Python: Upgraded azure-ai-projects to 2.0.0b4

python/packages/azure-ai/agent_framework_azure_ai/_client.py

@@ -37,12 +37,13 @@
 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 @@ async def _get_agent_reference_or_create(
             # 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 @@ async def _get_agent_reference_or_create(
             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 @@ def _remove_agent_level_run_options(
             "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 @@ async def _prepare_options(
             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 @@ def get_code_interpreter_tool(  # type: ignore[override]
         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

@@ -18,7 +18,6 @@
 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 @@ async def before_run(
         # 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 @@ async def before_run(
         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 @@ async def after_run(
         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

@@ -4,7 +4,7 @@
 
 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.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 @@ async def create_agent(
         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 @@ async def create_agent(
         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 @@ async def get_agent(
         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 @@ async def get_agent(
 
         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 @@ async def get_agent(
         """
         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

@@ -19,9 +19,9 @@
 from azure.ai.projects.models import (
     CodeInterpreterTool,
     MCPTool,
-    ResponseTextFormatConfigurationJsonObject,
-    ResponseTextFormatConfigurationJsonSchema,
-    ResponseTextFormatConfigurationText,
+    TextResponseFormatConfigurationResponseFormatJsonObject,
+    TextResponseFormatConfigurationResponseFormatText,
+    TextResponseFormatJsonSchema,
     Tool,
     WebSearchPreviewTool,
 )
@@ -463,17 +463,17 @@ 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):
         schema = response_format.model_json_schema()
         # 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

@@ -28,12 +28,12 @@
 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"