[Test] Consolidate tool parser unit tests to tests/tool_parsers (#37834)

Signed-off-by: Ben Browning <bbrownin@redhat.com>

tests/entrypoints/openai/tool_parsers/conftest.py

@@ -1,12 +0,0 @@
-# SPDX-License-Identifier: Apache-2.0
-# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
-
-import pytest
-from transformers import AutoTokenizer
-
-from vllm.tokenizers import TokenizerLike
-
-
-@pytest.fixture(scope="function")
-def default_tokenizer() -> TokenizerLike:
-    return AutoTokenizer.from_pretrained("gpt2")

tests/entrypoints/openai/tool_parsers/test_granite4_tool_parser.py

@@ -1,18 +1,9 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 import json
-import random
-from typing import Any
 
 import openai
 import pytest
-from transformers import AutoTokenizer
-
-from vllm.entrypoints.openai.chat_completion.protocol import ChatCompletionRequest
-from vllm.entrypoints.openai.engine.protocol import (
-    DeltaMessage,
-)
-from vllm.tool_parsers.granite4_tool_parser import Granite4ToolParser
 
 from ....utils import RemoteOpenAIServer
 
@@ -38,137 +29,6 @@ def server():
         yield server
 
 
-def create_complex_input(create_string_args: bool):
-    coord_arg: dict | str = {
-        "coordinates": [[23.54, 43.1], [-12.2, 54.3], [4, 5]],
-        "coordinate_type": "latlong",
-    }
-    if create_string_args:
-        # test granite behavior
-        coord_arg = json.dumps(coord_arg)
-    return [
-        {"name": "find_bbox", "arguments": coord_arg},
-        {
-            "name": "get_stock_price",
-            "arguments": {
-                "symbol": "AAPL",
-                "start_date": "2021-01-01",
-                "end_date": "2021-12-31",
-            },
-        },
-        {"name": "find_bbox", "arguments": coord_arg},
-    ]
-
-
-def random_chunks(s: str, min_len: int, max_len: int):
-    chunks = []
-    i = 0
-    n = len(s)
-
-    while i < n:
-        size = random.randint(min_len, max_len)
-        chunks.append(s[i : i + size])
-        i += size
-
-    return chunks
-
-
-@pytest.fixture(scope="module")
-def tokenizer():
-    return AutoTokenizer.from_pretrained(MODEL)
-
-
-# create a variety of input chunk sizes
-@pytest.mark.parametrize(
-    "min_chunk, max_chunk",
-    [
-        (1, 1),
-        (1, 2),
-        (5, 7),
-        (6, 20),
-    ],
-)
-def test_tool_call_parser_complex(min_chunk: int, max_chunk: int, tokenizer):
-    input_dicts = create_complex_input(True)
-
-    formatted_tcs = [
-        "<tool_call> " + json.dumps(call) + " </tool_call>" for call in input_dicts
-    ]
-
-    text_messages = [
-        "Here goes the bbox call: \n",
-        " Now the stock price call: \n ",
-        " Now another bbox call: \n ",
-        " See? I'm a helpful assistant.",
-    ]
-
-    test_input = (
-        text_messages[0]
-        + formatted_tcs[0]
-        + text_messages[1]
-        + formatted_tcs[1]
-        + text_messages[2]
-        + formatted_tcs[2]
-        + text_messages[3]
-    )
-
-    any_chat_request = ChatCompletionRequest(
-        seed=42,
-        model=MODEL,
-        messages=[],
-    )
-
-    parser = Granite4ToolParser(tokenizer=tokenizer)
-
-    delta_messages = list[DeltaMessage]()
-    for text in random_chunks(test_input, min_chunk, max_chunk):
-        delta = parser.extract_tool_calls_streaming(
-            previous_text="",
-            current_text="",
-            delta_text=text,
-            previous_token_ids=[],
-            current_token_ids=[],
-            delta_token_ids=[],
-            request=any_chat_request,
-        )
-        if delta is not None:
-            delta_messages.append(delta)
-
-    content = ""
-    tool_calls = list[dict[str, Any]]()
-
-    current_name = "__start__"
-    current_args = ""
-
-    for msg in delta_messages:
-        if msg.content:
-            content += msg.content
-        for tool_call in msg.tool_calls:
-            if delta_func := tool_call.function:
-                if delta_func.name is not None:
-                    if current_name == "__start__":
-                        current_name = delta_func.name
-
-                    if delta_func.name != current_name:
-                        tool_calls.append(
-                            {
-                                "name": current_name,
-                                "arguments": json.loads(current_args),
-                            }
-                        )
-                        current_name = delta_func.name
-                        current_args = ""
-
-                if delta_func.arguments:
-                    current_args += delta_func.arguments
-
-    if current_name != "__start__":
-        tool_calls.append({"name": current_name, "arguments": json.loads(current_args)})
-
-    assert content == "".join(text_messages)
-    assert tool_calls == create_complex_input(False)
-
-
 tools = [
     {
         "type": "function",

