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# ------------------------------------
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# ------------------------------------
import json
import azure.ai.inference as sdk
import azure.ai.inference.aio as async_sdk
from model_inference_test_base import (
ModelClientTestBase,
ServicePreparerImageEmbeddings,
)
from devtools_testutils.aio import recorded_by_proxy_async
from azure.core.exceptions import ServiceRequestError
from azure.core.credentials import AzureKeyCredential
# The test class name needs to start with "Test" to get collected by pytest
class TestImageEmbeddingsClientAsync(ModelClientTestBase):
# **********************************************************************************
#
# IMAGE EMBEDDINGS REGRESSION TESTS - NO SERVICE RESPONSE REQUIRED
#
# **********************************************************************************
# Regression test. Send a request that includes all supported types of input objects. Make sure the resulting
# JSON payload that goes up to the service (including headers) is the correct one after hand-inspection.
@ServicePreparerImageEmbeddings() # Not sure why this is needed. It errors out if not present. We don't use the env variables in this test.
async def test_async_image_embeddings_request_payload(self, **kwargs):
client = async_sdk.ImageEmbeddingsClient(
endpoint="http://does.not.exist",
credential=AzureKeyCredential("key-value"),
headers={"some_header": "some_header_value"},
user_agent="MyAppId",
)
image_embedding_input = ModelClientTestBase._get_image_embeddings_input()
for _ in range(2):
try:
_ = await client.embed(
input=[image_embedding_input],
dimensions=2048,
encoding_format=sdk.models.EmbeddingEncodingFormat.UBINARY,
input_type=sdk.models.EmbeddingInputType.QUERY,
model_extras={
"key1": 1,
"key2": True,
"key3": "Some value",
"key4": [1, 2, 3],
"key5": {"key6": 2, "key7": False, "key8": "Some other value", "key9": [4, 5, 6, 7]},
},
model="some-model-id",
raw_request_hook=self.request_callback,
)
await client.close()
assert False
except ServiceRequestError as _:
# The test should throw this exception!
self._validate_image_embeddings_json_request_payload()
continue
await client.close()
# Regression test. Send a request that includes all supported types of input objects, with embedding settings
# specified in the constructor. Make sure the resulting JSON payload that goes up to the service
# is the correct one after hand-inspection.
@ServicePreparerImageEmbeddings() # Not sure why this is needed. It errors out if not present. We don't use the env variables in this test.
async def test_async_image_embeddings_request_payload_with_defaults(self, **kwargs):
client = async_sdk.ImageEmbeddingsClient(
endpoint="http://does.not.exist",
credential=AzureKeyCredential("key-value"),
headers={"some_header": "some_header_value"},
user_agent="MyAppId",
dimensions=2048,
encoding_format=sdk.models.EmbeddingEncodingFormat.UBINARY,
input_type=sdk.models.EmbeddingInputType.QUERY,
model_extras={
"key1": 1,
"key2": True,
"key3": "Some value",
"key4": [1, 2, 3],
"key5": {"key6": 2, "key7": False, "key8": "Some other value", "key9": [4, 5, 6, 7]},
},
model="some-model-id",
)
image_embedding_input = ModelClientTestBase._get_image_embeddings_input()
for _ in range(2):
try:
_ = await client.embed(input=[image_embedding_input], raw_request_hook=self.request_callback)
await client.close()
assert False
except ServiceRequestError as _:
# The test should throw this exception!
self._validate_image_embeddings_json_request_payload()
continue
await client.close()
# Regression test. Send a request that includes all supported types of input objects, with embeddings settings
# specified in the constructor and all of them overwritten in the 'embed' call.
# Make sure the resulting JSON payload that goes up to the service is the correct one after hand-inspection.
@ServicePreparerImageEmbeddings() # Not sure why this is needed. It errors out if not present. We don't use the env variables in this test.
