[Bugfix] Improve JSON extraction in LlamaToolParser (#19024)

Signed-off-by: keru <keyang.ru@oracle.com>
Co-authored-by: keru <keyang.ru@oracle.com>

tests/entrypoints/openai/tool_parsers/test_llama3_json_tool_parser.py

+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+import pytest
+from transformers import AutoTokenizer
+
+from vllm.entrypoints.openai.protocol import ExtractedToolCallInformation
+from vllm.entrypoints.openai.tool_parsers.llama_tool_parser import (
+    Llama3JsonToolParser)
+
+
+@pytest.fixture
+def parser():
+    # Use a small tokenizer for testing
+    tokenizer = AutoTokenizer.from_pretrained("gpt2")
+    return Llama3JsonToolParser(tokenizer)
+
+
+def test_extract_tool_calls_simple(parser):
+    # Test with a simple tool call
+    model_output = ('Here is the result: {"name": "getOpenIncidentsTool", '
+                    '"parameters": {}} Would you like to know more?')
+    result = parser.extract_tool_calls(model_output, None)
+
+    assert isinstance(result, ExtractedToolCallInformation)
+    assert result.tools_called is True
+    assert len(result.tool_calls) == 1
+    assert result.tool_calls[0].type == "function"
+    assert result.tool_calls[0].function.name == "getOpenIncidentsTool"
+    assert result.tool_calls[0].function.arguments == "{}"
+    assert result.content is None
+
+
+def test_extract_tool_calls_with_arguments(parser):
+    # Test with a tool call that has arguments
+    model_output = (
+        '{"name": "searchTool", "parameters": {"query": "test query", '
+        '"limit": 10}}')
+    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"
+    assert '"query": "test query"' in result.tool_calls[0].function.arguments
+    assert '"limit": 10' in result.tool_calls[0].function.arguments
+
+
+def test_extract_tool_calls_no_json(parser):
+    # Test with text that doesn't contain a JSON object
+    model_output = "This is just some text without any tool calls"
+    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_invalid_json(parser):
+    # Test with invalid JSON
+    model_output = '{"name": "invalidTool", "parameters": {invalid json}'
+    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_with_arguments_key(parser):
+    # Test with a tool call that uses "arguments" instead of "parameters"
+    model_output = '{"name": "searchTool", "arguments": {"query": "test"}}'
+    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"
+    assert '"query": "test"' in result.tool_calls[0].function.arguments
+
+
+def test_extract_tool_calls_multiple_json(parser):
+    # Test with multiple JSONs separated by semicolons
+    model_output = (
+        '{"name": "searchTool", "parameters": {"query": "test1"}}; '
+        '{"name": "getOpenIncidentsTool", "parameters": {}}; '
+        '{"name": "searchTool", "parameters": {"query": "test2"}}')
+    result = parser.extract_tool_calls(model_output, None)
+
+    assert result.tools_called is True
+    assert len(result.tool_calls) == 3
+
+    # Check first tool call
+    assert result.tool_calls[0].function.name == "searchTool"
+    assert '"query": "test1"' in result.tool_calls[0].function.arguments
+
+    # Check second tool call
+    assert result.tool_calls[1].function.name == "getOpenIncidentsTool"
+    assert result.tool_calls[1].function.arguments == "{}"
+
+    # Check third tool call
+    assert result.tool_calls[2].function.name == "searchTool"
+    assert '"query": "test2"' in result.tool_calls[2].function.arguments
+
+
+def test_extract_tool_calls_multiple_json_with_whitespace(parser):
+    # Test with multiple JSONs separated by semicolons and extra whitespace
+    model_output = (
+        '{"name": "searchTool", "parameters": {"query": "test1"}} ; '
+        '{"name": "getOpenIncidentsTool", "parameters": {}} ; '
+        '{"name": "searchTool", "parameters": {"query": "test2"}}')
+    result = parser.extract_tool_calls(model_output, None)
+
+    assert result.tools_called is True
+    assert len(result.tool_calls) == 3
+    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_multiple_json_with_surrounding_text(parser):
+    # Test with multiple JSONs and surrounding text
+    model_output = (
+        'Here are the results: '
+        '{"name": "searchTool", "parameters": {"query": "test1"}}; '
+        '{"name": "getOpenIncidentsTool", "parameters": {}}; '
+        '{"name": "searchTool", "parameters": {"query": "test2"}} '
+        'Would you like to know more?')
+    result = parser.extract_tool_calls(model_output, None)
+
+    assert result.tools_called is True
+    assert len(result.tool_calls) == 3
+    assert result.tool_calls[0].function.name == "searchTool"
+    assert result.tool_calls[1].function.name == "getOpenIncidentsTool"
+    assert result.tool_calls[2].function.name == "searchTool"

