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Python: Upgraded azure-ai-projects to 2.0.0b4 (#4438)

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* Upgraded azure-ai-projects to 2.0.0b4

* Fixed tests
This commit is contained in:
Dmytro Struk
2026-03-03 16:11:41 -08:00
committed by GitHub
Unverified
parent 5ba1c6f0cc
commit b5edb529b7
12 changed files with 120 additions and 105 deletions
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python/packages/azure-ai/agent_framework_azure_ai/_client.py
+20 -11
View File
@@ -37,12 +37,13 @@ from agent_framework.openai._responses_client import RawOpenAIResponsesClient
from azure.ai.projects.aio import AIProjectClient
from azure.ai.projects.models import (
ApproximateLocation,
CodeInterpreterContainerAuto,
CodeInterpreterTool,
CodeInterpreterToolAuto,
FoundryFeaturesOptInKeys,
ImageGenTool,
MCPTool,
PromptAgentDefinition,
PromptAgentDefinitionText,
PromptAgentDefinitionTextOptions,
RaiConfig,
Reasoning,
WebSearchPreviewTool,
@@ -78,6 +79,9 @@ class AzureAIProjectAgentOptions(OpenAIResponsesOptions, total=False):
reasoning: Reasoning # type: ignore[misc]
"""Configuration for enabling reasoning capabilities (requires azure.ai.projects.models.Reasoning)."""
foundry_features: FoundryFeaturesOptInKeys | str
"""Optional Foundry preview feature opt-in for agent version creation."""
AzureAIClientOptionsT = TypeVar(
"AzureAIClientOptionsT",
@@ -392,7 +396,7 @@ class RawAzureAIClient(RawOpenAIResponsesClient[AzureAIClientOptionsT], Generic[
# response_format is accessed from chat_options or additional_properties
# since the base class excludes it from run_options
if chat_options and (response_format := chat_options.get("response_format")):
args["text"] = PromptAgentDefinitionText(format=create_text_format_config(response_format))
args["text"] = PromptAgentDefinitionTextOptions(format=create_text_format_config(response_format))
# Combine instructions from messages and options
# instructions is accessed from chat_options since the base class excludes it from run_options
@@ -404,11 +408,15 @@ class RawAzureAIClient(RawOpenAIResponsesClient[AzureAIClientOptionsT], Generic[
if combined_instructions:
args["instructions"] = "".join(combined_instructions)
created_agent = await self.project_client.agents.create_version(
agent_name=self.agent_name,
definition=PromptAgentDefinition(**args),
description=self.agent_description,
)
create_version_kwargs: dict[str, Any] = {
"agent_name": self.agent_name,
"definition": PromptAgentDefinition(**args),
"description": self.agent_description,
}
if foundry_features := run_options.get("foundry_features"):
create_version_kwargs["foundry_features"] = foundry_features
created_agent = await self.project_client.agents.create_version(**create_version_kwargs)
self.agent_version = created_agent.version
self.warn_runtime_tools_and_structure_changed = True
@@ -500,6 +508,7 @@ class RawAzureAIClient(RawOpenAIResponsesClient[AzureAIClientOptionsT], Generic[
"temperature": ("temperature",),
"top_p": ("top_p",),
"reasoning": ("reasoning",),
"foundry_features": ("foundry_features",),
}
for run_keys in agent_level_option_to_run_keys.values():
@@ -526,9 +535,9 @@ class RawAzureAIClient(RawOpenAIResponsesClient[AzureAIClientOptionsT], Generic[
run_options["input"] = self._transform_input_for_azure_ai(cast(list[dict[str, Any]], run_options["input"]))
if not self._is_application_endpoint:
# Application-scoped response APIs do not support "agent" property.
# Application-scoped response APIs do not support "agent_reference" property.
agent_reference = await self._get_agent_reference_or_create(run_options, instructions, options)
