Python: Add support for Foundry Toolboxes (#5346)

* Add support for the Foundry Toolbox in MAF

Introduces a Foundry Toolbox integration: FoundryChatClient gains a
get_toolbox() helper plus select_toolbox_tools(), normalize_tools in
the core package flattens tool-collection wrappers (ToolboxVersionObject
and generic iterables, while leaving Pydantic BaseModel instances
alone), and the new agent_framework.foundry namespace re-exports the
toolbox helpers. Ships with unit tests, a sample, and a design doc.

azure-ai-projects is pinned to the public >=2.0.0,<3.0 range and the
lockfile resolves from public PyPI. The toolbox test module skips when
Toolbox* types are unavailable so CI stays green until the public 2.1.0
SDK lands. OMC tooling directories (.omc/, .omx/) are gitignored.

* Update to latest azure ai projects package

* Improve sample

* Rename ADR to 0025

* Update ADR

* Apply suggestion from @alliscode

Co-authored-by: Ben Thomas <ben.thomas@microsoft.com>

* Improve samples

* Update test

---------

Co-authored-by: Ben Thomas <ben.thomas@microsoft.com>

python/packages/foundry/agent_framework_foundry/__init__.py

@@ -16,6 +16,7 @@ from ._foundry_evals import (
     evaluate_traces,
 )
 from ._memory_provider import FoundryMemoryProvider
+from ._tools import FoundryHostedToolType, get_toolbox_tool_name, get_toolbox_tool_type, select_toolbox_tools
 
 try:
     __version__ = importlib.metadata.version(__name__)
@@ -30,6 +31,7 @@ __all__ = [
     "FoundryEmbeddingOptions",
     "FoundryEmbeddingSettings",
     "FoundryEvals",
+    "FoundryHostedToolType",
     "FoundryMemoryProvider",
     "RawFoundryAgent",
     "RawFoundryAgentChatClient",
@@ -38,4 +40,7 @@ __all__ = [
     "__version__",
     "evaluate_foundry_target",
     "evaluate_traces",
+    "get_toolbox_tool_name",
+    "get_toolbox_tool_type",
+    "select_toolbox_tools",
 ]

python/packages/foundry/agent_framework_foundry/_agent.py

@@ -34,6 +34,8 @@ from azure.ai.projects.aio import AIProjectClient
 from azure.core.credentials import TokenCredential
 from azure.core.credentials_async import AsyncTokenCredential
 
+from ._tools import sanitize_foundry_response_tool
+
 if sys.version_info >= (3, 13):
     from typing import TypeVar  # type: ignore # pragma: no cover
 else:
@@ -307,6 +309,20 @@ class RawFoundryAgentChatClient(  # type: ignore[misc]
         """Skip model check — model is configured on the Foundry agent."""
         pass
 
+    @override
+    def _prepare_tools_for_openai(
+        self,
+        tools: ToolTypes | Callable[..., Any] | Sequence[ToolTypes | Callable[..., Any]] | None,
+    ) -> list[Any]:
+        """Prepare tools for Foundry agent Responses API calls.
+
+        Mirrors ``RawFoundryChatClient`` sanitization so toolbox-fetched MCP
+        tools with extra read-model fields continue to work through the agent
+        surface.
+        """
+        response_tools = super()._prepare_tools_for_openai(tools)
+        return [sanitize_foundry_response_tool(tool_item) for tool_item in response_tools]
+
     def _prepare_messages_for_azure_ai(self, messages: Sequence[Message]) -> tuple[list[Message], str | None]:
         """Extract system/developer messages as instructions for Azure AI.
 

python/packages/foundry/agent_framework_foundry/_chat_client.py

@@ -16,6 +16,7 @@ from agent_framework import (
     load_settings,
 )
 from agent_framework._compaction import CompactionStrategy, TokenizerProtocol
+from agent_framework._feature_stage import ExperimentalFeature, experimental
 from agent_framework.observability import ChatTelemetryLayer
 from agent_framework_openai._chat_client import OpenAIChatOptions, RawOpenAIChatClient
 from azure.ai.projects.aio import AIProjectClient
@@ -32,6 +33,8 @@ from azure.ai.projects.models import MCPTool as FoundryMCPTool
 from azure.core.credentials import TokenCredential
 from azure.core.credentials_async import AsyncTokenCredential
 
