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Python: Update sample validation scripts (#4870)

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* Update sample validation scripts

* Adjust prompt

* Update autogen-migration samples

* Add fix suggestion

* Split jobs

* Add .env

* Create trend report

* Add timestamp

* Add more env vars

* Comments

* force node24

* force node24

* force node22
This commit is contained in:
Tao Chen
2026-03-24 18:21:32 -07:00
committed by GitHub
Unverified
parent 2c000b032d
commit 4b533608b6
19 changed files with 928 additions and 202 deletions
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python/samples/02-agents/chat_client/built_in_chat_clients.py
+9 -7
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@@ -5,7 +5,7 @@ import os
from random import randint
from typing import Annotated, Any, Literal
from agent_framework import SupportsChatGetResponse, tool
from agent_framework import Message, SupportsChatGetResponse, tool
from agent_framework.azure import (
AzureAIAgentClient,
AzureOpenAIAssistantsClient,
@@ -117,35 +117,37 @@ async def main(client_name: ClientName = "openai_chat") -> None:
client = get_client(client_name)
# 1. Configure prompt and streaming mode.
message = "What's the weather in Amsterdam and in Paris?"
message = Message("user", text="What's the weather in Amsterdam and in Paris?")
stream = os.getenv("STREAM", "false").lower() == "true"
print(f"Client: {client_name}")
print(f"User: {message}")
print(f"User: {message.text}")
# 2. Run with context-managed clients.
if isinstance(client, OpenAIAssistantsClient | AzureOpenAIAssistantsClient | AzureAIAgentClient):
async with client:
if stream:
response_stream = client.get_response(message, stream=True, options={"tools": get_weather})
response_stream = client.get_response([message], stream=True, options={"tools": get_weather})
print("Assistant: ", end="")
async for chunk in response_stream:
if chunk.text:
print(chunk.text, end="")
print("")
else:
print(f"Assistant: {await client.get_response(message, stream=False, options={'tools': get_weather})}")
print(
f"Assistant: {await client.get_response([message], stream=False, options={'tools': get_weather})}"
)
return
# 3. Run with non-context-managed clients.
if stream:
response_stream = client.get_response(message, stream=True, options={"tools": get_weather})
response_stream = client.get_response([message], stream=True, options={"tools": get_weather})
print("Assistant: ", end="")
async for chunk in response_stream:
if chunk.text:
print(chunk.text, end="")
print("")
else:
print(f"Assistant: {await client.get_response(message, stream=False, options={'tools': get_weather})}")
print(f"Assistant: {await client.get_response([message], stream=False, options={'tools': get_weather})}")
if __name__ == "__main__":
python/samples/autogen-migration/orchestrations/01_round_robin_group_chat.py
+8 -18
View File
@@ -1,25 +1,17 @@
# /// script
# requires-python = ">=3.10"
# dependencies = [
# "autogen-agentchat",
# "autogen-ext[openai]",
# ]
# ///
# Run with any PEP 723 compatible runner, e.g.:
# uv run samples/autogen-migration/orchestrations/01_round_robin_group_chat.py
# Copyright (c) Microsoft. All rights reserved.
"""AutoGen RoundRobinGroupChat vs Agent Framework GroupChatBuilder/SequentialBuilder.
Demonstrates sequential agent orchestration where agents take turns processing
the task in a round-robin fashion.
"""
import asyncio
from agent_framework import Message
from dotenv import load_dotenv
"""AutoGen RoundRobinGroupChat vs Agent Framework GroupChatBuilder/SequentialBuilder.
Demonstrates sequential agent orchestration where agents take turns processing
the task in a round-robin fashion.
"""
# Load environment variables from .env file
load_dotenv()
@@ -98,7 +90,7 @@ async def run_agent_framework() -> None:
print("[Agent Framework] Sequential conversation:")
