fix: optimize tool_choice reset logic and fix lint errors

- Refactor tool_choice reset to target only problematic edge cases
- Replace manual ModelSettings recreation with dataclasses.replace
- Fix line length and error handling lint issues in tests

Author: mini-peanut

src/agents/_run_impl.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 import asyncio
+import dataclasses
 import inspect
 from collections.abc import Awaitable
 from dataclasses import dataclass
@@ -51,7 +52,7 @@
 from .models.interface import ModelTracing
 from .run_context import RunContextWrapper, TContext
 from .stream_events import RunItemStreamEvent, StreamEvent
-from .tool import ComputerTool, FunctionTool, FunctionToolResult
+from .tool import ComputerTool, FunctionTool, FunctionToolResult, Tool
 from .tracing import (
     SpanError,
     Trace,
@@ -208,34 +209,22 @@ async def execute_tools_and_side_effects(
         new_step_items.extend(computer_results)
 
         # Reset tool_choice to "auto" after tool execution to prevent infinite loops
-        if (processed_response.functions or processed_response.computer_actions):
-            # Reset agent's model_settings
-            if agent.model_settings.tool_choice == "required" or isinstance(agent.model_settings.tool_choice, str):
-                # Create a new model_settings to avoid modifying the original shared instance
-                agent.model_settings = ModelSettings(
-                    temperature=agent.model_settings.temperature,
-                    top_p=agent.model_settings.top_p,
-                    frequency_penalty=agent.model_settings.frequency_penalty,
-                    presence_penalty=agent.model_settings.presence_penalty,
-                    tool_choice="auto",  # Reset to auto
-                    parallel_tool_calls=agent.model_settings.parallel_tool_calls,
-                    truncation=agent.model_settings.truncation,
-                    max_tokens=agent.model_settings.max_tokens,
+        if processed_response.functions or processed_response.computer_actions:
+            tools = agent.tools
+            # Only reset in the problematic scenarios where loops are likely unintentional
+            if cls._should_reset_tool_choice(agent.model_settings, tools):
+                agent.model_settings = dataclasses.replace(
+                    agent.model_settings,
+                    tool_choice="auto"
                 )
-            
-            # Also reset run_config's model_settings if it exists
-            if run_config.model_settings and (run_config.model_settings.tool_choice == "required" or 
-                                             isinstance(run_config.model_settings.tool_choice, str)):
-                # Create a new model_settings for run_config
-                run_config.model_settings = ModelSettings(
-                    temperature=run_config.model_settings.temperature,
-                    top_p=run_config.model_settings.top_p,
-                    frequency_penalty=run_config.model_settings.frequency_penalty,
-                    presence_penalty=run_config.model_settings.presence_penalty,
-                    tool_choice="auto",  # Reset to auto
-                    parallel_tool_calls=run_config.model_settings.parallel_tool_calls,
-                    truncation=run_config.model_settings.truncation,
-                    max_tokens=run_config.model_settings.max_tokens,
+
+            if (
+                run_config.model_settings and
+                cls._should_reset_tool_choice(run_config.model_settings, tools)
+            ):
+                run_config.model_settings = dataclasses.replace(
+                    run_config.model_settings,
+                    tool_choice="auto"
                 )
 
         # Second, check if there are any handoffs
@@ -328,6 +317,24 @@ async def execute_tools_and_side_effects(
                 next_step=NextStepRunAgain(),
             )
 
+    @classmethod
+    def _should_reset_tool_choice(cls, model_settings: ModelSettings, tools: list[Tool]) -> bool:
+        if model_settings is None or model_settings.tool_choice is None:
+            return False
+
+        # for specific tool choices
+        if (
+            isinstance(model_settings.tool_choice, str) and
+            model_settings.tool_choice not in ["auto", "required", "none"]
+        ):
+            return True
+
+        # for one tool and required tool choice
+        if model_settings.tool_choice == "required":
+            return len(tools) == 1
+
+        return False
+
     @classmethod
     def process_model_response(
         cls,