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[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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@ -1,6 +1,8 @@
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# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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from unittest.mock import MagicMock, patch
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import pytest
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from vllm.entrypoints.openai.protocol import ExtractedToolCallInformation
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@ -132,3 +134,129 @@ def test_extract_tool_calls_multiple_json_with_surrounding_text(parser):
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assert result.tool_calls[0].function.name == "searchTool"
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assert result.tool_calls[1].function.name == "getOpenIncidentsTool"
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assert result.tool_calls[2].function.name == "searchTool"
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def test_extract_tool_calls_deeply_nested_json(parser):
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# Test with deeply nested JSON parameters (5 levels)
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model_output = (
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'{"name": "complexTool", '
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'"parameters": {'
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'"level1": {'
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'"level2": {'
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'"level3": {'
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'"level4": {'
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'"value": "deep"'
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"}}}}}}"
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)
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result = parser.extract_tool_calls(model_output, None)
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assert result.tools_called is True
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assert len(result.tool_calls) == 1
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assert result.tool_calls[0].function.name == "complexTool"
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# Verify the nested structure is preserved in the arguments
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import json
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args = json.loads(result.tool_calls[0].function.arguments)
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assert args["level1"]["level2"]["level3"]["level4"]["value"] == "deep"
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def test_extract_tool_calls_multiple_with_deep_nesting(parser):
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# Test with multiple tool calls where some have deeply nested parameters
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model_output = (
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'{"name": "simpleTool", "parameters": {"value": "test"}}; '
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'{"name": "complexTool", "parameters": '
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'{"config": {"database": {"connection": {"pool": {"size": 10}}}}}}'
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)
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result = parser.extract_tool_calls(model_output, None)
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assert result.tools_called is True
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assert len(result.tool_calls) == 2
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# Check first tool call
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assert result.tool_calls[0].function.name == "simpleTool"
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import json
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args0 = json.loads(result.tool_calls[0].function.arguments)
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assert args0["value"] == "test"
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# Check second tool call with deep nesting
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assert result.tool_calls[1].function.name == "complexTool"
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args1 = json.loads(result.tool_calls[1].function.arguments)
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assert args1["config"]["database"]["connection"]["pool"]["size"] == 10
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def test_extract_tool_calls_with_quotes_and_brackets_in_string(parser):
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# Test with quotes and brackets inside quoted string values
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model_output = (
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'{"name": "searchTool", '
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'"parameters": {'
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'"query": "test {value} [complex]",'
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'"nested": {"inner": "more {brackets}"}'
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"}}"
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)
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result = parser.extract_tool_calls(model_output, None)
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assert result.tools_called is True
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assert len(result.tool_calls) == 1
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assert result.tool_calls[0].function.name == "searchTool"
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# Verify the string values are preserved including brackets and quotes
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import json
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args = json.loads(result.tool_calls[0].function.arguments)
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assert args["query"] == "test {value} [complex]"
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assert args["nested"]["inner"] == "more {brackets}"
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def test_extract_tool_calls_with_escaped_quotes_in_nested_json(parser):
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# Test with escaped quotes in deeply nested JSON
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model_output = (
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'{"name": "parserTool", "parameters": {"text": "He said \\"Hello {world}\\""}}'
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)
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result = parser.extract_tool_calls(model_output, None)
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assert result.tools_called is True
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assert len(result.tool_calls) == 1
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assert result.tool_calls[0].function.name == "parserTool"
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# Verify escaped quotes are preserved
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import json
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args = json.loads(result.tool_calls[0].function.arguments)
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assert args["text"] == 'He said "Hello {world}"'
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def test_extract_tool_calls_missing_name_key(parser):
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# Test that missing "name" key returns content
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model_output = '{"parameters": {}}'
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result = parser.extract_tool_calls(model_output, None)
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assert result.tools_called is False
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assert len(result.tool_calls) == 0
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assert result.content == model_output
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def test_extract_tool_calls_missing_parameters_and_arguments_key(parser):
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# Test that missing both "parameters" and "arguments" keys returns content
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model_output = '{"name": "toolWithoutParams"}'
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result = parser.extract_tool_calls(model_output, None)
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assert result.tools_called is False
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assert len(result.tool_calls) == 0
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assert result.content == model_output
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def test_regex_timeout_handling(parser):
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"""Test regex timeout is handled gracefully"""
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fake_problematic_input = "{hello world[A(A=" + "\t)A(A=,\t" * 2
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# create a mock regex that raises TimeoutError
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mock_regex = MagicMock()
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mock_regex.finditer.side_effect = TimeoutError("Regex timeout")
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with patch.object(parser, "tool_call_start_regex", mock_regex):
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result = parser.extract_tool_calls(fake_problematic_input, None)
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# should treat as regular text when regex times out
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assert result.content == fake_problematic_input
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assert result.tools_called is False
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assert len(result.tool_calls) == 0
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mock_regex.finditer.assert_called_once()
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@ -9,6 +9,7 @@ import regex as re
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from partial_json_parser.core.options import Allow
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from transformers import PreTrainedTokenizerBase
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import vllm.envs as envs