async for event in workflow.run("Create a brief summary about electric vehicles", stream=True):
if event.type == "output" and isinstance(event.data, list):
for message in event.data:
for message in event.data: # type: ignore
if isinstance(message, Message) and message.role == "assistant" and message.text:
print(f"---------- {message.author_name} ----------")
print(message.text)
@@ -144,9 +136,7 @@ async def run_agent_framework_with_cycle() -> None:
if last_message and "APPROVED" in last_message.text:
await context.yield_output("Content approved.")
else:
await context.send_message(
AgentExecutorRequest(messages=response.full_conversation, should_respond=True)
)
await context.send_message(AgentExecutorRequest(messages=response.full_conversation, should_respond=True))
workflow = (
WorkflowBuilder(start_executor=researcher)
python/samples/autogen-migration/orchestrations/02_selector_group_chat.py
+7 -15
View File
@@ -1,25 +1,17 @@
# /// script
# requires-python = ">=3.10"
# dependencies = [
# "autogen-agentchat",
# "autogen-ext[openai]",
# ]
# ///
# Run with any PEP 723 compatible runner, e.g.:
# uv run samples/autogen-migration/orchestrations/02_selector_group_chat.py
# Copyright (c) Microsoft. All rights reserved.
"""AutoGen SelectorGroupChat vs Agent Framework GroupChatBuilder.
Demonstrates LLM-based speaker selection where an orchestrator decides
which agent should speak next based on the conversation context.
"""
import asyncio
from agent_framework import Message
from dotenv import load_dotenv
"""AutoGen SelectorGroupChat vs Agent Framework GroupChatBuilder.
Demonstrates LLM-based speaker selection where an orchestrator decides
which agent should speak next based on the conversation context.
"""
# Load environment variables from .env file
load_dotenv()
@@ -113,7 +105,7 @@ async def run_agent_framework() -> None:
print("[Agent Framework] Group chat conversation:")
async for event in workflow.run("How do I connect to a PostgreSQL database using Python?", stream=True):
if event.type == "output" and isinstance(event.data, list):
for message in event.data:
for message in event.data: # type: ignore
if isinstance(message, Message) and message.role == "assistant" and message.text:
print(f"---------- {message.author_name} ----------")
print(message.text)
python/samples/autogen-migration/orchestrations/03_swarm.py
+6 -15
View File
@@ -1,19 +1,4 @@
# /// script
# requires-python = ">=3.10"
# dependencies = [
# "autogen-agentchat",
# "autogen-ext[openai]",
# ]
# ///
# Run with any PEP 723 compatible runner, e.g.:
# uv run samples/autogen-migration/orchestrations/03_swarm.py
# Copyright (c) Microsoft. All rights reserved.
"""AutoGen Swarm pattern vs Agent Framework HandoffBuilder.
Demonstrates agent handoff coordination where agents can transfer control
to other specialized agents based on the task requirements.
"""
import asyncio
from typing import Any
@@ -21,6 +6,12 @@ from typing import Any
from agent_framework import AgentResponseUpdate, WorkflowEvent
from dotenv import load_dotenv
"""AutoGen Swarm pattern vs Agent Framework HandoffBuilder.
Demonstrates agent handoff coordination where agents can transfer control
to other specialized agents based on the task requirements.
"""
# Load environment variables from .env file
load_dotenv()
python/samples/autogen-migration/orchestrations/04_magentic_one.py
+6 -15
View File
@@ -1,19 +1,4 @@
# /// script
# requires-python = ">=3.10"
# dependencies = [
# "autogen-agentchat",
# "autogen-ext[openai]",
# ]
# ///
# Run with any PEP 723 compatible runner, e.g.:
# uv run samples/autogen-migration/orchestrations/04_magentic_one.py
# Copyright (c) Microsoft. All rights reserved.
"""AutoGen MagenticOneGroupChat vs Agent Framework MagenticBuilder.
Demonstrates orchestrated multi-agent workflows with a central coordinator
managing specialized agents for complex tasks.
"""
import asyncio
import json
@@ -27,6 +12,12 @@ from agent_framework import (
