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feat: Add support for Conversatsions in Responses API

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Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
This commit is contained in:
Francisco Javier Arceo 2025-10-08 15:51:11 -04:00
parent 548ccff368
commit 1e59793288
18 changed files with 662 additions and 10 deletions
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128
tests/integration/responses/test_conversation_responses.py Normal file
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@ -0,0 +1,128 @@
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
import pytest
@pytest.mark.integration
class TestConversationResponses:
"""Integration tests for the conversation parameter in responses API."""
def test_conversation_basic_workflow(self, openai_client, text_model_id):
"""Test basic conversation workflow: create conversation, add response, verify sync."""
conversation = openai_client.conversations.create(metadata={"topic": "test"})
assert conversation.id.startswith("conv_")
response = openai_client.responses.create(
model=text_model_id,
input=[{"role": "user", "content": "What are the 5 Ds of dodgeball?"}],
conversation=conversation.id,
)
assert response.id.startswith("resp_")
assert len(response.output_text.strip()) > 0
# Verify conversation was synced
conversation_items = openai_client.conversations.items.list(conversation.id)
assert len(conversation_items.data) >= 2
roles = [item.role for item in conversation_items.data if hasattr(item, "role")]
assert "user" in roles and "assistant" in roles
def test_conversation_multi_turn_and_streaming(self, openai_client, text_model_id):
"""Test multi-turn conversations and streaming responses."""
conversation = openai_client.conversations.create()
# First turn
response1 = openai_client.responses.create(
model=text_model_id,
input=[{"role": "user", "content": "Say hello"}],
conversation=conversation.id,
)
# Second turn with streaming
response_stream = openai_client.responses.create(
model=text_model_id,
input=[{"role": "user", "content": "Say goodbye"}],
conversation=conversation.id,
stream=True,
)
final_response = None
for chunk in response_stream:
if chunk.type == "response.completed":
final_response = chunk.response
break
assert response1.id != final_response.id
assert len(response1.output_text.strip()) > 0
assert len(final_response.output_text.strip()) > 0
# Verify all turns are in conversation
conversation_items = openai_client.conversations.items.list(conversation.id)
assert len(conversation_items.data) >= 4 # 2 user + 2 assistant messages
def test_conversation_context_loading(self, openai_client, text_model_id):
"""Test that conversation context is properly loaded for responses."""
conversation = openai_client.conversations.create(
items=[
{"type": "message", "role": "user", "content": "My name is Alice"},
{"type": "message", "role": "assistant", "content": "Hello Alice!"},
]
)
response = openai_client.responses.create(
model=text_model_id,
input=[{"role": "user", "content": "What's my name?"}],
conversation=conversation.id,
)
assert "alice" in response.output_text.lower()
def test_conversation_error_handling(self, openai_client, text_model_id):
"""Test error handling for invalid and nonexistent conversations."""
# Invalid conversation ID format
with pytest.raises(Exception) as exc_info:
openai_client.responses.create(
model=text_model_id,
input=[{"role": "user", "content": "Hello"}],
conversation="invalid_id",
)
assert any(word in str(exc_info.value).lower() for word in ["conv", "invalid", "bad"])
# Nonexistent conversation ID
with pytest.raises(Exception) as exc_info:
openai_client.responses.create(
model=text_model_id,
input=[{"role": "user", "content": "Hello"}],
conversation="conv_nonexistent123",
)
assert any(word in str(exc_info.value).lower() for word in ["not found", "404"])
def test_conversation_backward_compatibility(self, openai_client, text_model_id):
"""Test that responses work without conversation parameter (backward compatibility)."""
response = openai_client.responses.create(
model=text_model_id, input=[{"role": "user", "content": "Hello world"}]
)
assert response.id.startswith("resp_")
assert len(response.output_text.strip()) > 0
def test_conversation_compat_client(self, compat_client, text_model_id):
"""Test conversation parameter works with compatibility client."""
if not hasattr(compat_client, "conversations"):
pytest.skip("compat_client does not support conversations API")
conversation = compat_client.conversations.create()
response = compat_client.responses.create(
model=text_model_id, input="Tell me a joke", conversation=conversation.id
)
assert response is not None
assert len(response.output_text.strip()) > 0
conversation_items = compat_client.conversations.items.list(conversation.id)
assert len(conversation_items.data) >= 2

5
tests/unit/providers/agent/test_meta_reference_agent.py
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@ -15,6 +15,7 @@ from llama_stack.apis.agents import (
AgentCreateResponse,
)
from llama_stack.apis.common.responses import PaginatedResponse
from llama_stack.apis.conversations import Conversations
from llama_stack.apis.inference import Inference
from llama_stack.apis.safety import Safety
from llama_stack.apis.tools import ListToolDefsResponse, ToolDef, ToolGroups, ToolRuntime
@ -33,6 +34,7 @@ def mock_apis():
"safety_api": AsyncMock(spec=Safety),
"tool_runtime_api": AsyncMock(spec=ToolRuntime),
"tool_groups_api": AsyncMock(spec=ToolGroups),
"conversations_api": AsyncMock(spec=Conversations),
}
@ -59,7 +61,8 @@ async def agents_impl(config, mock_apis):
mock_apis["safety_api"],
mock_apis["tool_runtime_api"],
mock_apis["tool_groups_api"],
{},
mock_apis["conversations_api"],
[],
)
await impl.initialize()
yield impl

332
tests/unit/providers/agents/meta_reference/test_conversation_integration.py Normal file
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@ -0,0 +1,332 @@
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
import pytest
from llama_stack.apis.agents.openai_responses import (
OpenAIResponseMessage,
OpenAIResponseObject,
OpenAIResponseObjectStreamResponseCompleted,
OpenAIResponseOutputMessageContentOutputText,
)
from llama_stack.apis.common.errors import (
ConversationNotFoundError,
InvalidConversationIdError,
)
from llama_stack.apis.conversations.conversations import (
Conversation,
ConversationItemList,
)
# Import existing fixtures from the main responses test file
pytest_plugins = ["tests.unit.providers.agents.meta_reference.test_openai_responses"]
from llama_stack.providers.inline.agents.meta_reference.responses.openai_responses import (
OpenAIResponsesImpl,
)
@pytest.fixture
def responses_impl_with_conversations(
mock_inference_api,
mock_tool_groups_api,
mock_tool_runtime_api,
mock_responses_store,
mock_vector_io_api,
mock_conversations_api,
):
"""Create OpenAIResponsesImpl instance with conversations API."""
return OpenAIResponsesImpl(
inference_api=mock_inference_api,
tool_groups_api=mock_tool_groups_api,
tool_runtime_api=mock_tool_runtime_api,
responses_store=mock_responses_store,
vector_io_api=mock_vector_io_api,
conversations_api=mock_conversations_api,
)
class TestConversationValidation:
"""Test conversation ID validation logic."""
async def test_conversation_existence_check_valid(self, responses_impl_with_conversations, mock_conversations_api):
"""Test conversation existence check for valid conversation."""
conv_id = "conv_valid123"
# Mock successful conversation retrieval
mock_conversations_api.get_conversation.return_value = Conversation(
id=conv_id, created_at=1234567890, metadata={}, object="conversation"
)
result = await responses_impl_with_conversations._check_conversation_exists(conv_id)
assert result is True
mock_conversations_api.get_conversation.assert_called_once_with(conv_id)
async def test_conversation_existence_check_invalid(
self, responses_impl_with_conversations, mock_conversations_api
):
"""Test conversation existence check for non-existent conversation."""
conv_id = "conv_nonexistent"
# Mock conversation not found
mock_conversations_api.get_conversation.side_effect = ConversationNotFoundError("conv_nonexistent")
result = await responses_impl_with_conversations._check_conversation_exists(conv_id)
assert result is False
mock_conversations_api.get_conversation.assert_called_once_with(conv_id)
class TestConversationContextLoading:
"""Test conversation context loading functionality."""
async def test_load_conversation_context_simple_input(
self, responses_impl_with_conversations, mock_conversations_api
):
"""Test loading conversation context with simple string input."""
conv_id = "conv_test123"
input_text = "Hello, how are you?"
