[Bugfix] properly handle nested json with llama3 tool parser (#27701)

Signed-off-by: Aydin Abiar <aydin@anyscale.com>
Signed-off-by: Aydin Abiar <62435714+Aydin-ab@users.noreply.github.com>
Co-authored-by: Aydin Abiar <aydin@anyscale.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
Co-authored-by: Chauncey <chaunceyjiang@gmail.com>
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Aydin Abiar 2025-11-24 07:28:51 -08:00 committed by GitHub
parent e48b2e6848
commit 656516c315
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2 changed files with 203 additions and 41 deletions

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@ -1,6 +1,8 @@
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from unittest.mock import MagicMock, patch
import pytest
from vllm.entrypoints.openai.protocol import ExtractedToolCallInformation
@ -132,3 +134,129 @@ def test_extract_tool_calls_multiple_json_with_surrounding_text(parser):
assert result.tool_calls[0].function.name == "searchTool"
assert result.tool_calls[1].function.name == "getOpenIncidentsTool"
assert result.tool_calls[2].function.name == "searchTool"
def test_extract_tool_calls_deeply_nested_json(parser):
# Test with deeply nested JSON parameters (5 levels)
model_output = (
'{"name": "complexTool", '
'"parameters": {'
'"level1": {'
'"level2": {'
'"level3": {'
'"level4": {'
'"value": "deep"'
"}}}}}}"
)
result = parser.extract_tool_calls(model_output, None)
assert result.tools_called is True
assert len(result.tool_calls) == 1
assert result.tool_calls[0].function.name == "complexTool"
# Verify the nested structure is preserved in the arguments
import json
args = json.loads(result.tool_calls[0].function.arguments)
assert args["level1"]["level2"]["level3"]["level4"]["value"] == "deep"
def test_extract_tool_calls_multiple_with_deep_nesting(parser):
# Test with multiple tool calls where some have deeply nested parameters
model_output = (
'{"name": "simpleTool", "parameters": {"value": "test"}}; '
'{"name": "complexTool", "parameters": '
'{"config": {"database": {"connection": {"pool": {"size": 10}}}}}}'
)
result = parser.extract_tool_calls(model_output, None)
assert result.tools_called is True
assert len(result.tool_calls) == 2
# Check first tool call
assert result.tool_calls[0].function.name == "simpleTool"
import json
args0 = json.loads(result.tool_calls[0].function.arguments)
assert args0["value"] == "test"
# Check second tool call with deep nesting
assert result.tool_calls[1].function.name == "complexTool"
args1 = json.loads(result.tool_calls[1].function.arguments)
assert args1["config"]["database"]["connection"]["pool"]["size"] == 10
def test_extract_tool_calls_with_quotes_and_brackets_in_string(parser):
# Test with quotes and brackets inside quoted string values
model_output = (
'{"name": "searchTool", '
'"parameters": {'
'"query": "test {value} [complex]",'
'"nested": {"inner": "more {brackets}"}'
"}}"
)
result = parser.extract_tool_calls(model_output, None)
assert result.tools_called is True
assert len(result.tool_calls) == 1
assert result.tool_calls[0].function.name == "searchTool"
# Verify the string values are preserved including brackets and quotes
import json
args = json.loads(result.tool_calls[0].function.arguments)
assert args["query"] == "test {value} [complex]"
assert args["nested"]["inner"] == "more {brackets}"
def test_extract_tool_calls_with_escaped_quotes_in_nested_json(parser):
# Test with escaped quotes in deeply nested JSON
model_output = (
'{"name": "parserTool", "parameters": {"text": "He said \\"Hello {world}\\""}}'
)
result = parser.extract_tool_calls(model_output, None)
assert result.tools_called is True
assert len(result.tool_calls) == 1
assert result.tool_calls[0].function.name == "parserTool"
# Verify escaped quotes are preserved
import json
args = json.loads(result.tool_calls[0].function.arguments)
assert args["text"] == 'He said "Hello {world}"'
def test_extract_tool_calls_missing_name_key(parser):
# Test that missing "name" key returns content
model_output = '{"parameters": {}}'
result = parser.extract_tool_calls(model_output, None)
assert result.tools_called is False
assert len(result.tool_calls) == 0
assert result.content == model_output
def test_extract_tool_calls_missing_parameters_and_arguments_key(parser):
# Test that missing both "parameters" and "arguments" keys returns content
model_output = '{"name": "toolWithoutParams"}'
result = parser.extract_tool_calls(model_output, None)
assert result.tools_called is False
assert len(result.tool_calls) == 0
assert result.content == model_output
def test_regex_timeout_handling(parser):
"""Test regex timeout is handled gracefully"""
fake_problematic_input = "{hello world[A(A=" + "\t)A(A=,\t" * 2
# create a mock regex that raises TimeoutError
mock_regex = MagicMock()
mock_regex.finditer.side_effect = TimeoutError("Regex timeout")
with patch.object(parser, "tool_call_start_regex", mock_regex):
result = parser.extract_tool_calls(fake_problematic_input, None)
# should treat as regular text when regex times out
assert result.content == fake_problematic_input
assert result.tools_called is False
assert len(result.tool_calls) == 0
mock_regex.finditer.assert_called_once()

