Evan Mattson
4b0522d62d
* Bump Python package versions to 1.5.0 for a release
* Promote orchestrations to 1.0.0rc1
* ci(python-setup): merge dynamic exclude into existing workspace exclude
The python-setup action injected exclude = [...] verbatim into
[tool.uv.workspace], producing a duplicate 'exclude' key when the
section already had a static exclude. Scope the rewrite to the
[tool.uv.workspace] section and append the package to the existing
array when present; idempotent if the package is already excluded.
* Address Copilot review feedback: raise inter-package floors to 1.5.0
- foundry, foundry-local: agent-framework-openai >=1.4.0 -> >=1.5.0
- azure-contentunderstanding: agent-framework-foundry >=1.4.0 -> >=1.5.0
- azurefunctions: pin agent-framework-durabletask to >=1.0.0b260519,<2
Keeps lockstep cohort consistent and avoids mixed 1.4.x / 1.5.0 installs.
* Re-include azurefunctions and durabletask in the uv workspace
The pinned durabletask>=1.4.0 floor is enough to make resolution succeed;
the workspace exclude was over-correction and broke CI samples and pyright
type-checking (re-exports in agent_framework/azure/__init__.pyi plus
samples/04-hosting/{azure_functions,durabletask}/ could not resolve their
imports). Dropping them from agent-framework-core[all] still stands so the
metapackage does not pull them.
* Restore azurefunctions and durabletask in agent-framework-core[all]
The durabletask floor pin keeps users on the safe 1.4.0, so they are once
again included in the metapackage. Update CHANGELOG to reflect the pin
rather than an [all] removal.
* Raise uvicorn ceiling in ag-ui and devui to allow 0.42+
The root override-dependencies pins uvicorn[standard]>=0.34.0 (no upper)
and the workspace lock resolves to 0.47.0. The package ceiling <0.42.0
meant the workspace was no longer testing the declared supported range.
Bump to <1 so the lock fits within the declared bounds.
Also picked up by validate-dependency-bounds: refresh stale orchestrations
RC pin in devui dev deps.
Agent Framework Foundry
This package contains the Microsoft Foundry integrations for Microsoft Agent Framework, including Foundry chat clients, preconfigured Foundry agents, Foundry embedding clients, and Foundry memory providers.
Toolboxes
A toolbox is a named, versioned bundle of hosted tool configurations — code interpreter, file search, image generation, MCP, web search, and so on — stored inside a Microsoft Foundry project. Toolboxes let you manage tool configuration once and reuse it across agents.
Authoring a toolbox
Toolboxes can be authored two ways:
- Foundry portal — create and version toolboxes through the UI without touching code.
- Programmatically — use the
azure-ai-projectsSDK to create, update, and version toolboxes from Python.
Toolbox authoring APIs (
ToolboxVersionObject,ToolboxObject,project_client.beta.toolboxes.*) requireazure-ai-projects>=2.1.0. Earlier versions can only consume toolboxes that already exist.
Using toolboxes with FoundryAgent
For hosted FoundryAgent, the toolbox must already be attached to the agent in the Microsoft Foundry project. Once attached, the agent invokes its toolbox tools transparently — no client-side wiring required — and you interact with the agent the same way you would with any other tool-equipped Foundry agent.
Using toolboxes with FoundryChatClient
Each toolbox is reachable as an MCP server. Connect to the toolbox's MCP endpoint with MCPStreamableHTTPTool — the agent then discovers and calls its tools over MCP at runtime:
from agent_framework import Agent, MCPStreamableHTTPTool
from agent_framework.foundry import FoundryChatClient
async with Agent(
client=FoundryChatClient(...),
instructions="You are a helpful assistant. Use the toolbox tools when useful.",
tools=MCPStreamableHTTPTool(
name="my_toolbox",
description="Tools served by my Foundry toolbox",
url="https://<your-toolbox-mcp-endpoint>",
),
) as agent:
result = await agent.run("What tools are available?")
print(result.text)