tests/entrypoints/openai/tool_parsers/test_hermes_tool_parser.py

@@ -9,8 +9,6 @@ import pytest_asyncio
 from huggingface_hub import snapshot_download
 from typing_extensions import TypedDict
 
-from vllm.entrypoints.openai.chat_completion.protocol import ChatCompletionRequest
-from vllm.tokenizers import TokenizerLike
 from vllm.tool_parsers.abstract_tool_parser import ToolParser
 from vllm.tool_parsers.granite4_tool_parser import Granite4ToolParser
 from vllm.tool_parsers.hermes_tool_parser import Hermes2ProToolParser
@@ -325,202 +323,3 @@ async def test_streaming_product_tool_call(
     print("\n[Streaming Product Test Passed]")
     print(f"Reconstructed Tool Call: {reconstructed_tool_call['name']}")
     print(f"Reconstructed Arguments: {arguments}")
-
-
-@pytest.fixture
-def qwen_tokenizer() -> TokenizerLike:
-    from vllm.tokenizers import get_tokenizer
-
-    return get_tokenizer("Qwen/Qwen3-32B")
-
-
-@pytest.fixture(params=CONFIGS.keys())
-def hermes_parser(request, qwen_tokenizer: TokenizerLike) -> ToolParser:
-    config = CONFIGS[request.param]
-    return config["tool_parser"](qwen_tokenizer)
-
-
-@pytest.fixture
-def any_chat_request() -> ChatCompletionRequest:
-    return ChatCompletionRequest(
-        seed=42,
-        model="Qwen/Qwen3-32B",
-        messages=[],
-    )
-
-
-def test_hermes_parser_streaming_just_forward_text(
-    qwen_tokenizer: TokenizerLike,
-    hermes_parser: ToolParser,
-    any_chat_request: ChatCompletionRequest,
-) -> None:
-    text = """This is some prior text that has nothing to do with tool calling."""
-    tokens = qwen_tokenizer.encode(text)
-    previous_text = ""
-    delta_messages = []
-    for token in tokens:
-        delta_text = qwen_tokenizer.decode([token])
-        current_text = previous_text + delta_text
-        delta = hermes_parser.extract_tool_calls_streaming(
-            previous_text=previous_text,
-            current_text=current_text,
-            delta_text=delta_text,
-            previous_token_ids=[],
-            current_token_ids=[],
-            delta_token_ids=[],
-            request=any_chat_request,
-        )
-        previous_text = current_text
-        delta_messages.append(delta)
-
-    for delta in delta_messages:
-        assert delta is not None
-        assert not delta.tool_calls
-
-    print(delta_messages)
-    assert "".join([delta.content for delta in delta_messages]) == text
-
-
-def test_hermes_parser_streaming_failure_case_bug_19056(
-    qwen_tokenizer: TokenizerLike,
-    hermes_parser: ToolParser,
-    any_chat_request: ChatCompletionRequest,
-) -> None:
-    text = """<tool_call>
-{"name": "final_answer", "arguments": {"trigger": true}}
-</tool_call>"""
-    tokens = qwen_tokenizer.encode(text)
-    previous_text = ""
-    delta_messages = []
-    for token in tokens:
-        text = qwen_tokenizer.decode([token])
-        current_text = previous_text + text
-        delta = hermes_parser.extract_tool_calls_streaming(
-            previous_text=previous_text,
-            current_text=current_text,
-            delta_text=text,
-            previous_token_ids=[],
-            current_token_ids=[],
-            delta_token_ids=[],
-            request=any_chat_request,
-        )
-        previous_text = current_text
-        if delta is not None:
-            delta_messages.append(delta)
-
-    assert delta_messages[0].tool_calls[0].function.name == "final_answer"
-    tool_call_args = "".join(
-        delta.tool_calls[0].function.arguments or "" for delta in delta_messages
-    )
-    assert tool_call_args == '{"trigger": true}'
-
-
-def test_hermes_parser_streaming(
-    qwen_tokenizer: TokenizerLike,
-    hermes_parser: ToolParser,
-    any_chat_request: ChatCompletionRequest,
-) -> None:
-    text = '<tool_call>\