run_options["extra_body"] = {"agent": agent_reference}
run_options["extra_body"] = {"agent_reference": agent_reference}
# Remove only keys that map to this client's declared options TypedDict.
self._remove_agent_level_run_options(run_options, options)
@@ -922,7 +931,7 @@ class RawAzureAIClient(RawOpenAIResponsesClient[AzureAIClientOptionsT], Generic[
if file_ids is None and isinstance(container, dict):
file_ids = container.get("file_ids")
resolved = resolve_file_ids(file_ids)
tool_container = CodeInterpreterToolAuto(file_ids=resolved)
tool_container = CodeInterpreterContainerAuto(file_ids=resolved)
return CodeInterpreterTool(container=tool_container, **kwargs)
@staticmethod
python/packages/azure-ai/agent_framework_azure_ai/_foundry_memory_provider.py
+10 -11
View File
@@ -18,7 +18,6 @@ from agent_framework._sessions import AgentSession, BaseContextProvider, Session
from agent_framework._settings import load_settings
from agent_framework.azure._entra_id_authentication import AzureCredentialTypes
from azure.ai.projects.aio import AIProjectClient
from azure.ai.projects.models import ItemParam, ResponsesAssistantMessageItemParam, ResponsesUserMessageItemParam
from ._shared import AzureAISettings
@@ -149,7 +148,7 @@ class FoundryMemoryProvider(BaseContextProvider):
# On first run, retrieve static memories (user profile memories)
if not state.get("initialized"):
try:
static_search_result = await self.project_client.memory_stores.search_memories(
static_search_result = await self.project_client.beta.memory_stores.search_memories(
name=self.memory_store_name,
scope=self.scope or context.session_id, # type: ignore[arg-type]
)
@@ -169,15 +168,15 @@ class FoundryMemoryProvider(BaseContextProvider):
if not has_input:
return
# Convert input messages to ItemParam format for search
# Convert input messages to memory search item format
items = [
ItemParam({"type": "text", "text": msg.text})
{"type": "text", "text": msg.text}
for msg in context.input_messages
if msg and msg.text and msg.text.strip()
]
try:
search_result = await self.project_client.memory_stores.search_memories(
search_result = await self.project_client.beta.memory_stores.search_memories(
name=self.memory_store_name,
scope=self.scope or context.session_id, # type: ignore[arg-type]
items=items,
@@ -224,24 +223,24 @@ class FoundryMemoryProvider(BaseContextProvider):
if context.response and context.response.messages:
messages_to_store.extend(context.response.messages)
# Filter and convert messages to ItemParam format
items: list[ResponsesUserMessageItemParam | ResponsesAssistantMessageItemParam] = []
# Filter and convert messages to memory update item format
items: list[dict[str, str]] = []
for message in messages_to_store:
if message.role in {"user", "assistant", "system"} and message.text and message.text.strip():
if message.role == "user":
items.append(ResponsesUserMessageItemParam(content=message.text))
items.append({"role": "user", "type": "message", "content": message.text})
elif message.role == "assistant":
items.append(ResponsesAssistantMessageItemParam(content=message.text))
items.append({"role": "assistant", "type": "message", "content": message.text})
if not items:
return
try:
# Fire and forget - don't wait for the update to complete
update_poller = await self.project_client.memory_stores.begin_update_memories(
update_poller = await self.project_client.beta.memory_stores.begin_update_memories(
name=self.memory_store_name,
scope=self.scope or context.session_id, # type: ignore[arg-type]
items=items, # type: ignore[arg-type]
items=items,
previous_update_id=state.get("previous_update_id"),
update_delay=self.update_delay,
)
python/packages/azure-ai/agent_framework_azure_ai/_project_provider.py
+21 -14
View File
@@ -4,7 +4,7 @@ from __future__ import annotations
import logging
import sys
from collections.abc import Callable, MutableMapping, Sequence
from collections.abc import Callable, Mapping, MutableMapping, Sequence
from typing import Any, Generic
from agent_framework import (
@@ -21,10 +21,9 @@ from agent_framework._tools import ToolTypes
from agent_framework.azure._entra_id_authentication import AzureCredentialTypes
from azure.ai.projects.aio import AIProjectClient
from azure.ai.projects.models import (
AgentReference,
AgentVersionDetails,
PromptAgentDefinition,
PromptAgentDefinitionText,
PromptAgentDefinitionTextOptions,
)
from azure.ai.projects.models import (
FunctionTool as AzureFunctionTool,
@@ -200,13 +199,14 @@ class AzureAIProjectAgentProvider(Generic[OptionsCoT]):
response_format = opts.get("response_format")
rai_config = opts.get("rai_config")
reasoning = opts.get("reasoning")
foundry_features = opts.get("foundry_features")
args: dict[str, Any] = {"model": resolved_model}
if instructions:
args["instructions"] = instructions
if response_format and isinstance(response_format, (type, dict)):
args["text"] = PromptAgentDefinitionText(
args["text"] = PromptAgentDefinitionTextOptions(
format=create_text_format_config(response_format) # type: ignore[arg-type]
)
if rai_config:
@@ -241,11 +241,15 @@ class AzureAIProjectAgentProvider(Generic[OptionsCoT]):
if all_tools_for_azure:
args["tools"] = to_azure_ai_tools(all_tools_for_azure)
created_agent = await self._project_client.agents.create_version(
agent_name=name,
definition=PromptAgentDefinition(**args),
description=description,
)
create_version_kwargs: dict[str, Any] = {
"agent_name": name,
"definition": PromptAgentDefinition(**args),
"description": description,
}
if foundry_features:
create_version_kwargs["foundry_features"] = foundry_features
created_agent = await self._project_client.agents.create_version(**create_version_kwargs)
return self._to_chat_agent_from_details(
created_agent,
@@ -259,7 +263,7 @@ class AzureAIProjectAgentProvider(Generic[OptionsCoT]):
self,
*,
name: str | None = None,
reference: AgentReference | None = None,
reference: Mapping[str, str | None] | None = None,
tools: ToolTypes | Callable[..., Any] | Sequence[ToolTypes | Callable[..., Any]] | None = None,
default_options: OptionsCoT | None = None,
middleware: Sequence[MiddlewareTypes] | None = None,
@@ -272,7 +276,7 @@ class AzureAIProjectAgentProvider(Generic[OptionsCoT]):
Args:
name: The name of the agent to retrieve (fetches latest version).