# mock items in chronological order (a consequence of order="asc")
mock_conversation_items = ConversationItemList(
data=[
OpenAIResponseMessage(
id="msg_1",
content=[{"type": "input_text", "text": "Previous user message"}],
role="user",
status="completed",
type="message",
),
OpenAIResponseMessage(
id="msg_2",
content=[{"type": "output_text", "text": "Previous assistant response"}],
role="assistant",
status="completed",
type="message",
),
],
first_id="msg_1",
has_more=False,
last_id="msg_2",
object="list",
)
mock_conversations_api.list.return_value = mock_conversation_items
result = await responses_impl_with_conversations._load_conversation_context(conv_id, input_text)
# should have conversation history + new input
assert len(result) == 3
assert isinstance(result[0], OpenAIResponseMessage)
assert result[0].role == "user"
assert isinstance(result[1], OpenAIResponseMessage)
assert result[1].role == "assistant"
assert isinstance(result[2], OpenAIResponseMessage)
assert result[2].role == "user"
assert result[2].content == input_text
async def test_load_conversation_context_api_error(self, responses_impl_with_conversations, mock_conversations_api):
"""Test loading conversation context when API call fails."""
conv_id = "conv_test123"
input_text = "Hello"
mock_conversations_api.list.side_effect = Exception("API Error")
result = await responses_impl_with_conversations._load_conversation_context(conv_id, input_text)
assert len(result) == 1
assert isinstance(result[0], OpenAIResponseMessage)
assert result[0].role == "user"
assert result[0].content == input_text
async def test_load_conversation_context_with_list_input(
self, responses_impl_with_conversations, mock_conversations_api
):
"""Test loading conversation context with list input."""
conv_id = "conv_test123"
input_messages = [
OpenAIResponseMessage(role="user", content="First message"),
OpenAIResponseMessage(role="user", content="Second message"),
]
mock_conversations_api.list.return_value = ConversationItemList(
data=[], first_id=None, has_more=False, last_id=None, object="list"
)
result = await responses_impl_with_conversations._load_conversation_context(conv_id, input_messages)
assert len(result) == 2
assert result == input_messages
async def test_load_conversation_context_empty_conversation(
self, responses_impl_with_conversations, mock_conversations_api
):
"""Test loading context from empty conversation."""
conv_id = "conv_empty"
input_text = "Hello"
mock_conversations_api.list.return_value = ConversationItemList(
data=[], first_id=None, has_more=False, last_id=None, object="list"
)
result = await responses_impl_with_conversations._load_conversation_context(conv_id, input_text)
assert len(result) == 1
assert result[0].role == "user"
assert result[0].content == input_text
class TestMessageSyncing:
"""Test message syncing to conversations."""
async def test_sync_response_to_conversation_simple(
self, responses_impl_with_conversations, mock_conversations_api
):
"""Test syncing simple response to conversation."""
conv_id = "conv_test123"
input_text = "What are the 5 Ds of dodgeball?"
# mock response
mock_response = OpenAIResponseObject(
id="resp_123",
created_at=1234567890,
model="test-model",
object="response",
output=[
OpenAIResponseMessage(
id="msg_response",
content=[
OpenAIResponseOutputMessageContentOutputText(
text="The 5 Ds are: Dodge, Duck, Dip, Dive, and Dodge.", type="output_text", annotations=[]
)
],
role="assistant",
status="completed",
type="message",
)
],
status="completed",
)
await responses_impl_with_conversations._sync_response_to_conversation(conv_id, input_text, mock_response)
# should call add_items with user input and assistant response
mock_conversations_api.add_items.assert_called_once()
call_args = mock_conversations_api.add_items.call_args
assert call_args[0][0] == conv_id # conversation_id
items = call_args[0][1] # conversation_items
assert len(items) == 2
# User message
assert items[0].type == "message"
assert items[0].role == "user"
assert items[0].content[0].type == "input_text"
assert items[0].content[0].text == input_text
# Assistant message
assert items[1].type == "message"
assert items[1].role == "assistant"
async def test_sync_response_to_conversation_api_error(
self, responses_impl_with_conversations, mock_conversations_api
):
"""Test syncing when conversations API call fails."""
