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fix: Responses API previous_response input items

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This adds storing of input items with previous responses and then
restores those input items to prepend to the user's messages list when
using conversation state.

I missed this in the initial implementation, but it makes sense that we
have to store the input items from previous responses so that we can
reconstruct the proper messages stack for multi-turn conversations -
just the output from previous responses isn't enough context for the
models to follow the turns and the original instructions.

Signed-off-by: Ben Browning <bbrownin@redhat.com>
This commit is contained in:
Ben Browning 2025-04-30 12:25:38 -04:00
parent 150b9a0834
commit 5b2e850754
2 changed files with 104 additions and 10 deletions
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17
llama_stack/apis/agents/openai_responses.py
View file

@ -131,3 +131,20 @@ OpenAIResponseInputTool = Annotated[
Field(discriminator="type"),
]
register_schema(OpenAIResponseInputTool, name="OpenAIResponseInputTool")
@json_schema_type
class OpenAIResponseInputItemMessage(OpenAIResponseInputMessage):
id: str
@json_schema_type
class OpenAIResponseInputItemList(BaseModel):
data: list[OpenAIResponseInputItemMessage]
object: Literal["list"] = "list"
@json_schema_type
class OpenAIResponsePreviousResponseWithInputItems(BaseModel):
input_items: OpenAIResponseInputItemList
response: OpenAIResponseObject

97
llama_stack/providers/inline/agents/meta_reference/openai_responses.py
View file

@ -12,7 +12,10 @@ from typing import cast
from openai.types.chat import ChatCompletionToolParam
from llama_stack.apis.agents.openai_responses import (
OpenAIResponseInputItemList,
OpenAIResponseInputItemMessage,
OpenAIResponseInputMessage,
OpenAIResponseInputMessageContent,
OpenAIResponseInputMessageContentImage,
OpenAIResponseInputMessageContentText,
OpenAIResponseInputTool,
@ -24,6 +27,7 @@ from llama_stack.apis.agents.openai_responses import (
OpenAIResponseOutputMessage,
OpenAIResponseOutputMessageContentOutputText,
OpenAIResponseOutputMessageWebSearchToolCall,
OpenAIResponsePreviousResponseWithInputItems,
)
from llama_stack.apis.inference.inference import (
Inference,
@ -52,9 +56,56 @@ logger = get_logger(name=__name__, category="openai_responses")
OPENAI_RESPONSES_PREFIX = "openai_responses:"
async def _previous_response_to_messages(previous_response: OpenAIResponseObject) -> list[OpenAIMessageParam]:
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,
) -> list[OpenAIMessageParam]:
messages: list[OpenAIMessageParam] = []
for output_message in previous_response.output:
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))
return messages
@ -102,15 +153,19 @@ class OpenAIResponsesImpl:
self.tool_groups_api = tool_groups_api
self.tool_runtime_api = tool_runtime_api
async def get_openai_response(
self,
id: str,
) -> OpenAIResponseObject:
async def _get_previous_response_with_input(self, id: str) -> OpenAIResponsePreviousResponseWithInputItems:
key = f"{OPENAI_RESPONSES_PREFIX}{id}"
response_json = await self.persistence_store.get(key=key)
if response_json is None:
raise ValueError(f"OpenAI response with id '{id}' not found")
return OpenAIResponseObject.model_validate_json(response_json)
return OpenAIResponsePreviousResponseWithInputItems.model_validate_json(response_json)
async def get_openai_response(
self,
id: str,
) -> OpenAIResponseObject:
response_with_input = await self._get_previous_response_with_input(id)
return response_with_input.response
async def create_openai_response(
self,
@ -126,8 +181,8 @@ class OpenAIResponsesImpl:
messages: list[OpenAIMessageParam] = []
if previous_response_id:
previous_response = await self.get_openai_response(previous_response_id)
messages.extend(await _previous_response_to_messages(previous_response))
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] = ""
@ -216,10 +271,32 @@ class OpenAIResponsesImpl:
if store:
# Store in kvstore
if isinstance(input, str):
# synthesize a message from the input string
input_content = OpenAIResponseInputMessageContentText(text=input)
input_content_item = OpenAIResponseInputItemMessage(
role="user",
content=[input_content],
id=f"msg_{uuid.uuid4()}",
)
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())
)
input_items = OpenAIResponseInputItemList(data=input_items_data)
prev_response = OpenAIResponsePreviousResponseWithInputItems(
input_items=input_items,
response=response,
)
key = f"{OPENAI_RESPONSES_PREFIX}{response.id}"
await self.persistence_store.set(
key=key,
value=response.model_dump_json(),
value=prev_response.model_dump_json(),
)
if stream: