fix: Restore previous responses to input list, not messages

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>

llama_stack/apis/agents/agents.py

@@ -29,7 +29,7 @@ from llama_stack.apis.tools import ToolDef
 from llama_stack.schema_utils import json_schema_type, register_schema, webmethod
 
 from .openai_responses import (
-    OpenAIResponseInputMessage,
+    OpenAIResponseInput,
     OpenAIResponseInputTool,
     OpenAIResponseObject,
     OpenAIResponseObjectStream,
@@ -588,7 +588,7 @@ class Agents(Protocol):
     @webmethod(route="/openai/v1/responses", method="POST")
     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,

llama_stack/apis/agents/openai_responses.py

@@ -17,6 +17,28 @@ class OpenAIResponseError(BaseModel):
     message: str
 
 
+@json_schema_type
+class OpenAIResponseInputMessageContentText(BaseModel):
+    text: str
+    type: Literal["input_text"] = "input_text"
+
+
+@json_schema_type
+class OpenAIResponseInputMessageContentImage(BaseModel):
+    detail: Literal["low"] | Literal["high"] | Literal["auto"] = "auto"
+    type: Literal["input_image"] = "input_image"
+    # TODO: handle file_id
+    image_url: str | None = None
+
+
+# TODO: handle file content types
+OpenAIResponseInputMessageContent = Annotated[
+    OpenAIResponseInputMessageContentText | OpenAIResponseInputMessageContentImage,
+    Field(discriminator="type"),
+]
+register_schema(OpenAIResponseInputMessageContent, name="OpenAIResponseInputMessageContent")
+
+
 @json_schema_type
 class OpenAIResponseOutputMessageContentOutputText(BaseModel):
     text: str
@@ -31,13 +53,22 @@ register_schema(OpenAIResponseOutputMessageContent, name="OpenAIResponseOutputMe
 
 
 @json_schema_type
-class OpenAIResponseOutputMessage(BaseModel):
-    id: str
-    content: list[OpenAIResponseOutputMessageContent]
-    role: Literal["assistant"] = "assistant"
-    status: str
+class OpenAIResponseMessage(BaseModel):
+    """
+    Corresponds to the various Message types in the Responses API.
+    They are all under one type because the Responses API gives them all
+    the same "type" value, and there is no way to tell them apart in certain
+    scenarios.
+    """
+
+    content: str | list[OpenAIResponseInputMessageContent] | list[OpenAIResponseOutputMessageContent]
+    role: Literal["system"] | Literal["developer"] | Literal["user"] | Literal["assistant"]
     type: Literal["message"] = "message"
 
+    # The fields below are not used in all scenarios, but are required in others.
+    id: str | None = None
+    status: str | None = None
+
 
 @json_schema_type
 class OpenAIResponseOutputMessageWebSearchToolCall(BaseModel):
@@ -47,7 +78,7 @@ class OpenAIResponseOutputMessageWebSearchToolCall(BaseModel):
 
 
 OpenAIResponseOutput = Annotated[
-    OpenAIResponseOutputMessage | OpenAIResponseOutputMessageWebSearchToolCall,
+    OpenAIResponseMessage | OpenAIResponseOutputMessageWebSearchToolCall,
     Field(discriminator="type"),
 ]
 register_schema(OpenAIResponseOutput, name="OpenAIResponseOutput")
@@ -89,33 +120,15 @@ OpenAIResponseObjectStream = Annotated[
 register_schema(OpenAIResponseObjectStream, name="OpenAIResponseObjectStream")
 
 
-@json_schema_type
-class OpenAIResponseInputMessageContentText(BaseModel):
-    text: str
-    type: Literal["input_text"] = "input_text"
-
-
-@json_schema_type
-class OpenAIResponseInputMessageContentImage(BaseModel):
-    detail: Literal["low"] | Literal["high"] | Literal["auto"] = "auto"
-    type: Literal["input_image"] = "input_image"
-    # TODO: handle file_id
-    image_url: str | None = None
-
-
-# TODO: handle file content types
-OpenAIResponseInputMessageContent = Annotated[
-    OpenAIResponseInputMessageContentText | OpenAIResponseInputMessageContentImage,
-    Field(discriminator="type"),
+OpenAIResponseInput = Annotated[
+    # Responses API allows output messages to be passed in as input
+    OpenAIResponseOutputMessageWebSearchToolCall
+    |
+    # Fallback to the generic message type as a last resort
+    OpenAIResponseMessage,
+    Field(union_mode="left_to_right"),
 ]
-register_schema(OpenAIResponseInputMessageContent, name="OpenAIResponseInputMessageContent")
-
-
-@json_schema_type
-class OpenAIResponseInputMessage(BaseModel):
-    content: str | list[OpenAIResponseInputMessageContent]
-    role: Literal["system"] | Literal["developer"] | Literal["user"] | Literal["assistant"]
-    type: Literal["message"] | None = "message"
+register_schema(OpenAIResponseInput, name="OpenAIResponseInput")
 
 
 @json_schema_type
@@ -133,18 +146,11 @@ OpenAIResponseInputTool = Annotated[
 register_schema(OpenAIResponseInputTool, name="OpenAIResponseInputTool")
 
 
-@json_schema_type
-class OpenAIResponseInputItemMessage(OpenAIResponseInputMessage):
-    id: str
-
-
-@json_schema_type
 class OpenAIResponseInputItemList(BaseModel):
-    data: list[OpenAIResponseInputItemMessage]
+    data: list[OpenAIResponseInput]
     object: Literal["list"] = "list"
 
 
-@json_schema_type
 class OpenAIResponsePreviousResponseWithInputItems(BaseModel):
     input_items: OpenAIResponseInputItemList
     response: OpenAIResponseObject