Backport multi-format tool parser to v0.12.0

tests/entrypoints/openai/test_tool_parser_kwargs.py

@@ -0,0 +1,177 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+# ruff: noqa: E402
+
+import sys
+import types
+from unittest.mock import MagicMock
+
+import pytest
+
+llguidance = types.ModuleType("llguidance")
+llguidance.LLMatcher = object
+llguidance.LLTokenizer = object
+sys.modules.setdefault("llguidance", llguidance)
+
+llguidance_hf = types.ModuleType("llguidance.hf")
+llguidance_hf.from_tokenizer = lambda *args, **kwargs: None
+sys.modules.setdefault("llguidance.hf", llguidance_hf)
+
+llguidance_torch = types.ModuleType("llguidance.torch")
+llguidance_torch.allocate_token_bitmask = lambda *args, **kwargs: None
+llguidance_torch.fill_next_token_bitmask = lambda *args, **kwargs: None
+sys.modules.setdefault("llguidance.torch", llguidance_torch)
+
+diskcache = types.ModuleType("diskcache")
+diskcache.Cache = object
+sys.modules.setdefault("diskcache", diskcache)
+
+xgrammar = types.ModuleType("xgrammar")
+xgrammar.TokenizerInfo = object
+xgrammar.VocabType = types.SimpleNamespace(RAW="RAW", BYTE_FALLBACK="BYTE_FALLBACK")
+xgrammar.GrammarCompiler = object
+xgrammar.StructuralTagItem = object
+xgrammar.GrammarMatcher = object
+xgrammar.__file__ = "/tmp/xgrammar_stub.py"
+
+
+def _xgrammar_getattr(name: str):
+    if name.startswith("__"):
+        raise AttributeError(name)
+    return object
+
+
+xgrammar.__getattr__ = _xgrammar_getattr
+sys.modules.setdefault("xgrammar", xgrammar)
+
+from vllm.entrypoints.openai.protocol import (
+    ChatCompletionRequest,
+    ExtractedToolCallInformation,
+    FunctionCall,
+    ToolCall,
+)
+from vllm.entrypoints.openai.serving_engine import OpenAIServing
+from vllm.entrypoints.openai.tool_parsers import ToolParser
+
+pytestmark = pytest.mark.cpu_test
+
+
+class KwargAwareToolParser(ToolParser):
+    def __init__(self, tokenizer, chat_template_kwargs=None):
+        super().__init__(tokenizer)
+        self.tool_format = (chat_template_kwargs or {}).get("tool_format")
+
+    def extract_tool_calls(self, model_output, request):
+        return ExtractedToolCallInformation(
+            tools_called=True,
+            tool_calls=[
+                ToolCall(
+                    function=FunctionCall(
+                        name=self.tool_format or "missing",
+                        arguments="{}",
+                    )
+                )
+            ],
+            content=None,
+        )
+
+    def extract_tool_calls_streaming(
+        self,
+        previous_text,
+        current_text,
+        delta_text,
+        previous_token_ids,
+        current_token_ids,
+        delta_token_ids,
+        request,
+    ):
+        return None
+
+
+class LegacyToolParser(ToolParser):
+    def __init__(self, tokenizer):
+        super().__init__(tokenizer)
+
+    def extract_tool_calls(self, model_output, request):
+        return ExtractedToolCallInformation(
+            tools_called=True,
+            tool_calls=[
+                ToolCall(
+                    function=FunctionCall(
+                        name="legacy",
+                        arguments="{}",
+                    )
+                )
+            ],
+            content=None,
+        )
+
+    def extract_tool_calls_streaming(
+        self,
+        previous_text,
+        current_text,
+        delta_text,
+        previous_token_ids,
+        current_token_ids,
+        delta_token_ids,
+        request,
+    ):
+        return None
+
+
+def make_request() -> ChatCompletionRequest:
+    return ChatCompletionRequest(
+        model="test-model",
+        messages=[],
+        tool_choice="auto",
+        tools=[
+            {
+                "type": "function",
+                "function": {
+                    "name": "noop",
+                    "parameters": {
+                        "type": "object",
+                        "properties": {},
+                    },
+                },
+            }
+        ],
+    )
+
+
+def test_parse_tool_calls_from_content_passes_chat_template_kwargs():
+    request = make_request()
+
+    function_calls, content = OpenAIServing._parse_tool_calls_from_content(
+        request=request,
+        tokenizer=MagicMock(),
+        enable_auto_tools=True,
+        tool_parser_cls=KwargAwareToolParser,
+        content="<function_calls>noop()</function_calls>",
+        chat_template_kwargs={"tool_format": "python"},
+    )
+
+    assert content is None
+    assert function_calls is not None
+    assert len(function_calls) == 1
+    assert function_calls[0].name == "python"
+    assert function_calls[0].arguments == "{}"
+
+
+def test_parse_tool_calls_from_content_keeps_legacy_parsers_compatible():
+    request = make_request()
+
+    function_calls, content = OpenAIServing._parse_tool_calls_from_content(
+        request=request,
+        tokenizer=MagicMock(),
+        enable_auto_tools=True,
+        tool_parser_cls=LegacyToolParser,
+        content="<function_calls>noop()</function_calls>",
+        chat_template_kwargs={"tool_format": "python"},
+    )
+
+    assert content is None
+    assert function_calls is not None
+    assert len(function_calls) == 1
+    assert function_calls[0].name == "legacy"
+    assert function_calls[0].arguments == "{}"