillset1)
skillset2 = SearchIndexerSkillset(name=name2,
skills=list([s]),
description="desc2")
await client.create_skillset(skillset2)
result = await 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 _create_skillset():
client = SearchIndexerClient(service_endpoint, AzureKeyCredential(key))
inp = InputFieldMappingEntry(name="text", source="/document/lastRenovationDate")
output = OutputFieldMappingEntry(name="dateTimes", target_name="RenovatedDate")
s = EntityRecognitionSkill(name="merge-skill", inputs=[inp], outputs=[output])
skillset = SearchIndexerSkillset(name='hotel-data-skill', skills=[s], description="example skillset")
result = client.create_skillset(skillset)
return result
async 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")])
await client.create_skillset(name='test-ss-1', skills=[s], description="desc1")
await client.create_skillset(name='test-ss-2', skills=[s], description="desc2")
result = await 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"}
async 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 = await client.create_skillset(name='test-ss', skills=[s], description="desc")
assert len(await client.get_skillsets()) == 1
await client.delete_skillset("test-ss")
if self.is_live:
time.sleep(TIME_TO_SLEEP)
assert len(await client.get_skillsets()) == 0
async 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 = await client.create_or_update_skillset(skillset1)
etag = ss.e_tag
skillset2 = SearchIndexerSkillset(name='test-ss', skills=[s], description="desc2", skillset=ss)
await client.create_or_update_skillset(skillset2)
assert len(await client.get_skillsets()) == 1
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)
etag = ss.e_tag
updated = SearchIndexerSkillset(name=name, skills=[s], description="desc2", skillset=ss)
updated.e_tag = etag
with pytest.raises(HttpResponseError):
client.create_or_update_skillset(updated, match_condition=MatchConditions.IfNotModified)
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_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")
])
skillset = SearchIndexerSkillset(name='test-ss',
skills=list([s]),
description="desc")
result = client.create_skillset(skillset)
assert len(client.get_skillsets()) == 1
client.delete_skillset("test-ss")
assert len(client.get_skillsets()) == 0