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from vllm.entrypoints.chat_utils import make_tool_call_id
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from vllm.entrypoints.openai.protocol import (
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ChatCompletionRequest,
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@ -56,12 +57,10 @@ class Llama3JsonToolParser(ToolParser):
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self.bot_token_id = tokenizer.encode(self.bot_token, add_special_tokens=False)[
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0
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]
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# Updated regex to match multiple JSONs separated by semicolons
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# This pattern is more robust and can handle nested JSON objects
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self.tool_call_regex = re.compile(
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r"{[^{}]*(?:{[^{}]*}[^{}]*)*}(?:\s*;\s*{[^{}]*(?:{[^{}]*}[^{}]*)*})*",
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re.DOTALL,
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)
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# Simple regex to find opening braces - we'll use JSON decoder for parsing
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# This handles arbitrary nesting depth correctly
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self.tool_call_start_regex = re.compile(r"\{")
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self.json_decoder = json.JSONDecoder()
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def extract_tool_calls(
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self, model_output: str, request: ChatCompletionRequest
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@ -77,49 +76,84 @@ class Llama3JsonToolParser(ToolParser):
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tools_called=False, tool_calls=[], content=model_output
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)
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# Find JSON object(s) in the text using regex
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match = self.tool_call_regex.search(model_output)
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if not match:
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# Keep track of the end index of the last parsed JSON object
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# so we don't parse inner brackets
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end_index = -1
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tool_calls: list[ToolCall] = []
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try:
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for match in self.tool_call_start_regex.finditer(
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model_output, timeout=envs.VLLM_TOOL_PARSE_REGEX_TIMEOUT_SECONDS
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):
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start_index = match.start()
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# Skip if this brace is inside a previously parsed JSON object
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if start_index <= end_index:
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continue
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try:
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obj, json_end_index = self.json_decoder.raw_decode(
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model_output[start_index:]
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)
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end_index = start_index + json_end_index
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# raise KeyError if missing
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name = obj["name"]
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arguments_or_params = (
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obj["arguments"] if "arguments" in obj else obj["parameters"]
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)
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tool_calls.append(
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ToolCall(
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type="function",
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function=FunctionCall(
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name=name,
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# function call args are JSON but as a string
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arguments=json.dumps(
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arguments_or_params, ensure_ascii=False
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),
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),
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)
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)
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except KeyError as e:
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# Missing required key
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missing_key = str(e).strip("'\"")
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logger.exception(
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"Couldn't extract tool call from JSON response. "
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"Required key '%s' not present. "
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"Returning output in content with empty tool calls.",
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missing_key,
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)
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return ExtractedToolCallInformation(
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tools_called=False, tool_calls=[], content=model_output
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)
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except Exception:
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# Any other error during parsing
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logger.exception(
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"Error in extracting tool call from response. "
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"Returning output in content with empty tool calls"
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)
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return ExtractedToolCallInformation(
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tools_called=False, tool_calls=[], content=model_output
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)
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except TimeoutError:
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logger.warning("Regex timeout occurred when matching tool call pattern.")
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logger.debug(
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"Regex timeout occurred when matching user input: %s", model_output
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)
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return ExtractedToolCallInformation(
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tools_called=False, tool_calls=[], content=model_output
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)
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try:
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json_str = match.group(0)
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# Split by semicolon and strip whitespace
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json_objects = [obj.strip() for obj in json_str.split(";")]
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tool_calls: list[ToolCall] = []
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for json_obj in json_objects:
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if not json_obj: # Skip empty strings
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continue
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obj = json.loads(json_obj)
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tool_calls.append(
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ToolCall(
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type="function",
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function=FunctionCall(
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name=obj["name"],
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# function call args are JSON but as a string
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arguments=json.dumps(
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obj["arguments"]
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if "arguments" in obj
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else obj["parameters"],
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ensure_ascii=False,
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),
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),
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)
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)
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# If we have valid tool calls, return them normally
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if tool_calls:
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return ExtractedToolCallInformation(
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tools_called=True, tool_calls=tool_calls, content=None
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)
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except Exception:
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logger.exception("Error in extracting tool call from response.")
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# return information to just treat the tool call as regular JSON
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return ExtractedToolCallInformation(
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tools_called=False, tool_calls=[], content=model_output
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)
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# No valid tool calls found
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return ExtractedToolCallInformation(
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tools_called=False, tool_calls=[], content=model_output
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)
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def extract_tool_calls_streaming(
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self,
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