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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/parallelism/fan_out_fan_in_edges.py
+3 -3
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@@ -18,7 +18,7 @@ from agent_framework import ( # Core chat primitives to build LLM requests
WorkflowOutputEvent, # Event emitted when workflow yields output
handler, # Decorator to mark an Executor method as invokable
)
from agent_framework.azure import AzureChatClient # Client wrapper for Azure OpenAI chat models
from agent_framework.azure import AzureOpenAIChatClient # Client wrapper for Azure OpenAI chat models
from azure.identity import AzureCliCredential # Uses your az CLI login for credentials
"""
@@ -35,7 +35,7 @@ Show how to construct a parallel branch pattern in workflows. Demonstrate:
Prerequisites:
- Familiarity with WorkflowBuilder, executors, edges, events, and streaming runs.
- Azure OpenAI access configured for AzureChatClient. Log in with Azure CLI and set any required environment variables.
- Azure OpenAI access configured for AzureOpenAIChatClient. Log in with Azure CLI and set any required environment variables.
- Comfort reading AgentExecutorResponse.agent_run_response.text for assistant output aggregation.
"""
@@ -107,7 +107,7 @@ class AggregateInsights(Executor):
async def main() -> None:
# 1) Create agent executors for domain experts
chat_client = AzureChatClient(credential=AzureCliCredential())
chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
researcher = AgentExecutor(
chat_client.create_agent(