forked from phoenix-oss/llama-stack-mirror
feat: add list responses API (#2233)
# What does this PR do? This is not part of the official OpenAI API, but we'll use this for the logs UI. In order to support more filtering options, I'm adopting the newly introduced sql store in in place of the kv store. ## Test Plan Added integration/unit tests.
This commit is contained in:
ehhuang
GitHub
parent
6463ee7633
commit
5844c2da68
47 changed files with 704 additions and 77 deletions
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@ -4,7 +4,7 @@
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from unittest.mock import AsyncMock, patch
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from unittest.mock import AsyncMock
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import pytest
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from openai.types.chat.chat_completion_chunk import (
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@ -16,12 +16,11 @@ from openai.types.chat.chat_completion_chunk import (
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)
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from llama_stack.apis.agents.openai_responses import (
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OpenAIResponseInputItemList,
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OpenAIResponseInputMessageContentText,
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OpenAIResponseInputToolFunction,
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OpenAIResponseInputToolWebSearch,
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OpenAIResponseMessage,
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OpenAIResponseObject,
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OpenAIResponseObjectWithInput,
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OpenAIResponseOutputMessageContentOutputText,
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OpenAIResponseOutputMessageWebSearchToolCall,
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)
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@ -33,19 +32,12 @@ from llama_stack.apis.inference.inference import (
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)
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from llama_stack.apis.tools.tools import Tool, ToolGroups, ToolInvocationResult, ToolParameter, ToolRuntime
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from llama_stack.providers.inline.agents.meta_reference.openai_responses import (
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OpenAIResponsePreviousResponseWithInputItems,
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OpenAIResponsesImpl,
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)
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from llama_stack.providers.utils.kvstore import KVStore
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from llama_stack.providers.utils.responses.responses_store import ResponsesStore
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from tests.unit.providers.agents.meta_reference.fixtures import load_chat_completion_fixture
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@pytest.fixture
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def mock_kvstore():
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kvstore = AsyncMock(spec=KVStore)
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return kvstore
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@pytest.fixture
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def mock_inference_api():
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inference_api = AsyncMock()
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@ -65,12 +57,18 @@ def mock_tool_runtime_api():
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@pytest.fixture
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def openai_responses_impl(mock_kvstore, mock_inference_api, mock_tool_groups_api, mock_tool_runtime_api):
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def mock_responses_store():
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responses_store = AsyncMock(spec=ResponsesStore)
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return responses_store
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@pytest.fixture
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def openai_responses_impl(mock_inference_api, mock_tool_groups_api, mock_tool_runtime_api, mock_responses_store):
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return OpenAIResponsesImpl(
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persistence_store=mock_kvstore,
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inference_api=mock_inference_api,
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tool_groups_api=mock_tool_groups_api,
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tool_runtime_api=mock_tool_runtime_api,
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responses_store=mock_responses_store,
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)
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@ -100,7 +98,7 @@ async def test_create_openai_response_with_string_input(openai_responses_impl, m
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stream=False,
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temperature=0.1,
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)
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openai_responses_impl.persistence_store.set.assert_called_once()
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openai_responses_impl.responses_store.store_response_object.assert_called_once()
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assert result.model == model
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assert len(result.output) == 1
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assert isinstance(result.output[0], OpenAIResponseMessage)
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@ -167,7 +165,7 @@ async def test_create_openai_response_with_string_input_with_tools(openai_respon
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kwargs={"query": "What is the capital of Ireland?"},
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)
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openai_responses_impl.persistence_store.set.assert_called_once()
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openai_responses_impl.responses_store.store_response_object.assert_called_once()
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# Check that we got the content from our mocked tool execution result
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assert len(result.output) >= 1
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@ -292,8 +290,7 @@ async def test_prepend_previous_response_none(openai_responses_impl):
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@pytest.mark.asyncio
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@patch.object(OpenAIResponsesImpl, "_get_previous_response_with_input")
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async def test_prepend_previous_response_basic(get_previous_response_with_input, openai_responses_impl):
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async def test_prepend_previous_response_basic(openai_responses_impl, mock_responses_store):
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"""Test prepending a basic previous response to a new response."""