conv_id = "conv_test123"
mock_response = OpenAIResponseObject(
id="resp_123", created_at=1234567890, model="test-model", object="response", output=[], status="completed"
)
# Mock API error
mock_conversations_api.add_items.side_effect = Exception("API Error")
# Should not raise exception (graceful failure)
result = await responses_impl_with_conversations._sync_response_to_conversation(conv_id, "Hello", mock_response)
assert result is None
class TestIntegrationWorkflow:
"""Integration tests for the full conversation workflow."""
async def test_create_response_with_valid_conversation(
self, responses_impl_with_conversations, mock_conversations_api
):
"""Test creating a response with a valid conversation parameter."""
mock_conversations_api.get_conversation.return_value = Conversation(
id="conv_test123", created_at=1234567890, metadata={}, object="conversation"
)
mock_conversations_api.list.return_value = ConversationItemList(
data=[], first_id=None, has_more=False, last_id=None, object="list"
)
async def mock_streaming_response(*args, **kwargs):
mock_response = OpenAIResponseObject(
id="resp_test123",
created_at=1234567890,
model="test-model",
object="response",
output=[
OpenAIResponseMessage(
id="msg_response",
content=[
OpenAIResponseOutputMessageContentOutputText(
text="Test response", type="output_text", annotations=[]
)
],
role="assistant",
status="completed",
type="message",
)
],
status="completed",
)
yield OpenAIResponseObjectStreamResponseCompleted(response=mock_response, type="response.completed")
responses_impl_with_conversations._create_streaming_response = mock_streaming_response
input_text = "Hello, how are you?"
conversation_id = "conv_test123"
response = await responses_impl_with_conversations.create_openai_response(
input=input_text, model="test-model", conversation=conversation_id, stream=False
)
assert response is not None
assert response.id == "resp_test123"
mock_conversations_api.get_conversation.assert_called_once_with(conversation_id)
mock_conversations_api.list.assert_called_once_with(conversation_id, order="asc")
# Note: conversation sync happens in the streaming response flow,
# which is complex to mock fully in this unit test
async def test_create_response_with_invalid_conversation_id(self, responses_impl_with_conversations):
"""Test creating a response with an invalid conversation ID."""
with pytest.raises(InvalidConversationIdError) as exc_info:
await responses_impl_with_conversations.create_openai_response(
input="Hello", model="test-model", conversation="invalid_id", stream=False
)
assert "Expected an ID that begins with 'conv_'" in str(exc_info.value)
async def test_create_response_with_nonexistent_conversation(
self, responses_impl_with_conversations, mock_conversations_api
):
"""Test creating a response with a non-existent conversation."""
mock_conversations_api.get_conversation.side_effect = ConversationNotFoundError("conv_nonexistent")
with pytest.raises(ConversationNotFoundError) as exc_info:
await responses_impl_with_conversations.create_openai_response(
input="Hello", model="test-model", conversation="conv_nonexistent", stream=False
)
assert "not found" in str(exc_info.value)

15
tests/unit/providers/agents/meta_reference/test_openai_responses.py
View file

@ -83,9 +83,21 @@ def mock_vector_io_api():
return vector_io_api
@pytest.fixture
def mock_conversations_api():
"""Mock conversations API for testing."""
mock_api = AsyncMock()
return mock_api
@pytest.fixture
def openai_responses_impl(
mock_inference_api, mock_tool_groups_api, mock_tool_runtime_api, mock_responses_store, mock_vector_io_api
mock_inference_api,
mock_tool_groups_api,
mock_tool_runtime_api,
mock_responses_store,
mock_vector_io_api,
mock_conversations_api,
):
return OpenAIResponsesImpl(
inference_api=mock_inference_api,
@ -93,6 +105,7 @@ def openai_responses_impl(
tool_runtime_api=mock_tool_runtime_api,
responses_store=mock_responses_store,
vector_io_api=mock_vector_io_api,
conversations_api=mock_conversations_api,
)