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Python: Allow AzureOpenAIResponsesClient creation with Foundry project endpoint (#3814)

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* Initial plan

* feat: extend AzureOpenAIResponsesClient to support Foundry project endpoints

Add project_client and project_endpoint parameters to allow creating
the client via an Azure AI Foundry project. When provided, the client
uses AIProjectClient.get_openai_client() to obtain the OpenAI client.
The azure-ai-projects package is imported lazily and only required
when using the project endpoint path.

Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com>

* fix: address code review - remove duplicate MagicMock imports in tests

Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com>

* fix: add type field to Responses API input items and add Foundry sample

- Add 'type: message' to input items in _prepare_message_for_openai
  to comply with the Responses API schema requirement
- Filter out empty dicts from unsupported content types to prevent
  sending items with invalid empty type values
- Add azure_responses_client_with_foundry.py sample demonstrating
  AzureOpenAIResponsesClient with project_endpoint
- Update README and pyrightconfig.samples.json accordingly

* updates to response format and setup

* fix: patch AIProjectClient at correct module path in test

Patch agent_framework.azure._responses_client.AIProjectClient instead of
azure.ai.projects.aio.AIProjectClient since the import is at module level.

* docs: add Foundry sample to READMEs and document AZURE_AI_PROJECT_ENDPOINT env var