reference: Reference containing the agent's name and optionally a specific version.
reference: Mapping containing the agent's ``name`` and optionally a specific ``version``.
tools: Tools to make available to the agent. Required if the agent has function tools.
default_options: A TypedDict containing default chat options for the agent.
These options are applied to every run unless overridden.
@@ -287,12 +291,15 @@ class AzureAIProjectAgentProvider(Generic[OptionsCoT]):
"""
existing_agent: AgentVersionDetails
if reference and reference.version:
reference_name = str(reference.get("name")) if reference and reference.get("name") else None
reference_version = str(reference.get("version")) if reference and reference.get("version") else None
if reference_name and reference_version:
# Fetch specific version
existing_agent = await self._project_client.agents.get_version(
agent_name=reference.name, agent_version=reference.version
agent_name=reference_name, agent_version=reference_version
)
elif agent_name := (reference.name if reference else name):
elif agent_name := (reference_name if reference_name else name):
# Fetch latest version
details = await self._project_client.agents.get(agent_name=agent_name)
existing_agent = details.versions.latest
python/packages/azure-ai/agent_framework_azure_ai/_shared.py
+10 -10
View File
@@ -19,9 +19,9 @@ from azure.ai.agents.models import (
from azure.ai.projects.models import (
CodeInterpreterTool,
MCPTool,
ResponseTextFormatConfigurationJsonObject,
ResponseTextFormatConfigurationJsonSchema,
ResponseTextFormatConfigurationText,
TextResponseFormatConfigurationResponseFormatJsonObject,
TextResponseFormatConfigurationResponseFormatText,
TextResponseFormatJsonSchema,
Tool,
WebSearchPreviewTool,
)
@@ -463,9 +463,9 @@ def _prepare_mcp_tool_dict_for_azure_ai(tool_dict: dict[str, Any]) -> MCPTool:
def create_text_format_config(
response_format: type[BaseModel] | Mapping[str, Any],
) -> (
ResponseTextFormatConfigurationJsonSchema
| ResponseTextFormatConfigurationJsonObject
| ResponseTextFormatConfigurationText
TextResponseFormatJsonSchema
| TextResponseFormatConfigurationResponseFormatJsonObject
| TextResponseFormatConfigurationResponseFormatText
):
"""Convert response_format into Azure text format configuration."""
if isinstance(response_format, type) and issubclass(response_format, BaseModel):
@@ -473,7 +473,7 @@ def create_text_format_config(
# Ensure additionalProperties is explicitly false to satisfy Azure validation
if isinstance(schema, dict):
schema.setdefault("additionalProperties", False)
return ResponseTextFormatConfigurationJsonSchema(
return TextResponseFormatJsonSchema(
name=response_format.__name__,
schema=schema,
strict=True,
@@ -494,11 +494,11 @@ def create_text_format_config(
config_kwargs["strict"] = format_config["strict"]
if "description" in format_config:
config_kwargs["description"] = format_config["description"]
return ResponseTextFormatConfigurationJsonSchema(**config_kwargs)
return TextResponseFormatJsonSchema(**config_kwargs)
if format_type == "json_object":
return ResponseTextFormatConfigurationJsonObject()
return TextResponseFormatConfigurationResponseFormatJsonObject()
if format_type == "text":
return ResponseTextFormatConfigurationText()
return TextResponseFormatConfigurationResponseFormatText()
raise IntegrationInvalidRequestException("response_format must be a Pydantic model or mapping.")
