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

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

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",