-{"name": "get_current_temperature",\
-"arguments": {"location":\
-"San Francisco, California, United States", "unit": "celsius"}}\
-</tool_call>'
-
-    tokens = qwen_tokenizer.encode(text)
-    previous_text = ""
-    delta_messages = []
-    for token in tokens:
-        text = qwen_tokenizer.decode([token])
-        current_text = previous_text + text
-        delta = hermes_parser.extract_tool_calls_streaming(
-            previous_text=previous_text,
-            current_text=current_text,
-            delta_text=text,
-            previous_token_ids=[],
-            current_token_ids=[],
-            delta_token_ids=[],
-            request=any_chat_request,
-        )
-        previous_text = current_text
-        if delta is not None:
-            delta_messages.append(delta)
-    print(delta_messages)
-    assert delta_messages[0].tool_calls[0].function.name == "get_current_temperature"
-    # load to normalize whitespace
-    tool_call_args = json.loads(
-        "".join(
-            delta.tool_calls[0].function.arguments or "" for delta in delta_messages
-        )
-    )
-    assert tool_call_args == {
-        "location": "San Francisco, California, United States",
-        "unit": "celsius",
-    }
-
-
-def test_hermes_parser_non_streaming_no_tool_call(
-    hermes_parser: ToolParser,
-    any_chat_request: ChatCompletionRequest,
-) -> None:
-    text = """This is not a tool call."""
-    tool_call = hermes_parser.extract_tool_calls(
-        model_output=text,
-        request=any_chat_request,
-    )
-
-    assert tool_call is not None
-    assert not tool_call.tools_called
-
-
-def test_hermes_parser_non_streaming_tool_call_between_tags(
-    hermes_parser: ToolParser,
-    any_chat_request: ChatCompletionRequest,
-) -> None:
-    text = """<tool_call>
-{"name": "final_answer", "arguments": {"trigger": true}}
-</tool_call>"""
-    tool_call = hermes_parser.extract_tool_calls(
-        model_output=text,
-        request=any_chat_request,
-    )
-
-    assert tool_call is not None
-    assert tool_call.tools_called
-    assert tool_call.tool_calls[0].function.name == "final_answer"
-    assert tool_call.tool_calls[0].function.arguments == '{"trigger": true}'
-
-
-def test_hermes_parser_non_streaming_tool_call_until_eos(
-    hermes_parser: ToolParser,
-    any_chat_request: ChatCompletionRequest,
-) -> None:
-    if isinstance(hermes_parser, Granite4ToolParser):
-        pytest.skip(reason="The Granite4 tool parser enforces a complete response")
-
-    text = """<tool_call>
-{"name": "final_answer", "arguments": {"trigger": true}}"""
-    tool_call = hermes_parser.extract_tool_calls(
-        model_output=text,
-        request=any_chat_request,
-    )
-
-    assert tool_call is not None
-    assert tool_call.tools_called
-    assert tool_call.tool_calls[0].function.name == "final_answer"
-    assert tool_call.tool_calls[0].function.arguments == '{"trigger": true}'
-
-
-def test_hermes_parser_non_streaming_tool_call_invalid_json(
-    hermes_parser: ToolParser,
-    any_chat_request: ChatCompletionRequest,
-) -> None:
-    # Missing closing brace to trigger exception
-    text = """<tool_call>
-{"name": "final_answer", "arguments": {"trigger": true}"""
-    tool_call = hermes_parser.extract_tool_calls(
-        model_output=text,
-        request=any_chat_request,
-    )
-
-    assert tool_call is not None
-    assert not tool_call.tools_called

tests/tool_parsers/test_gigachat3_tool_parser.py

@@ -4,6 +4,7 @@
 import json
 
 import pytest
+from transformers import AutoTokenizer
 
 from tests.tool_parsers.utils import (
     run_tool_extraction,
@@ -13,6 +14,14 @@ from vllm.entrypoints.openai.engine.protocol import FunctionCall
 from vllm.tokenizers import TokenizerLike
 from vllm.tool_parsers import ToolParser, ToolParserManager
 