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@ -9,6 +9,7 @@ import regex as re
from partial_json_parser.core.options import Allow
from transformers import PreTrainedTokenizerBase
import vllm.envs as envs
from vllm.entrypoints.chat_utils import make_tool_call_id
from vllm.entrypoints.openai.protocol import (
ChatCompletionRequest,
@ -56,12 +57,10 @@ class Llama3JsonToolParser(ToolParser):
self.bot_token_id = tokenizer.encode(self.bot_token, add_special_tokens=False)[
0
]
# Updated regex to match multiple JSONs separated by semicolons
# This pattern is more robust and can handle nested JSON objects
self.tool_call_regex = re.compile(
r"{[^{}]*(?:{[^{}]*}[^{}]*)*}(?:\s*;\s*{[^{}]*(?:{[^{}]*}[^{}]*)*})*",
re.DOTALL,
)
# Simple regex to find opening braces - we'll use JSON decoder for parsing
# This handles arbitrary nesting depth correctly
self.tool_call_start_regex = re.compile(r"\{")
self.json_decoder = json.JSONDecoder()
def extract_tool_calls(
self, model_output: str, request: ChatCompletionRequest
@ -77,49 +76,84 @@ class Llama3JsonToolParser(ToolParser):
tools_called=False, tool_calls=[], content=model_output
)
# Find JSON object(s) in the text using regex
match = self.tool_call_regex.search(model_output)
if not match:
# Keep track of the end index of the last parsed JSON object
# so we don't parse inner brackets
end_index = -1
tool_calls: list[ToolCall] = []
try:
for match in self.tool_call_start_regex.finditer(
model_output, timeout=envs.VLLM_TOOL_PARSE_REGEX_TIMEOUT_SECONDS
):
start_index = match.start()
# Skip if this brace is inside a previously parsed JSON object
if start_index <= end_index:
continue
try:
obj, json_end_index = self.json_decoder.raw_decode(
model_output[start_index:]
)
end_index = start_index + json_end_index
# raise KeyError if missing
name = obj["name"]
arguments_or_params = (
obj["arguments"] if "arguments" in obj else obj["parameters"]
)
tool_calls.append(
ToolCall(
type="function",
function=FunctionCall(
name=name,
# function call args are JSON but as a string
arguments=json.dumps(
arguments_or_params, ensure_ascii=False
),
),
)
)
except KeyError as e:
# Missing required key
missing_key = str(e).strip("'\"")
logger.exception(
"Couldn't extract tool call from JSON response. "
"Required key '%s' not present. "
"Returning output in content with empty tool calls.",
missing_key,
)
return ExtractedToolCallInformation(
tools_called=False, tool_calls=[], content=model_output
)
except Exception:
# Any other error during parsing
logger.exception(
"Error in extracting tool call from response. "
"Returning output in content with empty tool calls"
)
return ExtractedToolCallInformation(
tools_called=False, tool_calls=[], content=model_output
)
except TimeoutError:
logger.warning("Regex timeout occurred when matching tool call pattern.")
logger.debug(
"Regex timeout occurred when matching user input: %s", model_output
)
return ExtractedToolCallInformation(
tools_called=False, tool_calls=[], content=model_output
)
try:
json_str = match.group(0)
# Split by semicolon and strip whitespace
json_objects = [obj.strip() for obj in json_str.split(";")]
tool_calls: list[ToolCall] = []
for json_obj in json_objects:
if not json_obj: # Skip empty strings
continue
obj = json.loads(json_obj)
tool_calls.append(
ToolCall(
type="function",
function=FunctionCall(
name=obj["name"],
# function call args are JSON but as a string
arguments=json.dumps(
obj["arguments"]
if "arguments" in obj
else obj["parameters"],
ensure_ascii=False,
),
),
)
)
# If we have valid tool calls, return them normally
if tool_calls:
return ExtractedToolCallInformation(
tools_called=True, tool_calls=tool_calls, content=None
)
except Exception:
logger.exception("Error in extracting tool call from response.")
# return information to just treat the tool call as regular JSON
return ExtractedToolCallInformation(
tools_called=False, tool_calls=[], content=model_output
)
# No valid tool calls found
return ExtractedToolCallInformation(
tools_called=False, tool_calls=[], content=model_output
)
def extract_tool_calls_streaming(
self,