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fix: Restore previous responses to input list, not messages

Browse source 
This adjusts the restoration of previous responses to prepend them to
the list of Responses API inputs instead of our converted list of Chat
Completion messages. This matches the expected behavior of the
Responses API, and I misinterpreted the nuances here in the initial implementation.

Signed-off-by: Ben Browning <bbrownin@redhat.com>
This commit is contained in:
Ben Browning 2025-05-02 11:08:09 -04:00
parent 5b2e850754
commit b90bb66f28
7 changed files with 428 additions and 364 deletions
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4
llama_stack/providers/inline/agents/meta_reference/agents.py
View file

@ -20,7 +20,7 @@ from llama_stack.apis.agents import (
AgentTurnCreateRequest,
AgentTurnResumeRequest,
Document,
OpenAIResponseInputMessage,
OpenAIResponseInput,
OpenAIResponseInputTool,
OpenAIResponseObject,
Session,
@ -311,7 +311,7 @@ class MetaReferenceAgentsImpl(Agents):
async def create_openai_response(
self,
input: str | list[OpenAIResponseInputMessage],
input: str | list[OpenAIResponseInput],
model: str,
previous_response_id: str | None = None,
store: bool | None = True,

160
llama_stack/providers/inline/agents/meta_reference/openai_responses.py
View file