+
+@pytest.fixture(scope="function")
+def default_tokenizer() -> TokenizerLike:
+    """Override module-scoped default_tokenizer because gigachat tests
+    mutate the tokenizer via ``add_tokens``."""
+    return AutoTokenizer.from_pretrained("gpt2")
+
+
 MSG_SEP_TOKEN = "<|message_sep|>\n\n"
 ROLE_SEP_TOKEN = "<|role_sep|>\n"
 EOS_TOKEN = "</s>"

tests/tool_parsers/test_granite4_tool_parser.py

@@ -0,0 +1,147 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+import json
+import random
+from typing import Any
+
+import pytest
+from transformers import AutoTokenizer
+
+from vllm.entrypoints.openai.chat_completion.protocol import ChatCompletionRequest
+from vllm.entrypoints.openai.engine.protocol import (
+    DeltaMessage,
+)
+from vllm.tool_parsers.granite4_tool_parser import Granite4ToolParser
+
+MODEL = "ibm-granite/granite-4.0-h-tiny"
+
+
+def create_complex_input(create_string_args: bool):
+    coord_arg: dict | str = {
+        "coordinates": [[23.54, 43.1], [-12.2, 54.3], [4, 5]],
+        "coordinate_type": "latlong",
+    }
+    if create_string_args:
+        # test granite behavior
+        coord_arg = json.dumps(coord_arg)
+    return [
+        {"name": "find_bbox", "arguments": coord_arg},
+        {
+            "name": "get_stock_price",
+            "arguments": {
+                "symbol": "AAPL",
+                "start_date": "2021-01-01",
+                "end_date": "2021-12-31",
+            },
+        },
+        {"name": "find_bbox", "arguments": coord_arg},
+    ]
+
+
+def random_chunks(s: str, min_len: int, max_len: int):
+    chunks = []
+    i = 0
+    n = len(s)
+
+    while i < n:
+        size = random.randint(min_len, max_len)
+        chunks.append(s[i : i + size])
+        i += size
+
+    return chunks
+
+
+@pytest.fixture(scope="module")
+def tokenizer():
+    return AutoTokenizer.from_pretrained(MODEL)
+
+
+# create a variety of input chunk sizes
+@pytest.mark.parametrize(
+    "min_chunk, max_chunk",
+    [
+        (1, 1),
+        (1, 2),
+        (5, 7),
+        (6, 20),
+    ],
+)
+def test_tool_call_parser_complex(min_chunk: int, max_chunk: int, tokenizer):
+    input_dicts = create_complex_input(True)
+
+    formatted_tcs = [
+        "<tool_call> " + json.dumps(call) + " </tool_call>" for call in input_dicts
+    ]
+
+    text_messages = [
+        "Here goes the bbox call: \n",
+        " Now the stock price call: \n ",
+        " Now another bbox call: \n ",
+        " See? I'm a helpful assistant.",
+    ]
+
+    test_input = (
+        text_messages[0]
+        + formatted_tcs[0]
+        + text_messages[1]
+        + formatted_tcs[1]
+        + text_messages[2]
+        + formatted_tcs[2]
+        + text_messages[3]
+    )
+
+    any_chat_request = ChatCompletionRequest(
+        seed=42,
+        model=MODEL,
+        messages=[],
+    )
+
+    parser = Granite4ToolParser(tokenizer=tokenizer)
+
+    delta_messages = list[DeltaMessage]()
+    for text in random_chunks(test_input, min_chunk, max_chunk):
+        delta = parser.extract_tool_calls_streaming(
+            previous_text="",
+            current_text="",
+            delta_text=text,
+            previous_token_ids=[],
+            current_token_ids=[],
+            delta_token_ids=[],
+            request=any_chat_request,
+        )
+        if delta is not None:
+            delta_messages.append(delta)
+
+    content = ""
+    tool_calls = list[dict[str, Any]]()
+
+    current_name = "__start__"
+    current_args = ""
+
+    for msg in delta_messages:
+        if msg.content:
+            content += msg.content
+        for tool_call in msg.tool_calls:
+            if delta_func := tool_call.function:
+                if delta_func.name is not None:
+                    if current_name == "__start__":
+                        current_name = delta_func.name
+
+                    if delta_func.name != current_name:
+                        tool_calls.append(
+                            {
+                                "name": current_name,
+                                "arguments": json.loads(current_args),
+                            }
+                        )
+                        current_name = delta_func.name
+                        current_args = ""
+
+                if delta_func.arguments:
+                    current_args += delta_func.arguments
+
+    if current_name != "__start__":
+        tool_calls.append({"name": current_name, "arguments": json.loads(current_args)})
+
+    assert content == "".join(text_messages)
+    assert tool_calls == create_complex_input(False)

