llama-stack-mirror/llama_stack/providers/utils/responses/responses_store.py
ehhuang 5844c2da68
feat: add list responses API (#2233)
# What does this PR do?
This is not part of the official OpenAI API, but we'll use this for the
logs UI.
In order to support more filtering options, I'm adopting the newly
introduced sql store in in place of the kv store.

## Test Plan
Added integration/unit tests.
2025-05-23 13:16:48 -07:00

98 lines
3.4 KiB
Python

# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from llama_stack.apis.agents import (
Order,
)
from llama_stack.apis.agents.openai_responses import (
ListOpenAIResponseObject,
OpenAIResponseInput,
OpenAIResponseObject,
OpenAIResponseObjectWithInput,
)
from llama_stack.distribution.utils.config_dirs import RUNTIME_BASE_DIR
from ..sqlstore.api import ColumnDefinition, ColumnType
from ..sqlstore.sqlstore import SqliteSqlStoreConfig, SqlStoreConfig, sqlstore_impl
class ResponsesStore:
def __init__(self, sql_store_config: SqlStoreConfig):
if not sql_store_config:
sql_store_config = SqliteSqlStoreConfig(
db_path=(RUNTIME_BASE_DIR / "sqlstore.db").as_posix(),
)
self.sql_store = sqlstore_impl(sql_store_config)
async def initialize(self):
"""Create the necessary tables if they don't exist."""
await self.sql_store.create_table(
"openai_responses",
{
"id": ColumnDefinition(type=ColumnType.STRING, primary_key=True),
"created_at": ColumnType.INTEGER,
"response_object": ColumnType.JSON,
"model": ColumnType.STRING,
},
)
async def store_response_object(
self, response_object: OpenAIResponseObject, input: list[OpenAIResponseInput]
) -> None:
data = response_object.model_dump()
data["input"] = [input_item.model_dump() for input_item in input]
await self.sql_store.insert(
"openai_responses",
{
"id": data["id"],
"created_at": data["created_at"],
"model": data["model"],
"response_object": data,
},
)
async def list_responses(
self,
after: str | None = None,
limit: int | None = 50,
model: str | None = None,
order: Order | None = Order.desc,
) -> ListOpenAIResponseObject:
"""
List responses from the database.
:param after: The ID of the last response to return.
:param limit: The maximum number of responses to return.
:param model: The model to filter by.
:param order: The order to sort the responses by.
"""
# TODO: support after
if after:
raise NotImplementedError("After is not supported for SQLite")
if not order:
order = Order.desc
rows = await self.sql_store.fetch_all(
"openai_responses",
where={"model": model} if model else None,
order_by=[("created_at", order.value)],
limit=limit,
)
data = [OpenAIResponseObjectWithInput(**row["response_object"]) for row in rows]
return ListOpenAIResponseObject(
data=data,
# TODO: implement has_more
has_more=False,
first_id=data[0].id if data else "",
last_id=data[-1].id if data else "",
)
async def get_response_object(self, response_id: str) -> OpenAIResponseObjectWithInput:
row = await self.sql_store.fetch_one("openai_responses", where={"id": response_id})
if not row:
raise ValueError(f"Response with id {response_id} not found") from None
return OpenAIResponseObjectWithInput(**row["response_object"])