python/packages/azure-ai/tests/test_azure_ai_client.py
+10 -10
View File
@@ -28,12 +28,12 @@ from agent_framework.openai._responses_client import RawOpenAIResponsesClient
from azure.ai.projects.aio import AIProjectClient
from azure.ai.projects.models import (
ApproximateLocation,
CodeInterpreterContainerAuto,
CodeInterpreterTool,
CodeInterpreterToolAuto,
FileSearchTool,
ImageGenTool,
MCPTool,
ResponseTextFormatConfigurationJsonSchema,
TextResponseFormatJsonSchema,
WebSearchPreviewTool,
)
from azure.core.exceptions import ResourceNotFoundError
@@ -427,7 +427,7 @@ async def test_prepare_options_basic(mock_project_client: MagicMock) -> None:
run_options = await client._prepare_options(messages, {})
assert "extra_body" in run_options
assert run_options["extra_body"]["agent"]["name"] == "test-agent"
assert run_options["extra_body"]["agent_reference"]["name"] == "test-agent"
@pytest.mark.parametrize(
@@ -465,7 +465,7 @@ async def test_prepare_options_with_application_endpoint(
if expects_agent:
assert "extra_body" in run_options
assert run_options["extra_body"]["agent"]["name"] == "test-agent"
assert run_options["extra_body"]["agent_reference"]["name"] == "test-agent"
else:
assert "extra_body" not in run_options
@@ -507,7 +507,7 @@ async def test_prepare_options_with_application_project_client(
if expects_agent:
assert "extra_body" in run_options
assert run_options["extra_body"]["agent"]["name"] == "test-agent"
assert run_options["extra_body"]["agent_reference"]["name"] == "test-agent"
else:
assert "extra_body" not in run_options
@@ -979,10 +979,10 @@ async def test_agent_creation_with_response_format(
assert hasattr(created_definition, "text")
assert created_definition.text is not None
# Check that the format is a ResponseTextFormatConfigurationJsonSchema
# Check that the format is a TextResponseFormatJsonSchema
assert hasattr(created_definition.text, "format")
format_config = created_definition.text.format
assert isinstance(format_config, ResponseTextFormatConfigurationJsonSchema)
assert isinstance(format_config, TextResponseFormatJsonSchema)
# Check the schema name matches the model class name
assert format_config.name == "ResponseFormatModel"
@@ -1040,7 +1040,7 @@ async def test_agent_creation_with_mapping_response_format(
assert hasattr(created_definition, "text")
assert created_definition.text is not None
format_config = created_definition.text.format
assert isinstance(format_config, ResponseTextFormatConfigurationJsonSchema)
assert isinstance(format_config, TextResponseFormatJsonSchema)
assert format_config.name == runtime_schema["title"]
assert format_config.schema == runtime_schema
assert format_config.strict is True
@@ -1110,7 +1110,7 @@ async def test_prepare_options_excludes_response_format(
assert "text_format" not in run_options
# But extra_body should contain agent reference
assert "extra_body" in run_options
assert run_options["extra_body"]["agent"]["name"] == "test-agent"
assert run_options["extra_body"]["agent_reference"]["name"] == "test-agent"
async def test_prepare_options_keeps_values_for_unsupported_option_keys(
@@ -1254,7 +1254,7 @@ def test_from_azure_ai_tools_mcp() -> None:
def test_from_azure_ai_tools_code_interpreter() -> None:
"""Test from_azure_ai_tools with Code Interpreter tool."""
ci_tool = CodeInterpreterTool(container=CodeInterpreterToolAuto(file_ids=["file-1"]))
ci_tool = CodeInterpreterTool(container=CodeInterpreterContainerAuto(file_ids=["file-1"]))
parsed_tools = from_azure_ai_tools([ci_tool])
assert len(parsed_tools) == 1
assert parsed_tools[0]["type"] == "code_interpreter"
python/packages/azure-ai/tests/test_foundry_memory_provider.py
+27 -26
View File
@@ -17,9 +17,10 @@ from agent_framework_azure_ai._foundry_memory_provider import FoundryMemoryProvi
def mock_project_client() -> AsyncMock:
"""Create a mock AIProjectClient."""
mock_client = AsyncMock()
mock_client.memory_stores = AsyncMock()
mock_client.memory_stores.search_memories = AsyncMock()
mock_client.memory_stores.begin_update_memories = AsyncMock()
mock_client.beta = AsyncMock()
mock_client.beta.memory_stores = AsyncMock()
mock_client.beta.memory_stores.search_memories = AsyncMock()
mock_client.beta.memory_stores.begin_update_memories = AsyncMock()
mock_client.__aenter__ = AsyncMock(return_value=mock_client)
mock_client.__aexit__ = AsyncMock()
return mock_client
@@ -146,7 +147,7 @@ class TestBeforeRun:
mem2.memory_item.content = "User is based in Seattle"
mock_search_result = Mock()
mock_search_result.memories = [mem1, mem2]
mock_project_client.memory_stores.search_memories.return_value = mock_search_result
mock_project_client.beta.memory_stores.search_memories.return_value = mock_search_result
provider = FoundryMemoryProvider(
project_client=mock_project_client,
@@ -161,7 +162,7 @@ class TestBeforeRun:
)
# Should call search_memories twice: once for static, once for contextual
assert mock_project_client.memory_stores.search_memories.call_count == 2
assert mock_project_client.beta.memory_stores.search_memories.call_count == 2
# Static memories should be cached
assert len(session.state[provider.source_id]["static_memories"]) == 2
assert session.state[provider.source_id]["initialized"] is True
@@ -181,7 +182,7 @@ class TestBeforeRun:
contextual_result.memories = [contextual_mem]
contextual_result.search_id = "search-123"
mock_project_client.memory_stores.search_memories.side_effect = [static_result, contextual_result]
mock_project_client.beta.memory_stores.search_memories.side_effect = [static_result, contextual_result]
provider = FoundryMemoryProvider(
project_client=mock_project_client,
@@ -208,7 +209,7 @@ class TestBeforeRun:
"""Empty input messages → only static search performed, no contextual search."""
