[BREAKING] Python: Fix workflow as agent streaming output (#3649)

* WIP: with_output_from

* Add with_output_from to other modules; next: workflow as agent

* WIP: remove agent run events

* orchestrations

* WIP: update samples; next start at guessing_game_With_human_input.py

* Update all samples

* WIP: consolidate workflow as agent streaming vs non-streaming

* Consolidate workflow as agent streaming vs non-streaming

* Move request info event processing to a share method

* Final pass on the samples

* Fix mypy

* Fix mypy

* Comments

---------

Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
This commit is contained in:
Tao Chen
2026-02-04 16:16:45 -08:00
committed by GitHub
Unverified
parent 907654a489
commit a971d24f1e
68 changed files with 2652 additions and 2247 deletions
@@ -12,7 +12,7 @@ from agent_framework import ( # Core chat primitives used to build requests
WorkflowBuilder, # Fluent builder for wiring executors and edges
WorkflowContext, # Per-run context and event bus
executor, # Decorator to declare a Python function as a workflow executor
)
)
from agent_framework.azure import AzureOpenAIChatClient # Thin client wrapper for Azure OpenAI chat models
from azure.identity import AzureCliCredential # Uses your az CLI login for credentials
from pydantic import BaseModel # Structured outputs for safer parsing
@@ -16,7 +16,7 @@ from agent_framework import ( # Core chat primitives used to form LLM requests
WorkflowBuilder, # Fluent builder for assembling the graph
WorkflowContext, # Per-run context and event bus
executor, # Decorator to turn a function into a workflow executor
)
)
from agent_framework.azure import AzureOpenAIChatClient # Thin client for Azure OpenAI chat models
from azure.identity import AzureCliCredential # Uses your az CLI login for credentials
from pydantic import BaseModel # Structured outputs with validation