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Convert formatting to use ruff instead of yapf + isort (#26247)

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Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
This commit is contained in:
Harry Mellor
2025-10-05 15:06:22 +01:00
committed by GitHub
parent 17edd8a807
commit d6953beb91
1508 changed files with 115244 additions and 94146 deletions
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73
tests/tool_use/test_parallel_tool_calls.py
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@@ -7,9 +7,13 @@ from typing import Optional
import openai
import pytest
from .utils import (MESSAGES_ASKING_FOR_PARALLEL_TOOLS,
MESSAGES_WITH_PARALLEL_TOOL_RESPONSE, SEARCH_TOOL,
WEATHER_TOOL, ServerConfig)
from .utils import (
MESSAGES_ASKING_FOR_PARALLEL_TOOLS,
MESSAGES_WITH_PARALLEL_TOOL_RESPONSE,
SEARCH_TOOL,
WEATHER_TOOL,
ServerConfig,
)
# test: getting the model to generate parallel tool calls (streaming/not)
@@ -17,12 +21,15 @@ from .utils import (MESSAGES_ASKING_FOR_PARALLEL_TOOLS,
# may be added in the future. e.g. llama 3.1 models are not designed to support
# parallel tool calls.
@pytest.mark.asyncio
async def test_parallel_tool_calls(client: openai.AsyncOpenAI,
server_config: ServerConfig):
async def test_parallel_tool_calls(
client: openai.AsyncOpenAI, server_config: ServerConfig
):
if not server_config.get("supports_parallel", True):
pytest.skip("The {} model doesn't support parallel tool calls".format(
server_config["model"]))
pytest.skip(
"The {} model doesn't support parallel tool calls".format(
server_config["model"]
)
)
models = await client.models.list()
model_name: str = models.data[0].id
@@ -32,7 +39,8 @@ async def test_parallel_tool_calls(client: openai.AsyncOpenAI,
max_completion_tokens=200,
model=model_name,
tools=[WEATHER_TOOL, SEARCH_TOOL],
logprobs=False)
logprobs=False,
)
choice = chat_completion.choices[0]
stop_reason = chat_completion.choices[0].finish_reason
@@ -69,7 +77,8 @@ async def test_parallel_tool_calls(client: openai.AsyncOpenAI,
max_completion_tokens=200,
tools=[WEATHER_TOOL, SEARCH_TOOL],
logprobs=False,
stream=True)
stream=True,
)
role_name: Optional[str] = None
finish_reason_count: int = 0
@@ -80,24 +89,22 @@ async def test_parallel_tool_calls(client: openai.AsyncOpenAI,
tool_call_id_count: int = 0
async for chunk in stream:
# if there's a finish reason make sure it's tools
if chunk.choices[0].finish_reason:
finish_reason_count += 1
assert chunk.choices[0].finish_reason == 'tool_calls'
assert chunk.choices[0].finish_reason == "tool_calls"
# if a role is being streamed make sure it wasn't already set to
# something else
if chunk.choices[0].delta.role:
assert not role_name or role_name == 'assistant'
role_name = 'assistant'
assert not role_name or role_name == "assistant"
role_name = "assistant"
# if a tool call is streamed make sure there's exactly one
# (based on the request parameters
streamed_tool_calls = chunk.choices[0].delta.tool_calls
if streamed_tool_calls and len(streamed_tool_calls) > 0:
# make sure only one diff is present - correct even for parallel
assert len(streamed_tool_calls) == 1
tool_call = streamed_tool_calls[0]
@@ -110,8 +117,7 @@ async def test_parallel_tool_calls(client: openai.AsyncOpenAI,
# if a tool call ID is streamed, make sure one hasn't been already
if tool_call.id:
tool_call_id_count += 1
assert (isinstance(tool_call.id, str)
and (len(tool_call.id) >= 9))
assert isinstance(tool_call.id, str) and (len(tool_call.id) >= 9)
# if parts of the function start being streamed
if tool_call.function:
@@ -125,32 +131,32 @@ async def test_parallel_tool_calls(client: openai.AsyncOpenAI,
# make sure they're a string and then add them to the list
assert isinstance(tool_call.function.arguments, str)
tool_call_args[
tool_call.index] += tool_call.function.arguments
tool_call_args[tool_call.index] += tool_call.function.arguments
assert finish_reason_count == 1
assert role_name == 'assistant'
assert role_name == "assistant"
assert (len(non_streamed_tool_calls) == len(tool_call_names) ==
len(tool_call_args))
assert len(non_streamed_tool_calls) == len(tool_call_names) == len(tool_call_args)
for i in range(2):
assert non_streamed_tool_calls[i].function.name == tool_call_names[i]
streamed_args = json.loads(tool_call_args[i])
non_streamed_args = json.loads(
non_streamed_tool_calls[i].function.arguments)
non_streamed_args = json.loads(non_streamed_tool_calls[i].function.arguments)
assert streamed_args == non_streamed_args
# test: providing parallel tool calls back to the model to get a response
# (streaming/not)
@pytest.mark.asyncio
async def test_parallel_tool_calls_with_results(client: openai.AsyncOpenAI,
server_config: ServerConfig):
async def test_parallel_tool_calls_with_results(
client: openai.AsyncOpenAI, server_config: ServerConfig
):
if not server_config.get("supports_parallel", True):
pytest.skip("The {} model doesn't support parallel tool calls".format(
server_config["model"]))
pytest.skip(
"The {} model doesn't support parallel tool calls".format(
server_config["model"]
)
)
models = await client.models.list()
model_name: str = models.data[0].id
@@ -160,14 +166,14 @@ async def test_parallel_tool_calls_with_results(client: openai.AsyncOpenAI,
max_completion_tokens=200,
model=model_name,
tools=[WEATHER_TOOL, SEARCH_TOOL],
logprobs=False)
logprobs=False,
)
choice = chat_completion.choices[0]
assert choice.finish_reason != "tool_calls" # "stop" or "length"
assert choice.message.role == "assistant"
assert choice.message.tool_calls is None \
or len(choice.message.tool_calls) == 0
assert choice.message.tool_calls is None or len(choice.message.tool_calls) == 0
assert choice.message.content is not None
assert "98" in choice.message.content # Dallas temp in tool response
assert "78" in choice.message.content # Orlando temp in tool response
@@ -179,7 +185,8 @@ async def test_parallel_tool_calls_with_results(client: openai.AsyncOpenAI,
model=model_name,
tools=[WEATHER_TOOL, SEARCH_TOOL],
logprobs=False,
stream=True)
stream=True,
)
chunks: list[str] = []
finish_reason_count = 0