Eduard van Valkenburg 55398e21df Python: Add max_function_calls to FunctionInvocationConfiguration (#2329) (#4175)
* Add max_function_calls to FunctionInvocationConfiguration (#2329)

Add a new per-request max_function_calls setting to FunctionInvocationConfiguration
that limits the total number of individual function invocations across all iterations
within a single get_response call. This complements max_iterations (which limits LLM
roundtrips) by providing a hard cap on actual tool executions regardless of parallelism.

- Add max_function_calls field to FunctionInvocationConfiguration (default: None/unlimited)
- Track cumulative function call count in both streaming and non-streaming tool loops
- Force tool_choice='none' when the limit is reached
- Add validation in normalize_function_invocation_configuration
- Improve docstrings for FunctionInvocationConfiguration, FunctionTool, and @tool
  to clarify semantics of max_iterations vs max_function_calls vs max_invocations
- Add tests for parallel calls, single calls, unlimited mode, and config validation

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Add sample for controlling total tool executions

Showcases all three mechanisms for limiting tool executions:
1. max_iterations — caps LLM roundtrips
2. max_function_calls — caps total individual function invocations per request
3. max_invocations — lifetime cap on a specific tool instance
Plus a combined scenario demonstrating defense in depth.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Suppress ruff E305/fmt in hosting sample to preserve XML doc tags

The XML snippet tags (# <create_agent> / # </create_agent>) are used for
docs extraction and must stay adjacent to the code they wrap. Both ruff
check (E305) and ruff format add blank lines after the function definition,
pushing the closing tag away. Suppress with ruff: noqa: E305 and fmt: off.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Add per-agent tool wrapping scenario to control_total_tool_executions sample

Show that wrapping the same callable with @tool multiple times creates
independent FunctionTool instances with separate invocation counters,
enabling per-agent max_invocations budgets for shared functions.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Clarify max_function_calls is a best-effort limit

The limit is checked after each batch of parallel calls completes, so the
current batch always runs to completion even if it overshoots the limit.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Address PR review: fix docstring reference, clarify best-effort in sample

- Fix malformed Sphinx :attr: role in FunctionTool docstring — use plain
  backtick reference instead
- Update sample to say 'best-effort cap' instead of 'hard cap' for
  max_function_calls, noting it's checked between iterations
- Parametrize pattern is correct (fixture override, matching existing tests)

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* clarify max_invocations limits

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
55398e21df · 2026-02-24 01:00:25 +00:00
1,522 Commits
2025-12-08 21:30:21 +00:00
2025-10-30 20:29:01 +00:00
2025-04-28 12:54:43 -07:00
2026-02-20 01:25:46 +00:00
2025-04-28 12:54:42 -07:00

Microsoft Agent Framework

Welcome to Microsoft Agent Framework!

Microsoft Azure AI Foundry Discord MS Learn Documentation PyPI NuGet

Welcome to Microsoft's comprehensive multi-language framework for building, orchestrating, and deploying AI agents with support for both .NET and Python implementations. This framework provides everything from simple chat agents to complex multi-agent workflows with graph-based orchestration.

Watch the full Agent Framework introduction (30 min)

Watch the full Agent Framework introduction (30 min)

📋 Getting Started

📦 Installation

Python

pip install agent-framework --pre
# This will install all sub-packages, see `python/packages` for individual packages.
# It may take a minute on first install on Windows.

.NET

dotnet add package Microsoft.Agents.AI

📚 Documentation

Still have questions? Join our weekly office hours or ask questions in our Discord channel to get help from the team and other users.

Highlights

  • Graph-based Workflows: Connect agents and deterministic functions using data flows with streaming, checkpointing, human-in-the-loop, and time-travel capabilities
  • AF Labs: Experimental packages for cutting-edge features including benchmarking, reinforcement learning, and research initiatives
  • DevUI: Interactive developer UI for agent development, testing, and debugging workflows

See the DevUI in action

See the DevUI in action (1 min)

💬 We want your feedback!

Quickstart

Basic Agent - Python

Create a simple Azure Responses Agent that writes a haiku about the Microsoft Agent Framework

# pip install agent-framework --pre
# Use `az login` to authenticate with Azure CLI
import os
import asyncio
from agent_framework.azure import AzureOpenAIResponsesClient
from azure.identity import AzureCliCredential


async def main():
    # Initialize a chat agent with Azure OpenAI Responses
    # the endpoint, deployment name, and api version can be set via environment variables
    # or they can be passed in directly to the AzureOpenAIResponsesClient constructor
    agent = AzureOpenAIResponsesClient(
        # endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],
        # deployment_name=os.environ["AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME"],
        # api_version=os.environ["AZURE_OPENAI_API_VERSION"],
        # api_key=os.environ["AZURE_OPENAI_API_KEY"],  # Optional if using AzureCliCredential
        credential=AzureCliCredential(), # Optional, if using api_key
    ).as_agent(
        name="HaikuBot",
        instructions="You are an upbeat assistant that writes beautifully.",
    )

    print(await agent.run("Write a haiku about Microsoft Agent Framework."))

if __name__ == "__main__":
    asyncio.run(main())

Basic Agent - .NET

Create a simple Agent, using OpenAI Responses, that writes a haiku about the Microsoft Agent Framework

// dotnet add package Microsoft.Agents.AI.OpenAI --prerelease
using Microsoft.Agents.AI;
using OpenAI;
using OpenAI.Responses;

// Replace the <apikey> with your OpenAI API key.
var agent = new OpenAIClient("<apikey>")
    .GetResponsesClient("gpt-4o-mini")
    .AsAIAgent(name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");

Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Framework."));

Create a simple Agent, using Azure OpenAI Responses with token based auth, that writes a haiku about the Microsoft Agent Framework

// dotnet add package Microsoft.Agents.AI.OpenAI --prerelease
// dotnet add package Azure.Identity
// Use `az login` to authenticate with Azure CLI
using System.ClientModel.Primitives;
using Azure.Identity;
using Microsoft.Agents.AI;
using OpenAI;
using OpenAI.Responses;

// Replace <resource> and gpt-4o-mini with your Azure OpenAI resource name and deployment name.
var agent = new OpenAIClient(
    new BearerTokenPolicy(new AzureCliCredential(), "https://ai.azure.com/.default"),
    new OpenAIClientOptions() { Endpoint = new Uri("https://<resource>.openai.azure.com/openai/v1") })
    .GetResponsesClient("gpt-4o-mini")
    .AsAIAgent(name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");

Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Framework."));

More Examples & Samples

Python

.NET

Contributor Resources

Important Notes

If you use the Microsoft Agent Framework to build applications that operate with third-party servers or agents, you do so at your own risk. We recommend reviewing all data being shared with third-party servers or agents and being cognizant of third-party practices for retention and location of data. It is your responsibility to manage whether your data will flow outside of your organization's Azure compliance and geographic boundaries and any related implications.

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