static_result = Mock()
static_result.memories = []
mock_project_client.memory_stores.search_memories.return_value = static_result
mock_project_client.beta.memory_stores.search_memories.return_value = static_result
provider = FoundryMemoryProvider(
project_client=mock_project_client,
@@ -223,14 +224,14 @@ class TestBeforeRun:
)
# Should only call search_memories once for static memories
assert mock_project_client.memory_stores.search_memories.call_count == 1
assert mock_project_client.beta.memory_stores.search_memories.call_count == 1
assert provider.source_id not in ctx.context_messages
async def test_empty_search_results_no_messages(self, mock_project_client: AsyncMock) -> None:
"""Empty search results → no messages added."""
mock_search_result = Mock()
mock_search_result.memories = []
mock_project_client.memory_stores.search_memories.return_value = mock_search_result
mock_project_client.beta.memory_stores.search_memories.return_value = mock_search_result
provider = FoundryMemoryProvider(
project_client=mock_project_client,
@@ -255,7 +256,7 @@ class TestBeforeRun:
contextual_result = Mock()
contextual_result.memories = []
mock_project_client.memory_stores.search_memories.side_effect = [static_result, contextual_result]
mock_project_client.beta.memory_stores.search_memories.side_effect = [static_result, contextual_result]
provider = FoundryMemoryProvider(
project_client=mock_project_client,
@@ -269,24 +270,24 @@ class TestBeforeRun:
await provider.before_run( # type: ignore[arg-type]
agent=None, session=session, context=ctx, state=session.state.setdefault(provider.source_id, {})
)
assert mock_project_client.memory_stores.search_memories.call_count == 2
assert mock_project_client.beta.memory_stores.search_memories.call_count == 2
# Reset mock for second call
mock_project_client.memory_stores.search_memories.reset_mock()
mock_project_client.beta.memory_stores.search_memories.reset_mock()
contextual_result2 = Mock()
contextual_result2.memories = []
mock_project_client.memory_stores.search_memories.return_value = contextual_result2
mock_project_client.beta.memory_stores.search_memories.return_value = contextual_result2
# Second call - should only search contextual, not static
ctx2 = SessionContext(input_messages=[Message(role="user", text="World")], session_id="s1")
await provider.before_run( # type: ignore[arg-type]
agent=None, session=session, context=ctx2, state=session.state.setdefault(provider.source_id, {})
)
assert mock_project_client.memory_stores.search_memories.call_count == 1
assert mock_project_client.beta.memory_stores.search_memories.call_count == 1
async def test_handles_search_exception_gracefully(self, mock_project_client: AsyncMock) -> None:
"""Search exception is logged but doesn't fail the operation."""
mock_project_client.memory_stores.search_memories.side_effect = Exception("API error")
mock_project_client.beta.memory_stores.search_memories.side_effect = Exception("API error")
provider = FoundryMemoryProvider(
project_client=mock_project_client,
@@ -315,7 +316,7 @@ class TestAfterRun:
"""Stores input+response messages via begin_update_memories."""
mock_poller = Mock()
mock_poller.update_id = "update-456"
mock_project_client.memory_stores.begin_update_memories.return_value = mock_poller
mock_project_client.beta.memory_stores.begin_update_memories.return_value = mock_poller
provider = FoundryMemoryProvider(
project_client=mock_project_client,
@@ -330,8 +331,8 @@ class TestAfterRun:
agent=None, session=session, context=ctx, state=session.state.setdefault(provider.source_id, {})
)
mock_project_client.memory_stores.begin_update_memories.assert_awaited_once()
call_kwargs = mock_project_client.memory_stores.begin_update_memories.call_args.kwargs
mock_project_client.beta.memory_stores.begin_update_memories.assert_awaited_once()
call_kwargs = mock_project_client.beta.memory_stores.begin_update_memories.call_args.kwargs
assert call_kwargs["name"] == "test_store"
assert call_kwargs["scope"] == "user_123"
assert len(call_kwargs["items"]) == 2
@@ -342,7 +343,7 @@ class TestAfterRun:
async def test_only_stores_user_assistant_system(self, mock_project_client: AsyncMock) -> None:
"""Only stores user/assistant/system messages with text."""
