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store prev messages

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# What does this PR do?


## Test Plan
This commit is contained in:
Eric Huang 2025-10-02 15:53:31 -07:00
parent 4819a2e0ee
commit 2ec9f8770e
7 changed files with 202 additions and 58 deletions
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70
llama_stack/providers/inline/agents/meta_reference/responses/openai_responses.py
View file

@ -8,7 +8,7 @@ import time
import uuid
from collections.abc import AsyncIterator
from pydantic import BaseModel
from pydantic import BaseModel, TypeAdapter
from llama_stack.apis.agents import Order
from llama_stack.apis.agents.openai_responses import (
@ -26,12 +26,16 @@ from llama_stack.apis.agents.openai_responses import (
)
from llama_stack.apis.inference import (
Inference,
OpenAIMessageParam,
OpenAISystemMessageParam,
)
from llama_stack.apis.tools import ToolGroups, ToolRuntime
from llama_stack.apis.vector_io import VectorIO
from llama_stack.log import get_logger
from llama_stack.providers.utils.responses.responses_store import ResponsesStore
from llama_stack.providers.utils.responses.responses_store import (
ResponsesStore,
_OpenAIResponseObjectWithInputAndMessages,
)
from .streaming import StreamingResponseOrchestrator
from .tool_executor import ToolExecutor
@ -72,26 +76,48 @@ class OpenAIResponsesImpl:
async def _prepend_previous_response(
self,
input: str | list[OpenAIResponseInput],
previous_response_id: str | None = None,
previous_response: _OpenAIResponseObjectWithInputAndMessages,
):
new_input_items = previous_response.input.copy()
new_input_items.extend(previous_response.output)
if isinstance(input, str):
new_input_items.append(OpenAIResponseMessage(content=input, role="user"))
else:
new_input_items.extend(input)
return new_input_items
async def _process_input_with_previous_response(
self,
input: str | list[OpenAIResponseInput],
previous_response_id: str | None,
) -> tuple[str | list[OpenAIResponseInput], list[OpenAIMessageParam]]:
"""Process input with optional previous response context.
Returns:
tuple: (all_input for storage, messages for chat completion)
"""
if previous_response_id:
previous_response_with_input = await self.responses_store.get_response_object(previous_response_id)
previous_response: _OpenAIResponseObjectWithInputAndMessages = (
await self.responses_store.get_response_object(previous_response_id)
)
all_input = await self._prepend_previous_response(input, previous_response)
# previous response input items
new_input_items = previous_response_with_input.input
# previous response output items
new_input_items.extend(previous_response_with_input.output)
# new input items from the current request
if isinstance(input, str):
new_input_items.append(OpenAIResponseMessage(content=input, role="user"))
if previous_response.messages:
# Use stored messages directly and convert only new input
message_adapter = TypeAdapter(list[OpenAIMessageParam])
messages = message_adapter.validate_python(previous_response.messages)
new_messages = await convert_response_input_to_chat_messages(input)
messages.extend(new_messages)
else:
new_input_items.extend(input)
# Backward compatibility: reconstruct from inputs
messages = await convert_response_input_to_chat_messages(all_input)
else:
all_input = input
messages = await convert_response_input_to_chat_messages(input)
input = new_input_items
return input
return all_input, messages
async def _prepend_instructions(self, messages, instructions):
if instructions:
@ -102,7 +128,7 @@ class OpenAIResponsesImpl:
response_id: str,
) -> OpenAIResponseObject:
response_with_input = await self.responses_store.get_response_object(response_id)
return OpenAIResponseObject(**{k: v for k, v in response_with_input.model_dump().items() if k != "input"})
return response_with_input.to_response_object()
async def list_openai_responses(
self,
@ -138,6 +164,7 @@ class OpenAIResponsesImpl:
self,
response: OpenAIResponseObject,
input: str | list[OpenAIResponseInput],
messages: list[OpenAIMessageParam],
) -> None:
new_input_id = f"msg_{uuid.uuid4()}"
if isinstance(input, str):
@ -165,6 +192,7 @@ class OpenAIResponsesImpl:
await self.responses_store.store_response_object(
response_object=response,
input=input_items_data,
messages=messages,
)
async def create_openai_response(
@ -224,8 +252,7 @@ class OpenAIResponsesImpl:
max_infer_iters: int | None = 10,
) -> AsyncIterator[OpenAIResponseObjectStream]:
# Input preprocessing
input = await self._prepend_previous_response(input, previous_response_id)
messages = await convert_response_input_to_chat_messages(input)
all_input, messages = await self._process_input_with_previous_response(input, previous_response_id)
await self._prepend_instructions(messages, instructions)
# Structured outputs
@ -265,7 +292,8 @@ class OpenAIResponsesImpl:
if store and final_response:
await self._store_response(
response=final_response,
input=input,
input=all_input,
messages=orchestrator.final_messages,
)
async def delete_openai_response(self, response_id: str) -> OpenAIDeleteResponseObject:

5
llama_stack/providers/inline/agents/meta_reference/responses/streaming.py
View file

@ -43,6 +43,7 @@ from llama_stack.apis.inference import (
OpenAIChatCompletion,
OpenAIChatCompletionToolCall,
OpenAIChoice,
OpenAIMessageParam,
)
from llama_stack.log import get_logger
@ -103,6 +104,8 @@ class StreamingResponseOrchestrator:
self.sequence_number = 0
# Store MCP tool mapping that gets built during tool processing
self.mcp_tool_to_server: dict[str, OpenAIResponseInputToolMCP] = {}
# Track final messages after all tool executions
self.final_messages: list[OpenAIMessageParam] = []
async def create_response(self) -> AsyncIterator[OpenAIResponseObjectStream]:
# Initialize output messages
@ -192,6 +195,8 @@ class StreamingResponseOrchestrator:
messages = next_turn_messages
self.final_messages = messages.copy() + [current_response.choices[0].message]
# Create final response
final_response = OpenAIResponseObject(
created_at=self.created_at,