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# pylint: disable=too-many-lines,line-too-long,useless-suppression
# ------------------------------------
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# ------------------------------------
# cSpell:disable
from pydantic import BaseModel, Field
import pytest
from test_base import TestBase, servicePreparer
from devtools_testutils import is_live_and_not_recording
from azure.ai.projects.models import (
PromptAgentDefinition,
ResponseTextFormatConfigurationJsonSchema,
PromptAgentDefinitionText,
)
class TestAgentResponsesCrud(TestBase):
@servicePreparer()
@pytest.mark.skipif(
condition=(not is_live_and_not_recording()),
reason="Skipped because we cannot record network calls with OpenAI client",
)
def test_agent_responses_crud(self, **kwargs):
"""
Test two-turn Responses with Agent reference and Conversation.
Routes used in this test:
Action REST API Route Client Method
------+---------------------------------------------+-----------------------------------
# Setup:
POST /agents/{agent_name}/versions project_client.agents.create_version()
POST /openai/conversations openai_client.conversations.create()
# Test focus:
POST /openai/responses openai_client.responses.create()
GET /openai/responses/{response_id} openai_client.responses.retrieve() # SERVICE BUG? returns 500 Internal Server Error
DELETE /openai/responses/{response_id} openai_client.responses.delete() # SERVICE BUG? returns 500 Internal Server Error
GET /openai/responses/{response_id}/input_items openai_client.responses.list_input_items() # SERVICE BUG? returns 500 Internal Server Error
GET /openai/responses openai_client.responses.list()
POST /openai/responses/{response_id}/cancel openai_client.responses.cancel() # SERVICE BUG? returns 500 Internal Server Error
# Teardown:
DELETE /conversations/{conversation_id} openai_client.conversations.delete()
DELETE /agents/{agent_name}/versions/{agent_version} project_client.agents.delete_version()
"""
model = self.test_agents_params["model_deployment_name"]
# Setup
project_client = self.create_client(operation_group="agents", **kwargs)
openai_client = project_client.get_openai_client()
agent = project_client.agents.create_version(
agent_name="MyAgent",
definition=PromptAgentDefinition(
model=model,
instructions="You are a helpful assistant that answers general questions",
),
)
print(f"Agent created (id: {agent.id}, name: {agent.name}, version: {agent.version})")
conversation = openai_client.conversations.create(
items=[{"type": "message", "role": "user", "content": "How many feet in a mile?"}]
)
print(f"Created conversation with initial user message (id: {conversation.id})")
response = openai_client.responses.create(
conversation=conversation.id,
extra_body={"agent": {"name": agent.name, "type": "agent_reference"}},
input="", # TODO: Remove 'input' once service is fixed
)
print(f"Response id: {response.id}, output text: {response.output_text}")
assert "5280" in response.output_text or "5,280" in response.output_text
items = openai_client.conversations.items.create(
conversation.id,
items=[{"type": "message", "role": "user", "content": "And how many meters?"}],
)