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com>
Co-authored-by: eavanvalkenburg <github@vanvalkenburg.eu>
This commit is contained in:
Copilot
2026-02-11 16:46:25 +01:00
committed by GitHub
Unverified
parent 235c578059
commit a427af91a9
12 changed files with 349 additions and 28 deletions
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python/packages/core/agent_framework/azure/_responses_client.py
+93 -5
View File
@@ -7,11 +7,14 @@ from collections.abc import Mapping, Sequence
from typing import TYPE_CHECKING, Any, Generic
from urllib.parse import urljoin
from azure.ai.projects.aio import AIProjectClient
from azure.core.credentials import TokenCredential
from openai.lib.azure import AsyncAzureADTokenProvider, AsyncAzureOpenAI
from openai import AsyncOpenAI
from openai.lib.azure import AsyncAzureADTokenProvider
from pydantic import ValidationError
from .._middleware import ChatMiddlewareLayer
from .._telemetry import AGENT_FRAMEWORK_USER_AGENT
from .._tools import FunctionInvocationConfiguration, FunctionInvocationLayer
from ..exceptions import ServiceInitializationError
from ..observability import ChatTelemetryLayer
@@ -72,7 +75,9 @@ class AzureOpenAIResponsesClient( # type: ignore[misc]
token_endpoint: str | None = None,
credential: TokenCredential | None = None,
default_headers: Mapping[str, str] | None = None,
async_client: AsyncAzureOpenAI | None = None,
async_client: AsyncOpenAI | None = None,
project_client: Any | None = None,
project_endpoint: str | None = None,
env_file_path: str | None = None,
env_file_encoding: str | None = None,
instruction_role: str | None = None,
@@ -82,6 +87,14 @@ class AzureOpenAIResponsesClient( # type: ignore[misc]
) -> None:
"""Initialize an Azure OpenAI Responses client.
The client can be created in two ways:
1. **Direct Azure OpenAI** (default): Provide endpoint, api_key, or credential
to connect directly to an Azure OpenAI deployment.
2. **Foundry project endpoint**: Provide a ``project_client`` or ``project_endpoint``
(with ``credential``) to create the client via an Azure AI Foundry project.
This requires the ``azure-ai-projects`` package to be installed.
Keyword Args:
api_key: The API key. If provided, will override the value in the env vars or .env file.
Can also be set via environment variable AZURE_OPENAI_API_KEY.
@@ -105,6 +118,12 @@ class AzureOpenAIResponsesClient( # type: ignore[misc]
default_headers: The default headers mapping of string keys to
string values for HTTP requests.
async_client: An existing client to use.
project_client: An existing ``AIProjectClient`` (from ``azure.ai.projects.aio``) to use.
The OpenAI client will be obtained via ``project_client.get_openai_client()``.
Requires the ``azure-ai-projects`` package.
project_endpoint: The Azure AI Foundry project endpoint URL.
When provided with ``credential``, an ``AIProjectClient`` will be created
and used to obtain the OpenAI client. Requires the ``azure-ai-projects`` package.
env_file_path: Use the environment settings file as a fallback to using env vars.
env_file_encoding: The encoding of the environment settings file, defaults to 'utf-8'.
instruction_role: The role to use for 'instruction' messages, for example, summarization
@@ -132,6 +151,27 @@ class AzureOpenAIResponsesClient( # type: ignore[misc]
# Or loading from a .env file
client = AzureOpenAIResponsesClient(env_file_path="path/to/.env")
# Using a Foundry project endpoint
from azure.identity import DefaultAzureCredential
client = AzureOpenAIResponsesClient(
project_endpoint="https://your-project.services.ai.azure.com",
deployment_name="gpt-4o",
credential=DefaultAzureCredential(),
)
# Or using an existing AIProjectClient
from azure.ai.projects.aio import AIProjectClient
project_client = AIProjectClient(
endpoint="https://your-project.services.ai.azure.com",
credential=DefaultAzureCredential(),
)
client = AzureOpenAIResponsesClient(
project_client=project_client,
deployment_name="gpt-4o",
)
# Using custom ChatOptions with type safety:
from typing import TypedDict
from agent_framework.azure import AzureOpenAIResponsesOptions
@@ -146,6 +186,15 @@ class AzureOpenAIResponsesClient( # type: ignore[misc]
"""
if model_id := kwargs.pop("model_id", None) and not deployment_name:
deployment_name = str(model_id)
# Project client path: create OpenAI client from an Azure AI Foundry project
if async_client is None and (project_client is not None or project_endpoint is not None):
async_client = self._create_client_from_project(
project_client=project_client,
project_endpoint=project_endpoint,
credential=credential,
)
try:
azure_openai_settings = AzureOpenAISettings(
# pydantic settings will see if there is a value, if not, will try the env var or .env file
@@ -195,9 +244,48 @@ class AzureOpenAIResponsesClient( # type: ignore[misc]
function_invocation_configuration=function_invocation_configuration,
