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Original file line number Diff line number Diff line change
@@ -1,6 +1,7 @@
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project

import datetime
from typing import Union

import openai # use the official client for correctness check
Expand Down Expand Up @@ -284,3 +285,62 @@ async def test_tool_id_kimi_k2(k2_client: openai.AsyncOpenAI, model_name: str,
output.extend(chunk.choices[0].delta.tool_calls)
for o in output:
assert o.id is None or o.id == 'functions.get_current_weather:0'


@pytest.mark.asyncio
@pytest.mark.parametrize("model_name", [MODEL_NAME])
@pytest.mark.parametrize("arguments", ["{}", ''])
async def test_no_args_tool_call(client: openai.AsyncOpenAI, model_name: str,
arguments: str):
# Step 1: Define a tool that requires no parameters
tools = [{
"type": "function",
"function": {
"name": "get_current_time",
"description":
"Get the current date and time. No parameters needed.",
"parameters": {
"type": "object",
"properties": {}, # No parameters
"required": [] # No required fields
}
}
}]
messages = [{"role": "user", "content": "What time is it now?"}]
# Step 2: Send user message and let model decide whether to call the tool
response = await client.chat.completions.create(
model=model_name,
messages=messages,
tools=tools,
tool_choice="auto" # Let model choose automatically
)

# Step 3: Check if model wants to call a tool
message = response.choices[0].message
if message.tool_calls:
# Get the first tool call
tool_call = message.tool_calls[0]
tool_name = tool_call.function.name
# Step 4: Execute the tool locally (no parameters)
if tool_name == "get_current_time":
# Test both empty string and "{}" for no-arg tool calls
tool_call.function.arguments = arguments
messages.append(message)
current_time = datetime.datetime.now()
result = current_time.isoformat()
messages.append({
"role": "tool",
"tool_call_id": tool_call.id,
"content": result,
})
# Step 5: Send tool result back to model to continue conversation
final_response = await client.chat.completions.create(
model=model_name,
messages=messages,
)
# Output final natural language response
assert final_response.choices[0].message.content is not None

else:
# No tool called — just print model's direct reply
assert message.content is not None
8 changes: 5 additions & 3 deletions vllm/entrypoints/chat_utils.py
Original file line number Diff line number Diff line change
Expand Up @@ -1450,9 +1450,11 @@ def _postprocess_messages(messages: list[ConversationMessage]) -> None:
and isinstance(message["tool_calls"], list)
):
for item in message["tool_calls"]:
item["function"]["arguments"] = json.loads(
item["function"]["arguments"]
)
# if arguments is None or empty string, set to {}
if content := item["function"].get("arguments"):
item["function"]["arguments"] = json.loads(content)
else:
item["function"]["arguments"] = {}


def parse_chat_messages(
Expand Down