vllm/entrypoints/openai/tool_parsers/llama_tool_parser.py

@@ -3,7 +3,6 @@
 
 import json
 from collections.abc import Sequence
-from json import JSONDecoder
 from typing import Union
 
 import partial_json_parser
@@ -31,11 +30,11 @@ logger = init_logger(__name__)
 @ToolParserManager.register_module("llama4_json")
 class Llama3JsonToolParser(ToolParser):
     """
-    Tool call parser for Llama 3.1 models intended for use with the
+    Tool call parser for Llama 3.x and 4 models intended for use with the
     examples/tool_chat_template_llama.jinja template.
 
-    Used when --enable-auto-tool-choice --tool-call-parser llama3_json 
-    are all set
+    Used when --enable-auto-tool-choice --tool-call-parser llama3_json or 
+    llama4_json are set.
     """
 
     def __init__(self, tokenizer: PreTrainedTokenizerBase):
@@ -51,54 +50,57 @@ class Llama3JsonToolParser(ToolParser):
         self.bot_token = "<|python_tag|>"
         self.bot_token_id = tokenizer.encode(self.bot_token,
                                              add_special_tokens=False)[0]
-        self.tool_call_regex = re.compile(r"\[{.*?}\]", re.DOTALL)
+        # 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)
 
     def extract_tool_calls(
             self, model_output: str,
             request: ChatCompletionRequest) -> ExtractedToolCallInformation:
         """
         Extract the tool calls from a complete model response.
+        Only extracts JSON content and ignores any surrounding plain text.
+        Supports both single JSON and multiple JSONs separated by semicolons.
         """
-        # case -- if a tool call token is not present, return a text response
-        if not (model_output.startswith(self.bot_token)
-                or model_output.startswith('{')):
+        # Quick check before running regex
+        if not (self.bot_token in model_output or '{' in model_output):
             return ExtractedToolCallInformation(tools_called=False,
                                                 tool_calls=[],
                                                 content=model_output)
 
-        try:
-            # load the JSON, and then use it to build the Function and
-            # Tool Call
-            dec = JSONDecoder()
-            function_call_arr = []
-
-            # depending on the prompt format the Llama model may or may not
-            # prefix the output with the <|python_tag|> token
-            start_idx = len(self.bot_token) if model_output.startswith(
-                self.bot_token) else 0
-            while start_idx < len(model_output):
-                (obj, end_idx) = dec.raw_decode(model_output[start_idx:])
-                start_idx += end_idx + len('; ')
-                function_call_arr.append(obj)
+        # Find JSON object(s) in the text using regex
+        match = self.tool_call_regex.search(model_output)
+        if not match:
+            return ExtractedToolCallInformation(tools_called=False,
+                                                tool_calls=[],
+                                                content=model_output)
 
-            tool_calls: list[ToolCall] = [
+        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=raw_function_call["name"],
+                            name=obj["name"],
                             # function call args are JSON but as a string
-                        arguments=json.dumps(raw_function_call["arguments"] \
-                                if "arguments" in raw_function_call \
-                                else raw_function_call["parameters"],
-                                ensure_ascii=False)))
-                for raw_function_call in function_call_arr
-            ]
-
-            # get any content before  the tool call
-            ret = ExtractedToolCallInformation(tools_called=True,
+                            arguments=json.dumps(
+                                obj["arguments"]
+                                if "arguments" in obj else obj["parameters"],
+                                ensure_ascii=False))))
+
+            return ExtractedToolCallInformation(tools_called=True,
                                                 tool_calls=tool_calls,
                                                 content=None)
-            return ret
 
         except Exception:
             logger.exception("Error in extracting tool call from response.")