)
@staticmethod
def _create_client_from_project(
*,
project_client: AIProjectClient | None,
project_endpoint: str | None,
credential: TokenCredential | None,
) -> AsyncOpenAI:
"""Create an AsyncOpenAI client from an Azure AI Foundry project.
Args:
project_client: An existing AIProjectClient to use.
project_endpoint: The Azure AI Foundry project endpoint URL.
credential: Azure credential for authentication.
Returns:
An AsyncAzureOpenAI client obtained from the project client.
Raises:
ServiceInitializationError: If required parameters are missing or
the azure-ai-projects package is not installed.
"""
if project_client is not None:
return project_client.get_openai_client()
if not project_endpoint:
raise ServiceInitializationError(
"Azure AI project endpoint is required when project_client is not provided."
)
if not credential:
raise ServiceInitializationError(
"Azure credential is required when using project_endpoint without a project_client."
)
project_client = AIProjectClient(
endpoint=project_endpoint,
credential=credential, # type: ignore[arg-type]
user_agent=AGENT_FRAMEWORK_USER_AGENT,
)
return project_client.get_openai_client()
@override
def _check_model_presence(self, run_options: dict[str, Any]) -> None:
if not run_options.get("model"):
def _check_model_presence(self, options: dict[str, Any]) -> None:
if not options.get("model"):
if not self.model_id:
raise ValueError("deployment_name must be a non-empty string")
run_options["model"] = self.model_id
options["model"] = self.model_id
python/packages/core/agent_framework/azure/_shared.py
+2 -1
View File
@@ -9,6 +9,7 @@ from copy import copy
from typing import Any, ClassVar, Final
from azure.core.credentials import TokenCredential
from openai import AsyncOpenAI
from openai.lib.azure import AsyncAzureOpenAI
from pydantic import SecretStr, model_validator
@@ -162,7 +163,7 @@ class AzureOpenAIConfigMixin(OpenAIBase):
token_endpoint: str | None = None,
credential: TokenCredential | None = None,
default_headers: Mapping[str, str] | None = None,
client: AsyncAzureOpenAI | None = None,
client: AsyncOpenAI | None = None,
instruction_role: str | None = None,
**kwargs: Any,
) -> None:
python/packages/core/agent_framework/openai/_responses_client.py
+13 -6
View File
@@ -901,6 +901,7 @@ class RawOpenAIResponsesClient( # type: ignore[misc]
"""Prepare a chat message for the OpenAI Responses API format."""
all_messages: list[dict[str, Any]] = []
args: dict[str, Any] = {
"type": "message",
"role": message.role,
}
for content in message.contents:
@@ -911,16 +912,22 @@ class RawOpenAIResponsesClient( # type: ignore[misc]
case "function_result":
new_args: dict[str, Any] = {}
new_args.update(self._prepare_content_for_openai(message.role, content, call_id_to_id)) # type: ignore[arg-type]
all_messages.append(new_args)
if new_args:
all_messages.append(new_args)
case "function_call":
function_call = self._prepare_content_for_openai(message.role, content, call_id_to_id) # type: ignore[arg-type]
all_messages.append(function_call) # type: ignore
if function_call:
all_messages.append(function_call) # type: ignore
case "function_approval_response" | "function_approval_request":
all_messages.append(self._prepare_content_for_openai(message.role, content, call_id_to_id)) # type: ignore
prepared = self._prepare_content_for_openai(Role(message.role), content, call_id_to_id)
if prepared:
all_messages.append(prepared) # type: ignore
case _:
if "content" not in args:
args["content"] = []
args["content"].append(self._prepare_content_for_openai(message.role, content, call_id_to_id)) # type: ignore
prepared_content = self._prepare_content_for_openai(message.role, content, call_id_to_id) # type: ignore
if prepared_content:
if "content" not in args:
args["content"] = []
args["content"].append(prepared_content) # type: ignore
if "content" in args or "tool_calls" in args:
all_messages.append(args)
return all_messages
python/packages/core/pyproject.toml
+1
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@@ -34,6 +34,7 @@ dependencies = [
# connectors and functions
"openai>=1.99.0",
"azure-identity>=1,<2",
"azure-ai-projects >= 2.0.0b3",
"mcp[ws]>=1.24.0,<2",
"packaging>=24.1",
]
python/packages/core/tests/azure/test_azure_responses_client.py
+114
View File
@@ -3,6 +3,7 @@
import json
import os
from typing import Annotated, Any
from unittest.mock import MagicMock
import pytest
from azure.identity import AzureCliCredential
@@ -115,6 +116,119 @@ def test_init_with_empty_model_id(azure_openai_unit_test_env: dict[str, str]) ->
)
def test_init_with_project_client(azure_openai_unit_test_env: dict[str, str]) -> None:
"""Test initialization with an existing AIProjectClient."""
from unittest.mock import patch
from openai import AsyncOpenAI
# Create a mock AIProjectClient that returns a mock AsyncOpenAI client
mock_openai_client = MagicMock(spec=AsyncOpenAI)
