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Python: (samples): adopt AzureOpenAIResponsesClient, reorganize orchestration examples, and fix workflow/orchestration bugs (#3873)

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* adopt AzureOpenAIResponsesClient, reorganize orchestration examples, and fix workflow/orchestration bugs

* Updates

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This commit is contained in:
Evan Mattson
2026-02-12 19:46:58 +09:00
committed by GitHub
Unverified
parent 8457533c69
commit 1b10b051fd
73 changed files with 1612 additions and 686 deletions
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python/samples/getting_started/workflows/visualization/concurrent_with_visualization.py
+19 -5
View File
@@ -1,6 +1,7 @@
# Copyright (c) Microsoft. All rights reserved.
import asyncio
import os
from dataclasses import dataclass
from agent_framework import (
@@ -14,7 +15,7 @@ from agent_framework import (
WorkflowViz,
handler,
)
from agent_framework.azure import AzureOpenAIChatClient
from agent_framework.azure import AzureOpenAIResponsesClient
from azure.identity import AzureCliCredential
from typing_extensions import Never
@@ -27,7 +28,8 @@ What it does:
- Visualization: generate Mermaid and GraphViz representations via `WorkflowViz` and optionally export SVG.
Prerequisites:
- Azure AI/ Azure OpenAI for `AzureOpenAIChatClient` agents.
- AZURE_AI_PROJECT_ENDPOINT must be your Azure AI Foundry Agent Service (V2) project endpoint.
- Azure AI/ Azure OpenAI for `AzureOpenAIResponsesClient` agents.
- Authentication via `azure-identity` — uses `AzureCliCredential()` (run `az login`).
- For visualization export: `pip install graphviz>=0.20.0` and install GraphViz binaries.
"""
@@ -90,7 +92,11 @@ async def main() -> None:
# Create agent instances
researcher = AgentExecutor(
AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
AzureOpenAIResponsesClient(
project_endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
deployment_name=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
credential=AzureCliCredential(),
).as_agent(
instructions=(
"You're an expert market and product researcher. Given a prompt, provide concise, factual insights,"
" opportunities, and risks."
@@ -100,7 +106,11 @@ async def main() -> None:
)
marketer = AgentExecutor(
AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
AzureOpenAIResponsesClient(
project_endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
deployment_name=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
credential=AzureCliCredential(),
).as_agent(
instructions=(
"You're a creative marketing strategist. Craft compelling value propositions and target messaging"
" aligned to the prompt."
@@ -110,7 +120,11 @@ async def main() -> None:
)
legal = AgentExecutor(
AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
AzureOpenAIResponsesClient(
project_endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
deployment_name=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
credential=AzureCliCredential(),
).as_agent(
instructions=(
"You're a cautious legal/compliance reviewer. Highlight constraints, disclaimers, and policy concerns"
" based on the prompt."