+from ._tools import fetch_toolbox, sanitize_foundry_response_tool
+
 if sys.version_info >= (3, 13):
     from typing import TypeVar  # type: ignore # pragma: no cover
 else:
@@ -46,7 +49,8 @@ else:
     from typing_extensions import TypedDict  # type: ignore # pragma: no cover
 
 if TYPE_CHECKING:
-    from agent_framework import ChatAndFunctionMiddlewareTypes
+    from agent_framework import ChatAndFunctionMiddlewareTypes, ToolTypes
+    from azure.ai.projects.models import ToolboxVersionObject
 
 logger: logging.Logger = logging.getLogger("agent_framework.foundry")
 
@@ -218,6 +222,21 @@ class RawFoundryChatClient(  # type: ignore[misc]
                 raise ValueError("model must be a non-empty string")
             options["model"] = self.model
 
+    @override
+    def _prepare_tools_for_openai(
+        self,
+        tools: ToolTypes | Callable[..., Any] | Sequence[ToolTypes | Callable[..., Any]] | None,
+    ) -> list[Any]:
+        """Prepare tools for Foundry Responses API calls.
+
+        Foundry toolbox reads can surface MCP tool objects with extra fields
+        (for example ``name``) that are accepted by the toolbox API but rejected
+        by the Responses API. Sanitize those hosted-tool payloads before sending
+        them downstream.
+        """
+        response_tools = super()._prepare_tools_for_openai(tools)
+        return [sanitize_foundry_response_tool(tool_item) for tool_item in response_tools]
+
     async def configure_azure_monitor(
         self,
         enable_sensitive_data: bool = False,
@@ -460,6 +479,37 @@ class RawFoundryChatClient(  # type: ignore[misc]
 
     # endregion
 
+    # region Toolbox methods (instance methods — these hit the network)
+
+    @experimental(feature_id=ExperimentalFeature.TOOLBOXES)
+    async def get_toolbox(
+        self,
+        name: str,
+        *,
+        version: str | None = None,
+    ) -> ToolboxVersionObject:
+        """Fetch a Foundry toolbox by name.
+
+        If ``version`` is omitted, resolves the toolbox's current default version
+        (two requests). If ``version`` is specified, fetches that version directly
+        (single request).
+
+        Args:
+            name: The name of the toolbox.
+
+        Keyword Args:
+            version: Optional immutable version identifier to pin to.
+
+        Returns:
+            A ``ToolboxVersionObject``. Pass its ``tools`` attribute to
+            ``Agent(tools=toolbox.tools)``.
+
+        Raises:
+            azure.core.exceptions.ResourceNotFoundError: If the toolbox or
+                the requested version does not exist.
+        """
+        return await fetch_toolbox(self.project_client, name, version)
+
 
 class FoundryChatClient(  # type: ignore[misc]
     FunctionInvocationLayer[FoundryChatOptionsT],