tests/tool_parsers/test_hermes_tool_parser.py

@@ -0,0 +1,220 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+import json
+
+import pytest
+
+from vllm.entrypoints.openai.chat_completion.protocol import ChatCompletionRequest
+from vllm.tokenizers import TokenizerLike
+from vllm.tool_parsers.abstract_tool_parser import ToolParser
+from vllm.tool_parsers.granite4_tool_parser import Granite4ToolParser
+from vllm.tool_parsers.hermes_tool_parser import Hermes2ProToolParser
+
+CONFIGS = {
+    "llama": {
+        "tool_parser": Hermes2ProToolParser,
+    },
+    "granite4": {
+        "tool_parser": Granite4ToolParser,
+    },
+}
+
+
+@pytest.fixture
+def qwen_tokenizer() -> TokenizerLike:
+    from vllm.tokenizers import get_tokenizer
+
+    return get_tokenizer("Qwen/Qwen3-32B")
+
+
+@pytest.fixture(params=CONFIGS.keys())
+def hermes_parser(request, qwen_tokenizer: TokenizerLike) -> ToolParser:
+    config = CONFIGS[request.param]
+    return config["tool_parser"](qwen_tokenizer)
+
+
+@pytest.fixture
+def any_chat_request() -> ChatCompletionRequest:
+    return ChatCompletionRequest(
+        seed=42,
+        model="Qwen/Qwen3-32B",
+        messages=[],
+    )
+
+
+def test_hermes_parser_streaming_just_forward_text(
+    qwen_tokenizer: TokenizerLike,
+    hermes_parser: ToolParser,
+    any_chat_request: ChatCompletionRequest,
+) -> None:
+    text = """This is some prior text that has nothing to do with tool calling."""
+    tokens = qwen_tokenizer.encode(text)
+    previous_text = ""
+    delta_messages = []
+    for token in tokens:
+        delta_text = qwen_tokenizer.decode([token])
+        current_text = previous_text + delta_text
+        delta = hermes_parser.extract_tool_calls_streaming(
+            previous_text=previous_text,
+            current_text=current_text,
+            delta_text=delta_text,
+            previous_token_ids=[],
+            current_token_ids=[],
+            delta_token_ids=[],
+            request=any_chat_request,
+        )
+        previous_text = current_text
+        delta_messages.append(delta)
+
+    for delta in delta_messages:
+        assert delta is not None
+        assert not delta.tool_calls
+
+    print(delta_messages)
+    assert "".join([delta.content for delta in delta_messages]) == text
+
+
+def test_hermes_parser_streaming_failure_case_bug_19056(
+    qwen_tokenizer: TokenizerLike,
+    hermes_parser: ToolParser,
+    any_chat_request: ChatCompletionRequest,
+) -> None:
+    text = """<tool_call>
+{"name": "final_answer", "arguments": {"trigger": true}}
+</tool_call>"""
+    tokens = qwen_tokenizer.encode(text)
+    previous_text = ""
+    delta_messages = []
+    for token in tokens:
+        text = qwen_tokenizer.decode([token])
+        current_text = previous_text + text
+        delta = hermes_parser.extract_tool_calls_streaming(
+            previous_text=previous_text,
+            current_text=current_text,
+            delta_text=text,
+            previous_token_ids=[],
+            current_token_ids=[],
+            delta_token_ids=[],
+            request=any_chat_request,
+        )
+        previous_text = current_text
+        if delta is not None:
+            delta_messages.append(delta)
+
+    assert delta_messages[0].tool_calls[0].function.name == "final_answer"
+    tool_call_args = "".join(
+        delta.tool_calls[0].function.arguments or "" for delta in delta_messages
+    )
+    assert tool_call_args == '{"trigger": true}'
+
+
+def test_hermes_parser_streaming(
+    qwen_tokenizer: TokenizerLike,