mock_poller = Mock()
mock_project_client.memory_stores.begin_update_memories.return_value = mock_poller
mock_project_client.beta.memory_stores.begin_update_memories.return_value = mock_poller
provider = FoundryMemoryProvider(
project_client=mock_project_client,
@@ -363,7 +364,7 @@ class TestAfterRun:
agent=None, session=session, context=ctx, state=session.state.setdefault(provider.source_id, {})
)
call_kwargs = mock_project_client.memory_stores.begin_update_memories.call_args.kwargs
call_kwargs = mock_project_client.beta.memory_stores.begin_update_memories.call_args.kwargs
items = call_kwargs["items"]
assert len(items) == 2
assert items[0]["content"] == "hello"
@@ -390,12 +391,12 @@ class TestAfterRun:
agent=None, session=session, context=ctx, state=session.state.setdefault(provider.source_id, {})
)
mock_project_client.memory_stores.begin_update_memories.assert_not_awaited()
mock_project_client.beta.memory_stores.begin_update_memories.assert_not_awaited()
async def test_uses_configured_update_delay(self, mock_project_client: AsyncMock) -> None:
"""Uses the configured update_delay parameter."""
mock_poller = Mock()
mock_project_client.memory_stores.begin_update_memories.return_value = mock_poller
mock_project_client.beta.memory_stores.begin_update_memories.return_value = mock_poller
provider = FoundryMemoryProvider(
project_client=mock_project_client,
@@ -411,7 +412,7 @@ class TestAfterRun:
agent=None, session=session, context=ctx, state=session.state.setdefault(provider.source_id, {})
)
call_kwargs = mock_project_client.memory_stores.begin_update_memories.call_args.kwargs
call_kwargs = mock_project_client.beta.memory_stores.begin_update_memories.call_args.kwargs
assert call_kwargs["update_delay"] == 60
async def test_uses_previous_update_id_for_incremental_updates(self, mock_project_client: AsyncMock) -> None:
@@ -421,7 +422,7 @@ class TestAfterRun:
mock_poller2 = Mock()
mock_poller2.update_id = "update-2"
mock_project_client.memory_stores.begin_update_memories.side_effect = [mock_poller1, mock_poller2]
mock_project_client.beta.memory_stores.begin_update_memories.side_effect = [mock_poller1, mock_poller2]
provider = FoundryMemoryProvider(
project_client=mock_project_client,
@@ -446,13 +447,13 @@ class TestAfterRun:
agent=None, session=session, context=ctx2, state=session.state.setdefault(provider.source_id, {})
)
call_kwargs = mock_project_client.memory_stores.begin_update_memories.call_args.kwargs
call_kwargs = mock_project_client.beta.memory_stores.begin_update_memories.call_args.kwargs
assert call_kwargs["previous_update_id"] == "update-1"
assert session.state[provider.source_id]["previous_update_id"] == "update-2"
async def test_handles_update_exception_gracefully(self, mock_project_client: AsyncMock) -> None:
"""Update exception is logged but doesn't fail the operation."""
mock_project_client.memory_stores.begin_update_memories.side_effect = Exception("API error")
mock_project_client.beta.memory_stores.begin_update_memories.side_effect = Exception("API error")
provider = FoundryMemoryProvider(
project_client=mock_project_client,
python/packages/azure-ai/tests/test_provider.py
+1 -2
View File
@@ -8,7 +8,6 @@ from agent_framework import Agent, FunctionTool
from agent_framework._mcp import MCPTool
from azure.ai.projects.aio import AIProjectClient
from azure.ai.projects.models import (
AgentReference,
AgentVersionDetails,
PromptAgentDefinition,
)
@@ -345,7 +344,7 @@ async def test_provider_get_agent_with_reference(mock_project_client: MagicMock)
mock_project_client.agents = AsyncMock()
mock_project_client.agents.get_version.return_value = mock_agent_version
agent_reference = AgentReference(name="test-agent", version="1.0")
agent_reference = {"name": "test-agent", "version": "1.0"}
agent = await provider.get_agent(reference=agent_reference)
assert isinstance(agent, Agent)
python/packages/core/pyproject.toml
+1 -2
View File
@@ -34,8 +34,7 @@ dependencies = [
# connectors and functions
"openai>=1.99.0",
"azure-identity>=1,<2",
# Pinned to 2.0.0b3 - breaking changes in 2.0.0b4, unpin once upgrades complete
"azure-ai-projects == 2.0.0b3",
"azure-ai-projects == 2.0.0b4",
"mcp[ws]>=1.24.0,<2",
"packaging>=24.1",
]
python/samples/02-agents/context_providers/azure_ai_foundry_memory.py
+3 -3
View File
@@ -61,7 +61,7 @@ async def main() -> None:
print(f"Creating memory store '{memory_store_name}'...")