@ -12,19 +12,17 @@ from typing import cast
from openai.types.chat import ChatCompletionToolParam
from llama_stack.apis.agents.openai_responses import (
OpenAIResponseInput,
OpenAIResponseInputItemList,
OpenAIResponseInputItemMessage,
OpenAIResponseInputMessage,
OpenAIResponseInputMessageContent,
OpenAIResponseInputMessageContentImage,
OpenAIResponseInputMessageContentText,
OpenAIResponseInputTool,
OpenAIResponseMessage,
OpenAIResponseObject,
OpenAIResponseObjectStream,
OpenAIResponseObjectStreamResponseCompleted,
OpenAIResponseObjectStreamResponseCreated,
OpenAIResponseOutput,
OpenAIResponseOutputMessage,
OpenAIResponseOutputMessageContentOutputText,
OpenAIResponseOutputMessageWebSearchToolCall,
OpenAIResponsePreviousResponseWithInputItems,
@ -56,62 +54,38 @@ logger = get_logger(name=__name__, category="openai_responses")
OPENAI_RESPONSES_PREFIX = "openai_responses:"
async def _convert_response_input_content_to_chat_content_parts(
input_content: list[OpenAIResponseInputMessageContent],
) -> list[OpenAIChatCompletionContentPartParam]:
"""
Convert a list of input content items to a list of chat completion content parts
"""
content_parts = []
for input_content_part in input_content:
if isinstance(input_content_part, OpenAIResponseInputMessageContentText):
content_parts.append(OpenAIChatCompletionContentPartTextParam(text=input_content_part.text))
elif isinstance(input_content_part, OpenAIResponseInputMessageContentImage):
if input_content_part.image_url:
image_url = OpenAIImageURL(url=input_content_part.image_url, detail=input_content_part.detail)
content_parts.append(OpenAIChatCompletionContentPartImageParam(image_url=image_url))
return content_parts
async def _convert_response_input_to_chat_user_content(
input: str | list[OpenAIResponseInputMessage],
) -> str | list[OpenAIChatCompletionContentPartParam]:
user_content: str | list[OpenAIChatCompletionContentPartParam] = ""
if isinstance(input, list):
user_content = []
for user_input in input:
if isinstance(user_input.content, list):
user_content.extend(await _convert_response_input_content_to_chat_content_parts(user_input.content))
else:
user_content.append(OpenAIChatCompletionContentPartTextParam(text=user_input.content))
else:
user_content = input
return user_content
async def _previous_response_to_messages(
previous_response: OpenAIResponsePreviousResponseWithInputItems,
async def _convert_response_input_to_chat_messages(
input: str | list[OpenAIResponseInput],
) -> list[OpenAIMessageParam]:
messages: list[OpenAIMessageParam] = []
for previous_message in previous_response.input_items.data:
previous_content = await _convert_response_input_content_to_chat_content_parts(previous_message.content)
if previous_message.role == "user":
converted_message = OpenAIUserMessageParam(content=previous_content)
elif previous_message.role == "assistant":
converted_message = OpenAIAssistantMessageParam(content=previous_content)
else:
# TODO: handle other message roles? unclear if system/developer roles are
# used in previous responses
continue
messages.append(converted_message)
for output_message in previous_response.response.output:
if isinstance(output_message, OpenAIResponseOutputMessage):
messages.append(OpenAIAssistantMessageParam(content=output_message.content[0].text))
content: str | list[OpenAIChatCompletionContentPartParam] = ""
if isinstance(input, list):
for input_message in input:
if isinstance(input_message.content, list):
content = []
for input_message_content in input_message.content:
if isinstance(input_message_content, OpenAIResponseInputMessageContentText):
content.append(OpenAIChatCompletionContentPartTextParam(text=input_message_content.text))
elif isinstance(input_message_content, OpenAIResponseInputMessageContentImage):
if input_message_content.image_url:
image_url = OpenAIImageURL(
url=input_message_content.image_url, detail=input_message_content.detail
)
content.append(OpenAIChatCompletionContentPartImageParam(image_url=image_url))
else:
content = input_message.content
message_type = await _get_message_type_by_role(input_message.role)
if message_type is None:
raise ValueError(
f"Llama Stack OpenAI Responses does not yet support message role '{input_message.role}' in this context"
)
messages.append(message_type(content=content))
else:
messages.append(OpenAIUserMessageParam(content=input))
return messages
async def _openai_choices_to_output_messages(choices: list[OpenAIChoice]) -> list[OpenAIResponseOutputMessage]:
async def _openai_choices_to_output_messages(choices: list[OpenAIChoice]) -> list[OpenAIResponseMessage]:
output_messages = []
for choice in choices:
output_content = ""
@ -121,10 +95,11 @@ async def _openai_choices_to_output_messages(choices: list[OpenAIChoice]) -> lis
output_content = choice.message.content.text
# TODO: handle image content
output_messages.append(
OpenAIResponseOutputMessage(
OpenAIResponseMessage(
id=f"msg_{uuid.uuid4()}",
content=[OpenAIResponseOutputMessageContentOutputText(text=output_content)],
status="completed",
role="assistant",
)
)
return output_messages
@ -160,6 +135,27 @@ class OpenAIResponsesImpl:
raise ValueError(f"OpenAI response with id '{id}' not found")
return OpenAIResponsePreviousResponseWithInputItems.model_validate_json(response_json)
async def _prepend_previous_response(
self, input: str | list[OpenAIResponseInput], previous_response_id: str | None = None
):
if previous_response_id:
previous_response_with_input = await self._get_previous_response_with_input(previous_response_id)
# previous response input items
new_input_items = previous_response_with_input.input_items.data
# previous response output items
new_input_items.extend(previous_response_with_input.response.output)
# new input items from the current request
if isinstance(input, str):
# Normalize input to a list of OpenAIResponseInputMessage objects
input = [OpenAIResponseMessage(content=input, role="user")]
new_input_items.extend(input)
input = new_input_items
return input
async def get_openai_response(
self,
id: str,
@ -169,7 +165,7 @@ class OpenAIResponsesImpl:
async def create_openai_response(
self,
input: str | list[OpenAIResponseInputMessage],
input: str | list[OpenAIResponseInput],
model: str,
previous_response_id: str | None = None,
store: bool | None = True,
@ -179,37 +175,8 @@ class OpenAIResponsesImpl:
):
stream = False if stream is None else stream
messages: list[OpenAIMessageParam] = []
if previous_response_id:
previous_response_with_input = await self._get_previous_response_with_input(previous_response_id)
messages.extend(await _previous_response_to_messages(previous_response_with_input))
# TODO: refactor this user_content parsing out into a separate method
content: str | list[OpenAIChatCompletionContentPartParam] = ""
if isinstance(input, list):
for input_message in input:
if isinstance(input_message.content, list):
content = []
for input_message_content in input_message.content:
if isinstance(input_message_content, OpenAIResponseInputMessageContentText):
content.append(OpenAIChatCompletionContentPartTextParam(text=input_message_content.text))
elif isinstance(input_message_content, OpenAIResponseInputMessageContentImage):
if input_message_content.image_url:
image_url = OpenAIImageURL(
url=input_message_content.image_url, detail=input_message_content.detail
)
content.append(OpenAIChatCompletionContentPartImageParam(image_url=image_url))
else:
content = input_message.content
message_type = await _get_message_type_by_role(input_message.role)
if message_type is None:
raise ValueError(
f"Llama Stack OpenAI Responses does not yet support message role '{input_message.role}' in this context"
)
messages.append(message_type(content=content))
else:
messages.append(OpenAIUserMessageParam(content=input))
input = await self._prepend_previous_response(input, previous_response_id)
messages = await _convert_response_input_to_chat_messages(input)
chat_tools = await self._convert_response_tools_to_chat_tools(tools) if tools else None
chat_response = await self.inference_api.openai_chat_completion(
model=model,
@ -272,22 +239,29 @@ class OpenAIResponsesImpl:
if store:
# Store in kvstore
new_input_id = f"msg_{uuid.uuid4()}"
if isinstance(input, str):
# synthesize a message from the input string
input_content = OpenAIResponseInputMessageContentText(text=input)
input_content_item = OpenAIResponseInputItemMessage(
input_content_item = OpenAIResponseMessage(
role="user",
content=[input_content],
id=f"msg_{uuid.uuid4()}",
id=new_input_id,
)
input_items_data = [input_content_item]
else:
# we already have a list of messages
input_items_data = []
for input_item in input:
input_items_data.append(
OpenAIResponseInputItemMessage(id=f"msg_{uuid.uuid4()}", **input_item.model_dump())
)
if isinstance(input_item, OpenAIResponseMessage):
# These may or may not already have an id, so dump to dict, check for id, and add if missing
input_item_dict = input_item.model_dump()
if "id" not in input_item_dict:
input_item_dict["id"] = new_input_id
input_items_data.append(OpenAIResponseMessage(**input_item_dict))
else:
input_items_data.append(input_item)
input_items = OpenAIResponseInputItemList(data=input_items_data)
prev_response = OpenAIResponsePreviousResponseWithInputItems(
input_items=input_items,