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feat(openai-responses): Support multiple message roles in API inputs

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Also update the nesting to add multiple messages(where appropriate)
rather then a single message with multiple content parts.

Signed-off-by: Derek Higgins <derekh@redhat.com>
This commit is contained in:
Derek Higgins 2025-05-02 11:10:07 +01:00 • committed by Ben Browning
parent 1369b5858e
commit 150b9a0834
2 changed files with 83 additions and 14 deletions
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46
llama_stack/providers/inline/agents/meta_reference/openai_responses.py
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@ -34,8 +34,10 @@ from llama_stack.apis.inference.inference import (
OpenAIChatCompletionContentPartTextParam,
OpenAIChatCompletionToolCallFunction,
OpenAIChoice,
OpenAIDeveloperMessageParam,
OpenAIImageURL,
OpenAIMessageParam,
OpenAISystemMessageParam,
OpenAIToolMessageParam,
OpenAIUserMessageParam,
)
@ -77,6 +79,16 @@ async def _openai_choices_to_output_messages(choices: list[OpenAIChoice]) -> lis
return output_messages
async def _get_message_type_by_role(role: str):
role_to_type = {
"user": OpenAIUserMessageParam,
"system": OpenAISystemMessageParam,
"assistant": OpenAIAssistantMessageParam,
"developer": OpenAIDeveloperMessageParam,
}
return role_to_type.get(role)
class OpenAIResponsesImpl:
def __init__(
self,
@ -116,26 +128,32 @@ class OpenAIResponsesImpl:
if previous_response_id:
previous_response = await self.get_openai_response(previous_response_id)
messages.extend(await _previous_response_to_messages(previous_response))
# TODO: refactor this user_content parsing out into a separate method
user_content: str | list[OpenAIChatCompletionContentPartParam] = ""
content: str | list[OpenAIChatCompletionContentPartParam] = ""
if isinstance(input, list):
user_content = []
for user_input in input:
if isinstance(user_input.content, list):
for user_input_content in user_input.content:
if isinstance(user_input_content, OpenAIResponseInputMessageContentText):
user_content.append(OpenAIChatCompletionContentPartTextParam(text=user_input_content.text))
elif isinstance(user_input_content, OpenAIResponseInputMessageContentImage):
if user_input_content.image_url:
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=user_input_content.image_url, detail=user_input_content.detail
url=input_message_content.image_url, detail=input_message_content.detail
)
user_content.append(OpenAIChatCompletionContentPartImageParam(image_url=image_url))
content.append(OpenAIChatCompletionContentPartImageParam(image_url=image_url))
else:
user_content.append(OpenAIChatCompletionContentPartTextParam(text=user_input.content))
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:
user_content = input
messages.append(OpenAIUserMessageParam(content=user_content))
messages.append(OpenAIUserMessageParam(content=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(