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Python: Remove duplicate samples (#3899)

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* Remove duplicate samples

* Correct paths

* Update readme

* Update readme

* Fix ruff

---------

Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
This commit is contained in:
Tao Chen
2026-02-12 15:46:41 -08:00
committed by GitHub
Unverified
parent 1441fd903c
commit e064f943ae
25 changed files with 173 additions and 2772 deletions
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python/samples/03-workflows/orchestrations/handoff_simple.py
+2 -2
View File
@@ -34,8 +34,8 @@ Key Concepts:
# NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production;
# See:
# samples/getting_started/tools/function_tool_with_approval.py
# samples/getting_started/tools/function_tool_with_approval_and_sessions.py.
# samples/02-agents/tools/function_tool_with_approval.py
# samples/02-agents/tools/function_tool_with_approval_and_sessions.py.
@tool(approval_mode="never_require")
def process_refund(order_number: Annotated[str, "Order number to process refund for"]) -> str:
"""Simulated function to process a refund for a given order number."""
python/samples/03-workflows/orchestrations/handoff_with_code_interpreter_file.py
+91 -146
View File
@@ -11,37 +11,26 @@ from the streaming workflow events.
Verifies GitHub issue #2718: files generated by code interpreter in
HandoffBuilder workflows can be properly retrieved.
Toggle USE_V2_CLIENT to switch between:
- V1: AzureAIAgentClient (azure-ai-agents SDK)
- V2: AzureAIClient (azure-ai-projects 2.x with Responses API)
IMPORTANT: When using V2 AzureAIClient with HandoffBuilder, each agent must
have its own client instance. The V2 client binds to a single server-side
agent name, so sharing a client between agents causes routing issues.
Prerequisites:
- AZURE_AI_PROJECT_ENDPOINT must be your Azure AI Foundry Agent Service (V2) project endpoint.
- `az login` (Azure CLI authentication)
- V1: AZURE_AI_AGENT_PROJECT_CONNECTION_STRING
- V2: AZURE_AI_PROJECT_ENDPOINT, AZURE_AI_MODEL_DEPLOYMENT_NAME
- AZURE_AI_MODEL_DEPLOYMENT_NAME
"""
import asyncio
from collections.abc import AsyncIterable, AsyncIterator
from contextlib import asynccontextmanager
import os
from collections.abc import AsyncIterable
from typing import cast
from agent_framework import (
Agent,
AgentResponseUpdate,
Message,
WorkflowEvent,
WorkflowRunState,
)
from agent_framework.azure import AzureOpenAIResponsesClient
from agent_framework.orchestrations import HandoffAgentUserRequest, HandoffBuilder
from azure.identity.aio import AzureCliCredential
# Toggle between V1 (AzureAIAgentClient) and V2 (AzureAIClient)
USE_V2_CLIENT = False
from azure.identity import AzureCliCredential
async def _drain(stream: AsyncIterable[WorkflowEvent]) -> list[WorkflowEvent]:
@@ -66,7 +55,7 @@ def _handle_events(events: list[WorkflowEvent]) -> tuple[list[WorkflowEvent[Hand
WorkflowRunState.IDLE,
WorkflowRunState.IDLE_WITH_PENDING_REQUESTS,
}:
print(f"[status] {event.state.name}")
print(f"[status] {event.state}")
elif event.type == "request_info" and isinstance(event.data, HandoffAgentUserRequest):
requests.append(cast(WorkflowEvent[HandoffAgentUserRequest], event))
elif event.type == "output":
@@ -81,8 +70,8 @@ def _handle_events(events: list[WorkflowEvent]) -> tuple[list[WorkflowEvent[Hand
file_id = annotation["file_id"] # type: ignore
file_ids.append(file_id)
print(f"[Found file annotation: file_id={file_id}]")
elif event.type == "output":
conversation = cast(list[Message], event.data)
elif isinstance(data, list):
conversation = cast(list[Message], data)
if isinstance(conversation, list):
print("\n=== Final Conversation Snapshot ===")
for message in conversation:
@@ -93,148 +82,104 @@ def _handle_events(events: list[WorkflowEvent]) -> tuple[list[WorkflowEvent[Hand
return requests, file_ids
@asynccontextmanager
async def create_agents_v1(credential: AzureCliCredential) -> AsyncIterator[tuple[Agent, Agent]]:
"""Create agents using V1 AzureAIAgentClient."""
from agent_framework.azure import AzureAIAgentClient
async with AzureAIAgentClient(credential=credential) as client:
triage = client.as_agent(
name="triage_agent",
instructions=(
"You are a triage agent. Route code-related requests to the code_specialist. "
"When the user asks to create or generate files, hand off to code_specialist "
"by calling handoff_to_code_specialist."
),
)
# Create code interpreter tool using instance method
code_interpreter_tool = client.get_code_interpreter_tool()
code_specialist = client.as_agent(
name="code_specialist",
instructions=(
"You are a Python code specialist. Use the code interpreter to execute Python code "
"and create files when requested. Always save files to /mnt/data/ directory."
),
tools=[code_interpreter_tool],
)
yield triage, code_specialist # type: ignore
@asynccontextmanager
async def create_agents_v2(credential: AzureCliCredential) -> AsyncIterator[tuple[Agent, Agent]]:
"""Create agents using V2 AzureAIClient.
Each agent needs its own client instance because the V2 client binds
to a single server-side agent name.
"""
from agent_framework.azure import AzureAIClient
async with (
AzureAIClient(credential=credential) as triage_client,
AzureAIClient(credential=credential) as code_client,
):
triage = triage_client.as_agent(
name="TriageAgent",
instructions="You are a triage agent. Your ONLY job is to route requests to the appropriate specialist.",
)
# Create code interpreter tool using instance method
code_interpreter_tool = code_client.get_code_interpreter_tool()
code_specialist = code_client.as_agent(
name="CodeSpecialist",
instructions=(
"You are a Python code specialist. You have access to a code interpreter tool. "
"Use the code interpreter to execute Python code and create files. "
"Always save files to /mnt/data/ directory. "
"Do NOT discuss handoffs or routing - just complete the coding task directly."
),
tools=[code_interpreter_tool],
)
yield triage, code_specialist
async def main() -> None:
"""Run a simple handoff workflow with code interpreter file generation."""
client_version = "V2 (AzureAIClient)" if USE_V2_CLIENT else "V1 (AzureAIAgentClient)"
print(f"=== Handoff Workflow with Code Interpreter File Generation [{client_version}] ===\n")
print("=== Handoff Workflow with Code Interpreter File Generation ===\n")
async with AzureCliCredential() as credential:
create_agents = create_agents_v2 if USE_V2_CLIENT else create_agents_v1
client = AzureOpenAIResponsesClient(
project_endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
deployment_name=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
credential=AzureCliCredential(),
)
async with create_agents(credential) as (triage, code_specialist):
workflow = (
HandoffBuilder(
termination_condition=lambda conv: sum(1 for msg in conv if msg.role == "user") >= 2,
)
.participants([triage, code_specialist])
.with_start_agent(triage)
.build()
)
triage = client.as_agent(
name="triage_agent",
instructions=(
"You are a triage agent. Route code-related requests to the code_specialist. "
"When the user asks to create or generate files, hand off to code_specialist "
"by calling handoff_to_code_specialist."
),
)
user_inputs = [
"Please create a text file called hello.txt with 'Hello from handoff workflow!' inside it.",
"exit",
]
input_index = 0
all_file_ids: list[str] = []
code_interpreter_tool = client.get_code_interpreter_tool()
print(f"User: {user_inputs[0]}")
events = await _drain(workflow.run(user_inputs[0], stream=True))
requests, file_ids = _handle_events(events)
all_file_ids.extend(file_ids)
input_index += 1
code_specialist = client.as_agent(
name="code_specialist",
instructions=(
"You are a Python code specialist. Use the code interpreter to execute Python code "