try:
# Create a memory store
memory_store = await project_client.memory_stores.create(
memory_store = await project_client.beta.memory_stores.create(
name=memory_store_name,
description="Memory store for Agent Framework with FoundryMemoryProvider",
definition=memory_store_definition,
@@ -126,7 +126,7 @@ async def main() -> None:
print(f"Agent: {result3}\n")
print(f"Stored memories from: {memory_store.name} ({memory_store.id})")
res = await project_client.memory_stores.search_memories(name=memory_store.name, scope="user_123")
res = await project_client.beta.memory_stores.search_memories(name=memory_store.name, scope="user_123")
for memory in res.memories:
print(f"Memory: {memory.memory_item.content}")
@@ -134,7 +134,7 @@ async def main() -> None:
print(f"An error occurred: {e}")
finally:
await project_client.memory_stores.delete(memory_store_name)
await project_client.beta.memory_stores.delete(memory_store_name)
print("==========================================")
print("Memory store deleted")
python/samples/02-agents/providers/azure_ai/azure_ai_provider_methods.py
+4 -4
View File
@@ -8,7 +8,7 @@ from typing import Annotated
from agent_framework import tool
from agent_framework.azure import AzureAIProjectAgentProvider
from azure.ai.projects.aio import AIProjectClient
from azure.ai.projects.models import AgentReference, PromptAgentDefinition
from azure.ai.projects.models import PromptAgentDefinition
from azure.identity.aio import AzureCliCredential
from dotenv import load_dotenv
from pydantic import Field
@@ -116,7 +116,7 @@ async def get_agent_by_name_example() -> None:
async def get_agent_by_reference_example() -> None:
"""Example of using provider.get_agent(reference=...) to retrieve a specific agent version.
This method fetches a specific version of an agent using an AgentReference.
This method fetches a specific version of an agent using a reference mapping.
Use this when you need to use a particular version of an agent.
"""
print("=== provider.get_agent(reference=...) Example ===")
@@ -136,9 +136,9 @@ async def get_agent_by_reference_example() -> None:
)
try:
# Get the agent using an AgentReference with specific version
# Get the agent using a reference mapping with specific version
provider = AzureAIProjectAgentProvider(project_client=project_client)
reference = AgentReference(name=created_agent.name, version=created_agent.version)
reference = {"name": created_agent.name, "version": created_agent.version}
agent = await provider.get_agent(reference=reference)
print(f"Retrieved agent: {agent.name} (version via reference)")
python/samples/02-agents/providers/azure_ai/azure_ai_with_memory_search.py
+3 -3
View File
@@ -43,7 +43,7 @@ async def main() -> None:
options=MemoryStoreDefaultOptions(user_profile_enabled=True, chat_summary_enabled=True),
)
memory_store = await project_client.memory_stores.create(
memory_store = await project_client.beta.memory_stores.create(
name=memory_store_name,
description="Memory store for Agent Framework conversations",
definition=memory_store_definition,
@@ -57,7 +57,7 @@ async def main() -> None:
instructions="""You are a helpful assistant that remembers past conversations.
Use the memory search tool to recall relevant information from previous interactions.""",
tools={
"type": "memory_search",
"type": "memory_search_preview",
"memory_store_name": memory_store.name,
"scope": "user_123",
"update_delay": 1, # Wait 1 second before updating memories (use higher value in production)
@@ -84,7 +84,7 @@ async def main() -> None:
# Clean up - delete the memory store
async with AIProjectClient(endpoint=endpoint, credential=credential) as project_client:
await project_client.memory_stores.delete(memory_store_name)
await project_client.beta.memory_stores.delete(memory_store_name)
print("Memory store deleted")
python/uv.lock
Generated
+10 -9
View File
@@ -401,7 +401,7 @@ requires-dist = [
{ name = "agent-framework-orchestrations", marker = "extra == 'all'", editable = "packages/orchestrations" },
{ name = "agent-framework-purview", marker = "extra == 'all'", editable = "packages/purview" },
{ name = "agent-framework-redis", marker = "extra == 'all'", editable = "packages/redis" },
{ name = "azure-ai-projects", specifier = "==2.0.0b3" },
{ name = "azure-ai-projects", specifier = "==2.0.0b4" },
{ name = "azure-identity", specifier = ">=1,<2" },
{ name = "mcp", extras = ["ws"], specifier = ">=1.24.0,<2" },
{ name = "openai", specifier = ">=1.99.0" },
@@ -1014,7 +1014,7 @@ wheels = [
[[package]]
name = "azure-ai-projects"
version = "2.0.0b3"
version = "2.0.0b4"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "azure-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -1022,10 +1022,11 @@ dependencies = [