# Test retrieving a response
# TODO: Service bug? Is this supposed to work? returns 500 Internal Server Error
# retrieved_response = openai_client.responses.retrieve(response_id=response.id)
# print(f"Retrieved response output: {retrieved_response.output_text}")
# assert retrieved_response.id == response.id
# assert retrieved_response.output_text == response.output_text
# Test deleting a response
# TODO: Service bug? Is this supposed to work? returns 500 Internal Server Error
# deleted_response = openai_client.responses.delete(response_id=response.id)
# assert deleted_response.id == response.id
# assert deleted_response.deleted is True
# print(f"Deleted response: {deleted_response}")
# Re-add original user message to the conversation
# conversation = openai_client.conversations.create(
# items=[ResponsesUserMessageItemParam(content="What is the size of France in square miles?")]
# )
# print(f"Created conversation with initial user message (id: {conversation.id})")
# openai_client.conversations.items.create(
# conversation_id=conversation.id,
# # items=[ResponsesUserMessageItemParam(content="And what is the capital city?")],
# items=[{"type": "message", "role": "user", "content": "And what is the capital city?"}],
# )
# print(f"Added a second user message to the conversation")
response = openai_client.responses.create(
conversation=conversation.id,
extra_body={"agent": {"name": agent.name, "type": "agent_reference"}},
input="", # TODO: Remove 'input' once service is fixed
)
print(f"Response id: {response.id}, output text: {response.output_text}")
assert "1609" in response.output_text or "1,609" in response.output_text
# TODO: Service bug? Is this supposed to work? returns 500 Internal Server Error
# print(f"List all input items in the response:")
# for listed_item in openai_client.responses.list_input_items(response_id=response.id):
# print(f" - response item type {listed_item.type}, id {listed_item.id}")
# OpenAI SDK does not support "list" responses. Even though the Azure endpoint does.
# print(f"List all responses:")
# count = 0
# for listed_response in openai_client.responses.list(conversation_id=conversation.id):
# count += 1
# # TODO: Note of these responses match the above created responses
# print(f" - Response id: {listed_response.id}, output text: {listed_response.output_text}")
# assert count >= 2
# openai_client.conversations.items.create(
# conversation_id=conversation.id,
# items=[ResponsesUserMessageItemParam(content="List all prime numbers between 1 and 1000.")],
# )
# print(f"Added a third user message to the conversation")
# response = openai_client.responses.create(
# conversation=conversation.id,
# extra_body={"agent": AgentReference(name=agent.name).as_dict()}
# )
# print(f"Response id: {response.id}, output text: {response.output_text}")
# TODO: Why do we have a cancel operation, when there are no long-running-operations?
# TODO: Service bug? Is this supposed to work? returns 500 Internal Server Error
# If the have the response ID, it means the "response.create" call is already completed...
# canceled_response = openai_client.responses.cancel(response_id=response.id)
# print(f"Canceled response id: {canceled_response.id}")
# Teardown
openai_client.conversations.delete(conversation_id=conversation.id)
print("Conversation deleted")
project_client.agents.delete_version(agent_name=agent.name, agent_version=agent.version)
print("Agent deleted")
# To run this tes:
# pytest tests\agents\test_agent_responses_crud.py::TestAgentResponsesCrud::test_agent_responses_with_structured_output -s
@servicePreparer()
@pytest.mark.skipif(
condition=(not is_live_and_not_recording()),
reason="Skipped because we cannot record network calls with OpenAI client",
)
def test_agent_responses_with_structured_output(self, **kwargs):
model = self.test_agents_params["model_deployment_name"]
# Setup
project_client = self.create_client(operation_group="agents", **kwargs)
openai_client = project_client.get_openai_client()
class CalendarEvent(BaseModel):
model_config = {"extra": "forbid"}
name: str
date: str = Field(description="Date in YYYY-MM-DD format")
participants: list[str]
agent = project_client.agents.create_version(
agent_name="MyAgent",
definition=PromptAgentDefinition(
model=model,
text=PromptAgentDefinitionText(
format=ResponseTextFormatConfigurationJsonSchema(
name="CalendarEvent", schema=CalendarEvent.model_json_schema()
)
),
instructions="""
You are a helpful assistant that extracts calendar event information from the input user messages,
and returns it in the desired structured output format.
""",
),
)
print(f"Agent created (id: {agent.id}, name: {agent.name}, version: {agent.version})")
conversation = openai_client.conversations.create(
items=[
{
"type": "message",
"role": "user",
"content": "Alice and Bob are going to a science fair this Friday, November 7, 2025.",
}
]
)
print(f"Created conversation with initial user message (id: {conversation.id})")
response = openai_client.responses.create(
conversation=conversation.id,
extra_body={"agent": {"name": agent.name, "type": "agent_reference"}},
input="", # TODO: Remove 'input' once service is fixed
)
print(f"Response id: {response.id}, output text: {response.output_text}")
assert response.output_text == '{"name":"Science Fair","date":"2025-11-07","participants":["Alice","Bob"]}'
openai_client.conversations.delete(conversation_id=conversation.id)
print("Conversation deleted")
project_client.agents.delete_version(agent_name=agent.name, agent_version=agent.version)
print("Agent deleted")
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