async def test_async_image_embeddings_request_payload_with_defaults_and_overrides(self, **kwargs):
client = async_sdk.ImageEmbeddingsClient(
endpoint="http://does.not.exist",
credential=AzureKeyCredential("key-value"),
headers={"some_header": "some_header_value"},
user_agent="MyAppId",
dimensions=1024,
encoding_format=sdk.models.EmbeddingEncodingFormat.UINT8,
input_type=sdk.models.EmbeddingInputType.DOCUMENT,
model_extras={
"hey1": 2,
"key2": False,
"key3": "Some other value",
"key9": "Yet another value",
},
model="some-other-model-id",
)
image_embedding_input = ModelClientTestBase._get_image_embeddings_input()
for _ in range(2):
try:
_ = await client.embed(
input=[image_embedding_input],
dimensions=2048,
encoding_format=sdk.models.EmbeddingEncodingFormat.UBINARY,
input_type=sdk.models.EmbeddingInputType.QUERY,
model_extras={
"key1": 1,
"key2": True,
"key3": "Some value",
"key4": [1, 2, 3],
"key5": {"key6": 2, "key7": False, "key8": "Some other value", "key9": [4, 5, 6, 7]},
},
model="some-model-id",
raw_request_hook=self.request_callback,
)
await client.close()
assert False
except ServiceRequestError as _:
# The test should throw this exception!
self._validate_image_embeddings_json_request_payload()
continue
await client.close()
# **********************************************************************************
#
# HAPPY PATH SERVICE TESTS - IMAGE EMBEDDINGS
#
# **********************************************************************************
# TODO: At the moment the /info route shows "model_type": "embedding", so load_client
# will return an EmbeddingsClient instead of ImageEmbeddingsClient. How can we resolve this?
# This Cohere model (cohere-embed-v2-english) supports both text embeddings and image embeddings.
@ServicePreparerImageEmbeddings()
@recorded_by_proxy_async
async def test_async_load_image_embeddings_client(self, **kwargs):
client = await self._load_async_image_embeddings_client(**kwargs)
assert isinstance(client, async_sdk.EmbeddingsClient)
assert client._model_info
response1 = await client.get_model_info()
self._print_model_info_result(response1)
self._validate_model_info_result(response1, "embedding") # TODO: What should this be?
await client.close()
# TODO: At the moment the /info route shows "model_type": "embedding", so load_client
# will return an EmbeddingsClient instead of ImageEmbeddingsClient. How can we resolve this?
# This Cohere model (cohere-embed-v2-english) supports both text embeddings and image embeddings.
@ServicePreparerImageEmbeddings()
@recorded_by_proxy_async
async def test_async_get_model_info_on_image_embeddings_client(self, **kwargs):
client = self._create_async_image_embeddings_client(**kwargs)
assert not client._model_info # pylint: disable=protected-access
response1 = await client.get_model_info()
assert client._model_info # pylint: disable=protected-access
self._print_model_info_result(response1)
self._validate_model_info_result(response1, "embedding") # TODO: what should this be?
# Get the model info again. No network calls should be made here,
# as the response is cached in the client.
response2 = await client.get_model_info()
self._print_model_info_result(response2)
assert response1 == response2
await client.close()
@ServicePreparerImageEmbeddings()
@recorded_by_proxy_async
async def test_async_image_embeddings_with_entra_id_auth(self, **kwargs):
client = self._create_async_image_embeddings_client(key_auth=False, **kwargs)
image_embedding_input = ModelClientTestBase._get_image_embeddings_input(False)
# Request image embeddings with default service format (list of floats)
response1 = await client.embed(input=[image_embedding_input])
self._print_embeddings_result(response1)
self._validate_image_embeddings_result(response1)
assert json.dumps(response1.as_dict(), indent=2) == response1.__str__()
await client.close()
@ServicePreparerImageEmbeddings()
@recorded_by_proxy_async
async def test_async_image_embeddings(self, **kwargs):
async with self._create_async_image_embeddings_client(**kwargs) as client:
image_embedding_input = ModelClientTestBase._get_image_embeddings_input(False)
# Request image embeddings with default service format (list of floats)
response1 = await client.embed(input=[image_embedding_input])
self._print_embeddings_result(response1)
self._validate_image_embeddings_result(response1)
assert json.dumps(response1.as_dict(), indent=2) == response1.__str__()
# Request embeddings as base64 encoded strings
response2 = await client.embed(
input=[image_embedding_input], encoding_format=sdk.models.EmbeddingEncodingFormat.BASE64
)
self._print_embeddings_result(response2, sdk.models.EmbeddingEncodingFormat.BASE64)
self._validate_image_embeddings_result(response2, sdk.models.EmbeddingEncodingFormat.BASE64)
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