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Eduard van Valkenburg 3a49b1d6dd Python: [BREAKING] Remove deprecated Python OpenAI/Azure AI surfaces (#4990 )

* [BREAKING] Remove deprecated Python OpenAI/Azure AI surfaces

Also clean up follow-on docs, environment guidance, package metadata, and lab test stability.

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

* Fix deleted semantic-kernel sample links

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

* Address PR review feedback

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

* improve foundry language

* Fix A2A Foundry sample regression

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

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

3a49b1d6dd · 2026-03-31 20:36:21 +00:00

History

_tools.py

Python: Add load_dotenv() to samples for .env file support (#4043 )

2026-02-19 10:55:13 +00:00

.env.example

Python: [BREAKING] Remove deprecated Python OpenAI/Azure AI surfaces (#4990 )

2026-03-31 20:36:21 +00:00

create_workflow.py

Python: [BREAKING] Python: Provider-leading client design & OpenAI package extraction (#4818 )

2026-03-25 09:56:29 +00:00

README.md

Python: restructure: Python samples into progressive 01-05 layout (#3862 )

2026-02-12 17:36:36 +00:00

run_evaluation.py

Python: [BREAKING] Remove deprecated Python OpenAI/Azure AI surfaces (#4990 )

2026-03-31 20:36:21 +00:00

README.md

Multi-Agent Travel Planning Workflow Evaluation

This sample demonstrates evaluating a multi-agent workflow using Azure AI's built-in evaluators. The workflow processes travel planning requests through seven specialized agents in a fan-out/fan-in pattern: travel request handler, hotel/flight/activity search agents, booking aggregator, booking confirmation, and payment processing.

Evaluation Metrics

The evaluation uses four Azure AI built-in evaluators:

Relevance - How well responses address the user query
Groundedness - Whether responses are grounded in available context
Tool Call Accuracy - Correct tool selection and parameter usage
Tool Output Utilization - Effective use of tool outputs in responses

Setup

Create a .env file with configuration as in the .env.example file in this folder.

Running the Evaluation

Execute the complete workflow and evaluation:

python run_evaluation.py

The script will:

Execute the multi-agent travel planning workflow
Display response summary for each agent
Create and run evaluation on hotel, flight, and activity search agents
Monitor progress and display the evaluation report URL