Feature: Google ai studio improvements

[Pento95]

• Fix thinkingConfig for Google models: correct level mapping per model family — Gemini 2.5 uses thinkingBudget (0 = disabled, -1 = unlimited, with per-effort budgets), Gemini 3.x uses thinkingLevel (low/medium/high), Gemma 4 uses thinkingLevel (minimal/high only).
• Dynamic image model fetching: Google image models are now fetched from the same /models?pageSize=200 endpoint used for text, filtered by predict method or -image/nano-banana in the model ID. Hardcoded list replaced with live data + fallback.
• Rewrite Google image provider: replaces direct HTTP :predict calls with the Vercel AI SDK's generateImage() + google.image(). Supports Imagen 4/Ultra/Fast and all Gemini image models (gemini--image, nano-banana-) transparently through the same code path.
• isGoogleImageModel() helper: Gemini image models are excluded from the text model list and included in the image model list instead.
• Imagen 4 img2img support: imagen-4.0-generate-001 now correctly reports supportsImg2Img: true.
• Reference profile UX: removed the model filter on the reference profile selector (all models now visible); replaced with an inline warning when the selected model doesn't support img2img.
• Rename provider label from Google Imagen to Google AI Studio.

[gemini-code-assist]

Code Review

This pull request refactors the Google image provider to use the Vercel AI SDK, enables dynamic model fetching for Google AI Studio, and improves the handling of reasoning configurations for Gemini and Gemma models. It also adds UI warnings for models that do not support img2img in reference profiles. The review feedback suggests using the createTimeoutFetch utility for network requests and ensuring API keys are URL-encoded in query parameters for better robustness and correctness.