+    hermes_parser: ToolParser,
+    any_chat_request: ChatCompletionRequest,
+) -> None:
+    text = '<tool_call>\
+{"name": "get_current_temperature",\
+"arguments": {"location":\
+"San Francisco, California, United States", "unit": "celsius"}}\
+</tool_call>'
+
+    tokens = qwen_tokenizer.encode(text)
+    previous_text = ""
+    delta_messages = []
+    for token in tokens:
+        text = qwen_tokenizer.decode([token])
+        current_text = previous_text + text
+        delta = hermes_parser.extract_tool_calls_streaming(
+            previous_text=previous_text,
+            current_text=current_text,
+            delta_text=text,
+            previous_token_ids=[],
+            current_token_ids=[],
+            delta_token_ids=[],
+            request=any_chat_request,
+        )
+        previous_text = current_text
+        if delta is not None:
+            delta_messages.append(delta)
+    print(delta_messages)
+    assert delta_messages[0].tool_calls[0].function.name == "get_current_temperature"
+    # load to normalize whitespace
+    tool_call_args = json.loads(
+        "".join(
+            delta.tool_calls[0].function.arguments or "" for delta in delta_messages
+        )
+    )
+    assert tool_call_args == {
+        "location": "San Francisco, California, United States",
+        "unit": "celsius",
+    }
+
+
+def test_hermes_parser_non_streaming_no_tool_call(
+    hermes_parser: ToolParser,
+    any_chat_request: ChatCompletionRequest,
+) -> None:
+    text = """This is not a tool call."""
+    tool_call = hermes_parser.extract_tool_calls(
+        model_output=text,
+        request=any_chat_request,
+    )
+
+    assert tool_call is not None
+    assert not tool_call.tools_called
+
+
+def test_hermes_parser_non_streaming_tool_call_between_tags(
+    hermes_parser: ToolParser,
+    any_chat_request: ChatCompletionRequest,
+) -> None:
+    text = """<tool_call>
+{"name": "final_answer", "arguments": {"trigger": true}}
+</tool_call>"""
+    tool_call = hermes_parser.extract_tool_calls(
+        model_output=text,
+        request=any_chat_request,
+    )
+
+    assert tool_call is not None
+    assert tool_call.tools_called
+    assert tool_call.tool_calls[0].function.name == "final_answer"
+    assert tool_call.tool_calls[0].function.arguments == '{"trigger": true}'
+
+
+def test_hermes_parser_non_streaming_tool_call_until_eos(
+    hermes_parser: ToolParser,
+    any_chat_request: ChatCompletionRequest,
+) -> None:
+    if isinstance(hermes_parser, Granite4ToolParser):
+        pytest.skip(reason="The Granite4 tool parser enforces a complete response")
+
+    text = """<tool_call>
+{"name": "final_answer", "arguments": {"trigger": true}}"""
+    tool_call = hermes_parser.extract_tool_calls(
+        model_output=text,
+        request=any_chat_request,
+    )
+
+    assert tool_call is not None
+    assert tool_call.tools_called
+    assert tool_call.tool_calls[0].function.name == "final_answer"
+    assert tool_call.tool_calls[0].function.arguments == '{"trigger": true}'
+
+
+def test_hermes_parser_non_streaming_tool_call_invalid_json(
+    hermes_parser: ToolParser,
+    any_chat_request: ChatCompletionRequest,
+) -> None:
+    # Missing closing brace to trigger exception
+    text = """<tool_call>
+{"name": "final_answer", "arguments": {"trigger": true}"""
+    tool_call = hermes_parser.extract_tool_calls(
+        model_output=text,
+        request=any_chat_request,
+    )
+
+    assert tool_call is not None
+    assert not tool_call.tools_called