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Python: [BREAKING] updated structure and samples (#875)

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* updated structure and samples

* updated names and removed cross tests

* updated projects etc

* updated tests

* updated test

* test fixes

* removed devui for now

* updated all-tests task

* removed old style configs

* remove coverage from tests

* updated to unit tests with all-tests

* updated foundry everywhere

* fix azure ai tests

* fix merge tests

* fix mypy
This commit is contained in:
Eduard van Valkenburg
2025-09-25 09:02:53 +02:00
committed by GitHub
Unverified
parent 366a7f7d47
commit 9355329dfd
169 changed files with 1159 additions and 1761 deletions
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python/samples/getting_started/workflow/_start-here/step2_agents_in_a_workflow.py
+4 -4
View File
@@ -3,7 +3,7 @@
import asyncio
from agent_framework import AgentRunEvent, WorkflowBuilder
from agent_framework.azure import AzureChatClient
from agent_framework.azure import AzureOpenAIChatClient
from azure.identity import AzureCliCredential
"""
@@ -13,12 +13,12 @@ This sample uses two custom executors. A Writer agent creates or edits content,
then hands the conversation to a Reviewer agent which evaluates and finalizes the result.
Purpose:
Show how to wrap chat agents created by AzureChatClient inside workflow executors. Demonstrate how agents
Show how to wrap chat agents created by AzureOpenAIChatClient inside workflow executors. Demonstrate how agents
automatically yield outputs when they complete, removing the need for explicit completion events.
The workflow completes when it becomes idle.
Prerequisites:
- Azure OpenAI configured for AzureChatClient with required environment variables.
- Azure OpenAI configured for AzureOpenAIChatClient with required environment variables.
- Authentication via azure-identity. Use AzureCliCredential and run az login before executing the sample.
- Basic familiarity with WorkflowBuilder, executors, edges, events, and streaming or non streaming runs.
"""
@@ -27,7 +27,7 @@ Prerequisites:
async def main():
"""Build and run a simple two node agent workflow: Writer then Reviewer."""
# Create the Azure chat client. AzureCliCredential uses your current az login.
chat_client = AzureChatClient(credential=AzureCliCredential())
chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
writer_agent = chat_client.create_agent(
instructions=(
"You are an excellent content writer. You create new content and edit contents based on the feedback."
python/samples/getting_started/workflow/_start-here/step3_streaming.py
+8 -9
View File
@@ -2,8 +2,6 @@
import asyncio
from typing_extensions import Never
from agent_framework import (
ChatAgent,
ChatMessage,
@@ -17,8 +15,9 @@ from agent_framework import (
handler,
)
from agent_framework._workflow._events import WorkflowOutputEvent
from agent_framework.azure import AzureChatClient
from agent_framework.azure import AzureOpenAIChatClient
from azure.identity import AzureCliCredential
from typing_extensions import Never
"""
Step 3: Agents in a workflow with streaming
@@ -28,14 +27,14 @@ then passes the conversation to a Reviewer agent that finalizes the result.
The workflow is invoked with run_stream so you can observe events as they occur.
Purpose:
Show how to wrap chat agents created by AzureChatClient inside workflow executors, wire them with WorkflowBuilder,
Show how to wrap chat agents created by AzureOpenAIChatClient inside workflow executors, wire them with WorkflowBuilder,
and consume streaming events from the workflow. Demonstrate the @handler pattern with typed inputs and typed
WorkflowContext[T_Out, T_W_Out] outputs. Agents automatically yield outputs when they complete.
The streaming loop also surfaces WorkflowEvent.origin so you can distinguish runner-generated lifecycle events
from executor-generated data-plane events.
Prerequisites:
- Azure OpenAI configured for AzureChatClient with required environment variables.
- Azure OpenAI configured for AzureOpenAIChatClient with required environment variables.
- Authentication via azure-identity. Use AzureCliCredential and run az login before executing the sample.
- Basic familiarity with WorkflowBuilder, executors, edges, events, and streaming runs.
"""
@@ -51,8 +50,8 @@ class Writer(Executor):
agent: ChatAgent
def __init__(self, chat_client: AzureChatClient, id: str = "writer"):
# Create a domain specific agent using your configured AzureChatClient.
def __init__(self, chat_client: AzureOpenAIChatClient, id: str = "writer"):
# Create a domain specific agent using your configured AzureOpenAIChatClient.
agent = chat_client.create_agent(
instructions=(
"You are an excellent content writer. You create new content and edit contents based on the feedback."
@@ -88,7 +87,7 @@ class Reviewer(Executor):
agent: ChatAgent
def __init__(self, chat_client: AzureChatClient, id: str = "reviewer"):
def __init__(self, chat_client: AzureOpenAIChatClient, id: str = "reviewer"):
# Create a domain specific agent that evaluates and refines content.
agent = chat_client.create_agent(
instructions=(
@@ -111,7 +110,7 @@ class Reviewer(Executor):
async def main():
"""Build the two node workflow and run it with streaming to observe events."""
# Create the Azure chat client. AzureCliCredential uses your current az login.
chat_client = AzureChatClient(credential=AzureCliCredential())
chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
# Instantiate the two agent backed executors.
writer = Writer(chat_client)
reviewer = Reviewer(chat_client)