llama-stack-mirror/tests/unit/providers/utils/inference/test_openai_compat.py
Ben Browning fd9d52564b fix: resolve BuiltinTools to strings for vllm tool_call messages
When the result of a ToolCall gets passed back into vLLM for the model
to handle the tool call result (as is often the case in agentic
tool-calling workflows), we forgot to handle the case where
BuiltinTool calls are not string values but instead instances of the
BuiltinTool enum. This fixes that, properly converting those enums to
string values before trying to serialize them into an OpenAI chat
completion request to vLLM.

PR #1931 fixed a bug where we weren't passing these tool calling
results back into vLLM, but as a side-effect it created this
serialization bug when using BuiltinTools.

Resolves #2070

Signed-off-by: Ben Browning <bbrownin@redhat.com>
2025-04-30 20:10:33 -04:00

69 lines
2.3 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.
import pytest
from llama_stack.apis.common.content_types import TextContentItem
from llama_stack.apis.inference.inference import CompletionMessage, UserMessage
from llama_stack.models.llama.datatypes import BuiltinTool, StopReason, ToolCall
from llama_stack.providers.utils.inference.openai_compat import convert_message_to_openai_dict
@pytest.mark.asyncio
async def test_convert_message_to_openai_dict():
message = UserMessage(content=[TextContentItem(text="Hello, world!")], role="user")
assert await convert_message_to_openai_dict(message) == {
"role": "user",
"content": [{"type": "text", "text": "Hello, world!"}],
}
# Test convert_message_to_openai_dict with a tool call
@pytest.mark.asyncio
async def test_convert_message_to_openai_dict_with_tool_call():
message = CompletionMessage(
content="",
tool_calls=[
ToolCall(call_id="123", tool_name="test_tool", arguments_json='{"foo": "bar"}', arguments={"foo": "bar"})
],
stop_reason=StopReason.end_of_turn,
)
openai_dict = await convert_message_to_openai_dict(message)
assert openai_dict == {
"role": "assistant",
"content": [{"type": "text", "text": ""}],
"tool_calls": [
{"id": "123", "type": "function", "function": {"name": "test_tool", "arguments": '{"foo": "bar"}'}}
],
}
@pytest.mark.asyncio
async def test_convert_message_to_openai_dict_with_builtin_tool_call():
message = CompletionMessage(
content="",
tool_calls=[
ToolCall(
call_id="123",
tool_name=BuiltinTool.brave_search,
arguments_json='{"foo": "bar"}',
arguments={"foo": "bar"},
)
],
stop_reason=StopReason.end_of_turn,
)
openai_dict = await convert_message_to_openai_dict(message)
assert openai_dict == {
"role": "assistant",
"content": [{"type": "text", "text": ""}],
"tool_calls": [
{"id": "123", "type": "function", "function": {"name": "brave_search", "arguments": '{"foo": "bar"}'}}
],
}