"and create files when requested. Always save files to /mnt/data/ directory."
),
tools=[code_interpreter_tool],
)
while requests:
request = requests[0]
if input_index >= len(user_inputs):
break
user_input = user_inputs[input_index]
print(f"\nUser: {user_input}")
workflow = (
HandoffBuilder(
termination_condition=lambda conv: sum(1 for msg in conv if msg.role == "user") >= 2,
)
.participants([triage, code_specialist])
.with_start_agent(triage)
.build()
)
responses = {request.request_id: HandoffAgentUserRequest.create_response(user_input)}
events = await _drain(workflow.run(stream=True, responses=responses))
requests, file_ids = _handle_events(events)
all_file_ids.extend(file_ids)
input_index += 1
user_inputs = [
"Please create a text file called hello.txt with 'Hello from handoff workflow!' inside it.",
"exit",
]
input_index = 0
all_file_ids: list[str] = []
print("\n" + "=" * 50)
if all_file_ids:
print(f"SUCCESS: Found {len(all_file_ids)} file ID(s) in handoff workflow:")
for fid in all_file_ids:
print(f" - {fid}")
else:
print("WARNING: No file IDs captured from the handoff workflow.")
print("=" * 50)
print(f"User: {user_inputs[0]}")
events = await _drain(workflow.run(user_inputs[0], stream=True))
requests, file_ids = _handle_events(events)
all_file_ids.extend(file_ids)
input_index += 1
"""
Sample Output:
while requests:
request = requests[0]
if input_index >= len(user_inputs):
break
user_input = user_inputs[input_index]
print(f"\nUser: {user_input}")
User: Please create a text file called hello.txt with 'Hello from handoff workflow!' inside it.
[Found HostedFileContent: file_id=assistant-JT1sA...]
responses = {request.request_id: HandoffAgentUserRequest.create_response(user_input)}
events = await _drain(workflow.run(stream=True, responses=responses))
requests, file_ids = _handle_events(events)
all_file_ids.extend(file_ids)
input_index += 1
=== Conversation So Far ===
- user: Please create a text file called hello.txt with 'Hello from handoff workflow!' inside it.
- triage_agent: I am handing off your request to create the text file "hello.txt" with the specified content to the code specialist. They will assist you shortly.
- code_specialist: The file "hello.txt" has been created with the content "Hello from handoff workflow!". You can download it using the link below:
print("\n" + "=" * 50)
if all_file_ids:
print(f"SUCCESS: Found {len(all_file_ids)} file ID(s) in handoff workflow:")
for fid in all_file_ids:
print(f" - {fid}")
else:
print("WARNING: No file IDs captured from the handoff workflow.")
print("=" * 50)
[hello.txt](sandbox:/mnt/data/hello.txt)
===========================
"""
Sample Output:
[status] IDLE_WITH_PENDING_REQUESTS
User: Please create a text file called hello.txt with 'Hello from handoff workflow!' inside it.
[Found HostedFileContent: file_id=assistant-JT1sA...]
User: exit
[status] IDLE
=== Conversation So Far ===
- user: Please create a text file called hello.txt with 'Hello from handoff workflow!' inside it.
- triage_agent: I am handing off your request to create the text file "hello.txt" with the specified content to the code specialist. They will assist you shortly.
- code_specialist: The file "hello.txt" has been created with the content "Hello from handoff workflow!". You can download it using the link below:
==================================================
SUCCESS: Found 1 file ID(s) in handoff workflow:
- assistant-JT1sA...
==================================================
""" # noqa: E501
[hello.txt](sandbox:/mnt/data/hello.txt)
===========================
[status] IDLE_WITH_PENDING_REQUESTS
User: exit
[status] IDLE
==================================================
SUCCESS: Found 1 file ID(s) in handoff workflow:
- assistant-JT1sA...
==================================================
""" # noqa: E501
if __name__ == "__main__":