python/packages/foundry/agent_framework_foundry/_tools.py

@@ -0,0 +1,166 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""Shared tool helpers for Foundry chat clients.
+
+Includes:
+
+* *Toolbox* helpers — a *toolbox* is a named, versioned bundle of tool
+  definitions stored in an Azure AI Foundry project.
+* Responses-API payload sanitization for Foundry hosted tools.
+"""
+
+from __future__ import annotations
+
+from collections.abc import Callable, Collection, Mapping, Sequence
+from typing import TYPE_CHECKING, Any, Literal, TypeAlias, cast
+
+from agent_framework._feature_stage import ExperimentalFeature, experimental
+from azure.ai.projects.models import MCPTool as FoundryMCPTool
+
+if TYPE_CHECKING:
+    from azure.ai.projects.aio import AIProjectClient
+    from azure.ai.projects.models import Tool, ToolboxVersionObject
+
+FoundryHostedToolType: TypeAlias = (
+    Literal[
+        "code_interpreter",
+        "file_search",
+        "image_generation",
+        "mcp",
+        "web_search",
+    ]
+    | str
+)
+ToolboxToolSelectionInput: TypeAlias = "ToolboxVersionObject | Sequence[Tool | dict[str, Any]]"
+
+
+@experimental(feature_id=ExperimentalFeature.TOOLBOXES)
+async def fetch_toolbox(
+    project_client: AIProjectClient,
+    name: str,
+    version: str | None = None,
+) -> ToolboxVersionObject:
+    """Fetch a toolbox version via an ``AIProjectClient``.
+
+    If ``version`` is omitted, resolves the toolbox's current default
+    version (two requests: one to ``.get(name)`` for the default version
+    pointer, one to ``.get_version(name, version)`` for the tools). If
+    ``version`` is specified, fetches that version directly (single request).
+    """
+    if version is None:
+        handle = await project_client.beta.toolboxes.get(name)
+        version = handle.default_version
+    return await project_client.beta.toolboxes.get_version(name, version)
+
+
+@experimental(feature_id=ExperimentalFeature.TOOLBOXES)
+def get_toolbox_tool_name(tool: Tool | dict[str, Any]) -> str | None:
+    """Return the best-effort display/selection name for a toolbox tool.
+
+    Selection precedence:
+    1. MCP ``server_label``
+    2. Generic tool ``name``
+    3. Tool ``type``
+    """
+    if isinstance(tool, dict):
+        if server_label := tool.get("server_label"):
+            return str(server_label)
+        if name := tool.get("name"):
+            return str(name)
+        if tool_type := tool.get("type"):
+            return str(tool_type)
+        return None
+
+    if server_label := getattr(tool, "server_label", None):
+        return str(server_label)
+    if name := getattr(tool, "name", None):
+        return str(name)
+    if tool_type := getattr(tool, "type", None):
+        return str(tool_type)
+    return None
+
+
+@experimental(feature_id=ExperimentalFeature.TOOLBOXES)
+def get_toolbox_tool_type(tool: Tool | dict[str, Any]) -> str | None:
+    """Return the raw tool ``type`` if present."""
+    tool_type = tool.get("type") if isinstance(tool, dict) else getattr(tool, "type", None)
+    return str(tool_type) if tool_type is not None else None
+
+
+@experimental(feature_id=ExperimentalFeature.TOOLBOXES)
+def select_toolbox_tools(
+    tools: ToolboxToolSelectionInput,
+    *,
+    include_names: Collection[str] | None = None,
+    exclude_names: Collection[str] | None = None,
+    include_types: Collection[FoundryHostedToolType] | None = None,
+    exclude_types: Collection[FoundryHostedToolType] | None = None,
+    predicate: Callable[[Tool | dict[str, Any]], bool] | None = None,
+) -> list[Tool | dict[str, Any]]:
+    """Filter toolbox tools by normalized name, raw type, and/or predicate.
+
+    Normalized name precedence:
+    1. ``server_label`` for MCP tools
+    2. ``name``
+    3. ``type``
+    """
+    tool_items: Sequence[Tool | dict[str, Any]] = (
+        tools if isinstance(tools, Sequence) else cast("Sequence[Tool | dict[str, Any]]", tools.tools)
+    )
+    include_name_set = {str(item) for item in include_names} if include_names is not None else None
+    exclude_name_set = {str(item) for item in exclude_names} if exclude_names is not None else None
+    include_type_set = {str(item) for item in include_types} if include_types is not None else None
+    exclude_type_set = {str(item) for item in exclude_types} if exclude_types is not None else None
+
+    selected: list[Tool | dict[str, Any]] = []
+    for tool in tool_items:
+        tool_name = get_toolbox_tool_name(tool)
+        tool_type = get_toolbox_tool_type(tool)
+
+        if include_name_set is not None and tool_name not in include_name_set:
+            continue
+        if exclude_name_set is not None and tool_name in exclude_name_set:
+            continue
+        if include_type_set is not None and tool_type not in include_type_set:
+            continue
+        if exclude_type_set is not None and tool_type in exclude_type_set:
+            continue
+        if predicate is not None and not predicate(tool):
+            continue
+
+        selected.append(tool)
+
+    return selected
+
+
+@experimental(feature_id=ExperimentalFeature.TOOLBOXES)
+def sanitize_foundry_response_tool(tool_item: Any) -> Any:
+    """Return a Responses-API-safe tool payload for Foundry hosted tools.
+
+    Azure AI Projects toolbox reads can currently return hosted tool objects with
+    extra read-model decoration fields such as top-level ``name`` and
+    ``description``. Azure AI Foundry rejects at least ``name`` on Responses API
+    requests with:
+
+    ``Unknown parameter: 'tools[0].name'``.
+
+    We defensively strip these decoration fields for non-function hosted tools so
+    the round-trip
+    ``toolbox.tools -> Agent(..., tools=...) -> run()`` works, while the Azure
+    SDK/service behavior is corrected upstream.
+    """
+    if isinstance(tool_item, FoundryMCPTool):
+        sanitized: dict[str, Any] = dict(cast("Mapping[str, Any]", tool_item))
+        sanitized.pop("name", None)
+        sanitized.pop("description", None)
+        return sanitized
+
+    if isinstance(tool_item, Mapping):
+        mapping = cast("Mapping[str, Any]", tool_item)
+        if "type" in mapping and mapping.get("type") not in {"function", "custom"}:
+            sanitized = dict(mapping)
+            sanitized.pop("name", None)
+            sanitized.pop("description", None)
+            return sanitized
+
+    return cast(Any, tool_item)