fix: Resolve type checking issues in output logging

Fix type annotation and variable naming issues identified by mypy:
- Change output_token_ids parameter type from list[int] to Sequence[int]
  to handle compatibility with different sequence types from output objects
- Fix variable naming conflict in tool call logging (tool_call_info -> tool_call_descriptions)
- Add proper type conversion in log_outputs method for truncation
- Update test imports to include Sequence type

These fixes ensure the output logging feature passes mypy type checking
while maintaining full functionality and backward compatibility.

Signed-off-by: Adrian Garcia <adrian.garcia@inceptionai.ai>

Author: mizadri

tests/test_logger.py

@@ -9,7 +9,7 @@
 from dataclasses import dataclass
 from json.decoder import JSONDecodeError
 from tempfile import NamedTemporaryFile
-from typing import Any
+from typing import Any, Sequence
 from unittest.mock import patch, MagicMock
 from uuid import uuid4
 

vllm/entrypoints/logger.py

@@ -1,7 +1,7 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 
-from typing import Optional, Union
+from typing import Optional, Union, Sequence
 
 import torch
 
@@ -53,7 +53,7 @@ def log_outputs(
         self,
         request_id: str,
         outputs: str,
-        output_token_ids: Optional[list[int]],
+        output_token_ids: Optional[Sequence[int]],
         finish_reason: Optional[str] = None,
         is_streaming: bool = False,
         delta: bool = False,
@@ -64,7 +64,8 @@ def log_outputs(
                 outputs = outputs[:max_log_len]
 
             if output_token_ids is not None:
-                output_token_ids = output_token_ids[:max_log_len]
+                # Convert to list and apply truncation
+                output_token_ids = list(output_token_ids)[:max_log_len]
 
         stream_info = ""
         if is_streaming:

vllm/entrypoints/openai/serving_chat.py

@@ -1197,11 +1197,11 @@ async def chat_completion_full_generator(
                     output_text = choice.message.content
                 elif choice.message.tool_calls:
                     # For tool calls, log the function name and arguments
-                    tool_call_info = []
+                    tool_call_descriptions = []
                     for tool_call in choice.message.tool_calls:
                         if hasattr(tool_call.function, 'name') and hasattr(tool_call.function, 'arguments'):
-                            tool_call_info.append(f"{tool_call.function.name}({tool_call.function.arguments})")
-                    output_text = f"[tool_calls: {', '.join(tool_call_info)}]"
+                            tool_call_descriptions.append(f"{tool_call.function.name}({tool_call.function.arguments})")
+                    output_text = f"[tool_calls: {', '.join(tool_call_descriptions)}]"
 
                 if output_text:
                     # Get the corresponding output token IDs