Add tool_choice setting

[dsfaccini]

Closes #2799

Adds tool_choice to ModelSettings, letting users control how the model interacts with function tools.

Currently Pydantic AI internally decides whether to use tool_choice='auto' or 'required' based on output configuration, but users have no way to override this. The workaround was using extra_body={'tool_choice': 'none'} which is provider-specific and doesn't work everywhere.

This PR allows the user to set tool_choice to:

• 'auto' - model decides whether to call tools
• 'required' - model must call a tool
• 'none' - model can't use function tools
• ['tool_a', 'tool_b'] - model must use one of these specific tools

One important distinction: this only affects function tools (the ones you register on the agent), not output tools (used internally for structured output). So if you have an agent with output_type=SomeModel
and you set tool_choice='none', the output tool stays available - you'll just get a warning about it.

Implementation is spread across all model providers since each has its own API format for tool_choice.
Added a resolve_tool_choice utility that handles validation (checking tool names exist, warning about
conflicts with output tools) and returns a normalized representation that each provider then maps to their specific format.

Bedrock is a bit of a special case - it doesn't support 'none' at all, so we fall back to 'auto' with a warning. Anthropic has a constraint where 'required' and specific tool selection don't work with thinking/extended thinking enabled.

TODO

• document this somewhere in the docs

[dsfaccini]

haven't integrated reviewed the code with #1820 in mind, so putting this back to draft