from agent_framework.orchestrations import MagenticProgressLedger
from dotenv import load_dotenv
"""AutoGen MagenticOneGroupChat vs Agent Framework MagenticBuilder.
Demonstrates orchestrated multi-agent workflows with a central coordinator
managing specialized agents for complex tasks.
"""
# Load environment variables from .env file
load_dotenv()
python/samples/autogen-migration/single_agent/01_basic_assistant_agent.py
+5 -14
View File
@@ -1,14 +1,9 @@
# /// script
# requires-python = ">=3.10"
# dependencies = [
# "autogen-agentchat",
# "autogen-ext[openai]",
# ]
# ///
# Run with any PEP 723 compatible runner, e.g.:
# uv run samples/autogen-migration/single_agent/01_basic_assistant_agent.py
# Copyright (c) Microsoft. All rights reserved.
import asyncio
from dotenv import load_dotenv
"""Basic AutoGen AssistantAgent vs Agent Framework Agent.
Both samples expect OpenAI-compatible environment variables (OPENAI_API_KEY or
@@ -16,10 +11,6 @@ Azure OpenAI configuration). Update the prompts or client wiring to match your
model of choice before running.
"""
import asyncio
from dotenv import load_dotenv
# Load environment variables from .env file
load_dotenv()
python/samples/autogen-migration/single_agent/02_assistant_agent_with_tool.py
+5 -15
View File
@@ -1,24 +1,14 @@
# /// script
# requires-python = ">=3.10"
# dependencies = [
# "autogen-agentchat",
# "autogen-core",
# "autogen-ext[openai]",
# ]
# ///
# Run with any PEP 723 compatible runner, e.g.:
# uv run samples/autogen-migration/single_agent/02_assistant_agent_with_tool.py
# Copyright (c) Microsoft. All rights reserved.
"""AutoGen AssistantAgent vs Agent Framework Agent with function tools.
Demonstrates how to create and attach tools to agents in both frameworks.
"""
import asyncio
from dotenv import load_dotenv
"""AutoGen AssistantAgent vs Agent Framework Agent with function tools.
Demonstrates how to create and attach tools to agents in both frameworks.
"""
# Load environment variables from .env file
load_dotenv()
python/samples/autogen-migration/single_agent/03_assistant_agent_thread_and_stream.py
+5 -14
View File
@@ -1,23 +1,14 @@
# /// script
# requires-python = ">=3.10"
# dependencies = [
# "autogen-agentchat",
# "autogen-ext[openai]",
# ]
# ///
# Run with any PEP 723 compatible runner, e.g.:
# uv run samples/autogen-migration/single_agent/03_assistant_agent_thread_and_stream.py
# Copyright (c) Microsoft. All rights reserved.
"""AutoGen vs Agent Framework: Thread management and streaming responses.
Demonstrates conversation state management and streaming in both frameworks.
"""
import asyncio
from dotenv import load_dotenv
"""AutoGen vs Agent Framework: Thread management and streaming responses.
Demonstrates conversation state management and streaming in both frameworks.
"""
# Load environment variables from .env file
load_dotenv()
python/samples/autogen-migration/single_agent/04_agent_as_tool.py
+6 -14
View File
@@ -1,24 +1,15 @@
# /// script
# requires-python = ">=3.10"
# dependencies = [
# "autogen-agentchat",
# "autogen-ext[openai]",
# ]
# ///
# Run with any PEP 723 compatible runner, e.g.:
# uv run samples/autogen-migration/single_agent/04_agent_as_tool.py
# Copyright (c) Microsoft. All rights reserved.
import asyncio
from dotenv import load_dotenv
"""AutoGen vs Agent Framework: Agent-as-a-Tool pattern.
Demonstrates hierarchical agent architectures where one agent delegates
work to specialized sub-agents wrapped as tools.
"""
import asyncio
from dotenv import load_dotenv
# Load environment variables from .env file
load_dotenv()
@@ -107,6 +98,7 @@ async def run_agent_framework() -> None:
if content.type == "function_call":
# Accumulate function call content as it streams in
call_id = content.call_id
assert call_id is not None, "Function call content must have a call_id"
if call_id in accumulated_calls:
# Add to existing call (arguments stream in gradually)
accumulated_calls[call_id] = accumulated_calls[call_id] + content