{ name = "azure-storage-blob", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
{ name = "isodate", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
{ name = "openai", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
{ name = "typing-extensions", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
]
sdist = { url = "https://files.pythonhosted.org/packages/24/e0/3512d3f07e9dd2eb4af684387c31598c435bd87833b6a81850972963cb9c/azure_ai_projects-2.0.0b3.tar.gz", hash = "sha256:6d09ad110086e450a47b991ee8a3644f1be97fa3085d5981d543f900d78f4505", size = 431749, upload-time = "2026-01-06T05:31:25.849Z" }
sdist = { url = "https://files.pythonhosted.org/packages/24/e9/1cb8e95a19fbf174cfd7b30368a011b3e17503928b7801b8d9129b7cc59b/azure_ai_projects-2.0.0b4.tar.gz", hash = "sha256:b6082eacf0a11db59ad4c48cb7962f5204b9a0391000bc22421236f229ff783a", size = 477764, upload-time = "2026-02-24T17:57:52.489Z" }
wheels = [
{ url = "https://files.pythonhosted.org/packages/4e/b6/8fbd4786bb5c0dd19eaff86ddce0fbfb53a6f90d712038272161067a076a/azure_ai_projects-2.0.0b3-py3-none-any.whl", hash = "sha256:3b3048a3ba3904d556ba392b7bd20b6e84c93bb39df6d43a6470cdb0ad08af8c", size = 240717, upload-time = "2026-01-06T05:31:27.716Z" },
{ url = "https://files.pythonhosted.org/packages/27/6e/6445d510a8cb6a54f57e4344c14d825c37c5146fa69ccf9d9d15a29d23e2/azure_ai_projects-2.0.0b4-py3-none-any.whl", hash = "sha256:f4cf1615bd815744ddce304b97eea9456b7f6f0bd8725547c4e54e3a67534635", size = 231920, upload-time = "2026-02-24T17:57:53.917Z" },
]
[[package]]
@@ -1408,7 +1409,7 @@ name = "clr-loader"
version = "0.2.10"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "cffi", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
{ name = "cffi", marker = "(python_full_version < '3.14' and sys_platform == 'darwin') or (python_full_version < '3.14' and sys_platform == 'linux') or (python_full_version < '3.14' and sys_platform == 'win32')" },
]
sdist = { url = "https://files.pythonhosted.org/packages/18/24/c12faf3f61614b3131b5c98d3bf0d376b49c7feaa73edca559aeb2aee080/clr_loader-0.2.10.tar.gz", hash = "sha256:81f114afbc5005bafc5efe5af1341d400e22137e275b042a8979f3feb9fc9446", size = 83605, upload-time = "2026-01-03T23:13:06.984Z" }
wheels = [
@@ -1887,7 +1888,7 @@ name = "exceptiongroup"
version = "1.3.1"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "typing-extensions", marker = "(python_full_version < '3.13' and sys_platform == 'darwin') or (python_full_version < '3.13' and sys_platform == 'linux') or (python_full_version < '3.13' and sys_platform == 'win32')" },
{ name = "typing-extensions", marker = "(python_full_version < '3.11' and sys_platform == 'darwin') or (python_full_version < '3.11' and sys_platform == 'linux') or (python_full_version < '3.11' and sys_platform == 'win32')" },
]
sdist = { url = "https://files.pythonhosted.org/packages/50/79/66800aadf48771f6b62f7eb014e352e5d06856655206165d775e675a02c9/exceptiongroup-1.3.1.tar.gz", hash = "sha256:8b412432c6055b0b7d14c310000ae93352ed6754f70fa8f7c34141f91c4e3219", size = 30371, upload-time = "2025-11-21T23:01:54.787Z" }
wheels = [
@@ -4654,8 +4655,8 @@ name = "powerfx"
version = "0.0.34"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "cffi", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
{ name = "pythonnet", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
{ name = "cffi", marker = "(python_full_version < '3.14' and sys_platform == 'darwin') or (python_full_version < '3.14' and sys_platform == 'linux') or (python_full_version < '3.14' and sys_platform == 'win32')" },
{ name = "pythonnet", marker = "(python_full_version < '3.14' and sys_platform == 'darwin') or (python_full_version < '3.14' and sys_platform == 'linux') or (python_full_version < '3.14' and sys_platform == 'win32')" },
]
sdist = { url = "https://files.pythonhosted.org/packages/9f/fb/6c4bf87e0c74ca1c563921ce89ca1c5785b7576bca932f7255cdf81082a7/powerfx-0.0.34.tar.gz", hash = "sha256:956992e7afd272657ed16d80f4cad24ec95d9e4a79fb9dfa4a068a09e136af32", size = 3237555, upload-time = "2025-12-22T15:50:59.682Z" }
wheels = [
@@ -5318,7 +5319,7 @@ name = "pythonnet"
version = "3.0.5"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "clr-loader", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
{ name = "clr-loader", marker = "(python_full_version < '3.14' and sys_platform == 'darwin') or (python_full_version < '3.14' and sys_platform == 'linux') or (python_full_version < '3.14' and sys_platform == 'win32')" },
]
sdist = { url = "https://files.pythonhosted.org/packages/9a/d6/1afd75edd932306ae9bd2c2d961d603dc2b52fcec51b04afea464f1f6646/pythonnet-3.0.5.tar.gz", hash = "sha256:48e43ca463941b3608b32b4e236db92d8d40db4c58a75ace902985f76dac21cf", size = 239212, upload-time = "2024-12-13T08:30:44.393Z" }
wheels = [