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input_item_message = OpenAIResponseMessage(
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@ -301,25 +298,21 @@ async def test_prepend_previous_response_basic(get_previous_response_with_input,
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content=[OpenAIResponseInputMessageContentText(text="fake_previous_input")],
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role="user",
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)
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input_items = OpenAIResponseInputItemList(data=[input_item_message])
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response_output_message = OpenAIResponseMessage(
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id="123",
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content=[OpenAIResponseOutputMessageContentOutputText(text="fake_response")],
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status="completed",
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role="assistant",
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)
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response = OpenAIResponseObject(
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previous_response = OpenAIResponseObjectWithInput(
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created_at=1,
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id="resp_123",
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model="fake_model",
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output=[response_output_message],
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status="completed",
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input=[input_item_message],
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)
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previous_response = OpenAIResponsePreviousResponseWithInputItems(
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input_items=input_items,
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response=response,
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)
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get_previous_response_with_input.return_value = previous_response
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mock_responses_store.get_response_object.return_value = previous_response
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input = await openai_responses_impl._prepend_previous_response("fake_input", "resp_123")
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@ -336,16 +329,13 @@ async def test_prepend_previous_response_basic(get_previous_response_with_input,
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@pytest.mark.asyncio
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@patch.object(OpenAIResponsesImpl, "_get_previous_response_with_input")
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async def test_prepend_previous_response_web_search(get_previous_response_with_input, openai_responses_impl):
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async def test_prepend_previous_response_web_search(openai_responses_impl, mock_responses_store):
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"""Test prepending a web search previous response to a new response."""
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input_item_message = OpenAIResponseMessage(
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id="123",
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content=[OpenAIResponseInputMessageContentText(text="fake_previous_input")],
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role="user",
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)
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input_items = OpenAIResponseInputItemList(data=[input_item_message])
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output_web_search = OpenAIResponseOutputMessageWebSearchToolCall(
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id="ws_123",
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status="completed",
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@ -356,18 +346,15 @@ async def test_prepend_previous_response_web_search(get_previous_response_with_i
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status="completed",
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role="assistant",
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)
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response = OpenAIResponseObject(
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response = OpenAIResponseObjectWithInput(
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created_at=1,
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id="resp_123",
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model="fake_model",
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output=[output_web_search, output_message],
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status="completed",
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input=[input_item_message],
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)
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previous_response = OpenAIResponsePreviousResponseWithInputItems(
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input_items=input_items,
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response=response,
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)
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get_previous_response_with_input.return_value = previous_response
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mock_responses_store.get_response_object.return_value = response
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input_messages = [OpenAIResponseMessage(content="fake_input", role="user")]
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input = await openai_responses_impl._prepend_previous_response(input_messages, "resp_123")
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@ -464,9 +451,8 @@ async def test_create_openai_response_with_instructions_and_multiple_messages(
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@pytest.mark.asyncio
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@patch.object(OpenAIResponsesImpl, "_get_previous_response_with_input")
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async def test_create_openai_response_with_instructions_and_previous_response(
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get_previous_response_with_input, openai_responses_impl, mock_inference_api
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openai_responses_impl, mock_responses_store, mock_inference_api
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):
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"""Test prepending both instructions and previous response."""
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@ -475,25 +461,21 @@ async def test_create_openai_response_with_instructions_and_previous_response(
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content="Name some towns in Ireland",
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role="user",
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)
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input_items = OpenAIResponseInputItemList(data=[input_item_message])
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response_output_message = OpenAIResponseMessage(
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id="123",
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content="Galway, Longford, Sligo",
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status="completed",
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role="assistant",
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)
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response = OpenAIResponseObject(
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response = OpenAIResponseObjectWithInput(
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created_at=1,
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id="resp_123",
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model="fake_model",
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output=[response_output_message],
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status="completed",
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input=[input_item_message],
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)
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previous_response = OpenAIResponsePreviousResponseWithInputItems(
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input_items=input_items,
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response=response,
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)
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get_previous_response_with_input.return_value = previous_response
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mock_responses_store.get_response_object.return_value = response
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model = "meta-llama/Llama-3.1-8B-Instruct"
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instructions = "You are a geography expert. Provide concise answers."
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@ -511,7 +493,7 @@ async def test_create_openai_response_with_instructions_and_previous_response(
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sent_messages = call_args.kwargs["messages"]
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# Check that instructions were prepended as a system message
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assert len(sent_messages) == 4
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assert len(sent_messages) == 4, sent_messages
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assert sent_messages[0].role == "system"
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assert sent_messages[0].content == instructions
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