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agent-framework/python/samples/04-hosting/durabletask/02_multi_agent
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Eduard van Valkenburg 5e056b672e Python: [BREAKING] Python: Provider-leading client design & OpenAI package extraction (#4818)
* Python: Provider-leading client design & OpenAI package extraction

Major refactoring of the Python Agent Framework client architecture:

- Extract OpenAI clients into new `agent-framework-openai` package
- Core package no longer depends on openai, azure-identity, azure-ai-projects
- Rename clients for discoverability: OpenAIResponsesClient → OpenAIChatClient,
  OpenAIChatClient → OpenAIChatCompletionClient
- Unify `model_id`/`deployment_name`/`model_deployment_name` → `model` param
- New FoundryChatClient for Azure AI Foundry Responses API
- New FoundryAgent/FoundryAgentClient for connecting to pre-configured Foundry agents
- Remove OpenAIBase/OpenAIConfigMixin from non-deprecated client MRO
- Deprecate AzureOpenAI* clients, AzureAIClient, OpenAIAssistantsClient
- Reorganize samples: azure_openai+azure_ai+azure_ai_agent → azure/
- ADR-0020: Provider-Leading Client Design

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

* fix: missing Agent imports in samples, .model_id → .model in foundry_local sample

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

* fix: CI failures — mypy errors, coverage targets, sample imports

- azure-ai mypy: add type ignores for TypedDict total=, model arg, forward ref
- Coverage: replace core.azure/openai targets with openai package target
- project_provider: add type annotation for opts dict

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

* fix: populate openai .pyi stub, fix broken README links, coverage targets

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

* fixes

* updated observabilitty

* reset azure init.pyi

* fix errors

* updated adr number

* fix foundry local

* fixed not renamed docstrings and comments, and added deprecated markers to old classes

* fix tests and pyprojects

* fix test vars

* updated function tests

* update durable

* updated test setup for functions

* Fix Foundry auth in workflow samples

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

* Stabilize Python integration workflows

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

* Update hosting samples for Foundry

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

* Trigger full CI rerun

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

* Trigger CI rerun again

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

* trigger rerun

* trigger rerun

* fix for litellm

* undo durabletask changes

* Move Foundry APIs into foundry namespace

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

* Fix Foundry pyproject formatting

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

* Split provider samples by Foundry surface

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

* Restore hosting sample requirements

Also fix the Foundry Local sample link after the provider sample move.

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

* updated tests

* udpated foundry integration tests

* removed dist from azurefunctions tests

* Use separate Foundry clients for concurrent agents

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

* fix client setup in azfunc and durable

* disabled two tests

* updated setup for some function and durable tests

* improved azure openai setup with new clients

* ignore deprecated

* fixes

* skip 11

* remove openai assistants int tests

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
5e056b672e · 2026-03-25 09:56:29 +00:00
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Multi-Agent

This sample demonstrates how to host multiple AI agents with different tools in a single worker-client setup using the Durable Task Scheduler.

Key Concepts Demonstrated

  • Hosting multiple agents (WeatherAgent and MathAgent) in a single worker process.
  • Each agent with its own specialized tools and instructions.
  • Interacting with different agents using separate conversation sessions.
  • Worker-client architecture for multi-agent systems.

Environment Setup

See the README.md file in the parent directory for more information on how to configure the environment, including how to install and run common sample dependencies.

Running the Sample

With the environment setup, you can run the sample using the combined approach or separate worker and client processes:

Option 1: Combined (Recommended for Testing)

cd samples/04-hosting/durabletask/02_multi_agent
python sample.py

Option 2: Separate Processes

Start the worker in one terminal:

python worker.py

In a new terminal, run the client:

python client.py

The client will interact with both agents:

Starting Durable Task Multi-Agent Client...
Using taskhub: default
Using endpoint: http://localhost:8080

================================================================================
Testing WeatherAgent
================================================================================

Created weather conversation session: <guid>
User: What is the weather in Seattle?

🔧 [TOOL CALLED] get_weather(location=Seattle)
✓ [TOOL RESULT] {'location': 'Seattle', 'temperature': 72, 'conditions': 'Sunny', 'humidity': 45}

WeatherAgent: The current weather in Seattle is sunny with a temperature of 72°F and 45% humidity.

================================================================================
Testing MathAgent
================================================================================

Created math conversation session: <guid>
User: Calculate a 20% tip on a $50 bill

🔧 [TOOL CALLED] calculate_tip(bill_amount=50.0, tip_percentage=20.0)
✓ [TOOL RESULT] {'bill_amount': 50.0, 'tip_percentage': 20.0, 'tip_amount': 10.0, 'total': 60.0}

MathAgent: For a $50 bill with a 20% tip, the tip amount is $10.00 and the total is $60.00.

Viewing Agent State

You can view the state of both agents in the Durable Task Scheduler dashboard:

  1. Open your browser and navigate to http://localhost:8082
  2. In the dashboard, you can view:
    • The state of both WeatherAgent and MathAgent entities (dafx-WeatherAgent, dafx-MathAgent)
    • Each agent's conversation state across multiple interactions