mock_openai_client.default_headers = {}
mock_project_client = MagicMock()
mock_project_client.get_openai_client.return_value = mock_openai_client
with patch(
"agent_framework.azure._responses_client.AzureOpenAIResponsesClient._create_client_from_project",
return_value=mock_openai_client,
):
azure_responses_client = AzureOpenAIResponsesClient(
project_client=mock_project_client,
deployment_name="gpt-4o",
)
assert azure_responses_client.model_id == "gpt-4o"
assert azure_responses_client.client is mock_openai_client
assert isinstance(azure_responses_client, SupportsChatGetResponse)
def test_init_with_project_endpoint(azure_openai_unit_test_env: dict[str, str]) -> None:
"""Test initialization with a project endpoint and credential."""
from unittest.mock import patch
from openai import AsyncOpenAI
mock_openai_client = MagicMock(spec=AsyncOpenAI)
mock_openai_client.default_headers = {}
with patch(
"agent_framework.azure._responses_client.AzureOpenAIResponsesClient._create_client_from_project",
return_value=mock_openai_client,
):
azure_responses_client = AzureOpenAIResponsesClient(
project_endpoint="https://test-project.services.ai.azure.com",
deployment_name="gpt-4o",
credential=AzureCliCredential(),
)
assert azure_responses_client.model_id == "gpt-4o"
assert azure_responses_client.client is mock_openai_client
assert isinstance(azure_responses_client, SupportsChatGetResponse)
def test_create_client_from_project_with_project_client() -> None:
"""Test _create_client_from_project with an existing project client."""
from openai import AsyncOpenAI
mock_openai_client = MagicMock(spec=AsyncOpenAI)
mock_project_client = MagicMock()
mock_project_client.get_openai_client.return_value = mock_openai_client
result = AzureOpenAIResponsesClient._create_client_from_project(
project_client=mock_project_client,
project_endpoint=None,
credential=None,
)
assert result is mock_openai_client
mock_project_client.get_openai_client.assert_called_once()
def test_create_client_from_project_with_endpoint() -> None:
"""Test _create_client_from_project with a project endpoint."""
from unittest.mock import patch
from openai import AsyncOpenAI
mock_openai_client = MagicMock(spec=AsyncOpenAI)
mock_credential = MagicMock()
with patch("agent_framework.azure._responses_client.AIProjectClient") as MockAIProjectClient:
mock_instance = MockAIProjectClient.return_value
mock_instance.get_openai_client.return_value = mock_openai_client
result = AzureOpenAIResponsesClient._create_client_from_project(
project_client=None,
project_endpoint="https://test-project.services.ai.azure.com",
credential=mock_credential,
)
assert result is mock_openai_client
MockAIProjectClient.assert_called_once()
mock_instance.get_openai_client.assert_called_once()
def test_create_client_from_project_missing_endpoint() -> None:
"""Test _create_client_from_project raises error when endpoint is missing."""
with pytest.raises(ServiceInitializationError, match="project endpoint is required"):
AzureOpenAIResponsesClient._create_client_from_project(
project_client=None,
project_endpoint=None,
credential=MagicMock(),
)
def test_create_client_from_project_missing_credential() -> None:
"""Test _create_client_from_project raises error when credential is missing."""
with pytest.raises(ServiceInitializationError, match="credential is required"):
AzureOpenAIResponsesClient._create_client_from_project(
project_client=None,
project_endpoint="https://test-project.services.ai.azure.com",
credential=None,
)
def test_serialize(azure_openai_unit_test_env: dict[str, str]) -> None:
default_headers = {"X-Unit-Test": "test-guid"}
python/packages/core/tests/openai/test_openai_responses_client.py
+4 -12
View File
@@ -798,12 +798,8 @@ def test_chat_message_with_error_content() -> None:
result = client._prepare_message_for_openai(message, call_id_to_id)
# Message should be prepared with empty content list since ErrorContent returns {}
assert len(result) == 1
prepared_message = result[0]
assert prepared_message["role"] == "assistant"
# Content should be a list with empty dict since ErrorContent returns {}
assert prepared_message.get("content") == [{}]
# Message should be empty since ErrorContent is filtered out
assert len(result) == 0
def test_chat_message_with_usage_content() -> None:
@@ -823,12 +819,8 @@ def test_chat_message_with_usage_content() -> None:
result = client._prepare_message_for_openai(message, call_id_to_id)
# Message should be prepared with empty content list since UsageContent returns {}
assert len(result) == 1
prepared_message = result[0]
assert prepared_message["role"] == "assistant"
# Content should be a list with empty dict since UsageContent returns {}
assert prepared_message.get("content") == [{}]
# Message should be empty since UsageContent is filtered out
assert len(result) == 0
def test_hosted_file_content_preparation() -> None: