adds support for gemini API

[charchit7]

What

Adds Google Gemini as a first-class model provider, selectable via the
gemini/<model> (Google AI Studio) and vertex_ai/<model> (Vertex AI) id
prefixes.

Previously any gemini/� id fell through to the HuggingFace router catch-all
and was misrouted (e.g. openai/gemini/�). This wires Gemini through
LiteLLM's native Google adapters instead.

Changes

• agent/core/llm_params.py: new gemini/ + vertex_ai/ branch in
  _resolve_llm_params. Forwards reasoning_effort as a top-level kwarg,
  which LiteLLM translates into the thinking budget for Gemini 2.5+ thinking
  models. Adds _GEMINI_EFFORTS = {low, medium, high}; minimal normalizes
  to low, and xhigh/max are handled by the existing effort cascade
  (no per-model capability table, consistent with the other providers).
• agent/core/model_switcher.py: adds gemini/gemini-2.5-pro and
  gemini/gemini-2.5-flash to the /model suggestions, marks gemini/ and
  vertex_ai/ as direct prefixes (skip the HF router catalog lookup), and
  updates the /model help text and is_valid_model_id docstring.
• tests/unit/test_llm_params.py: 6 new tests â�� effort forwarding,
  vertex_ai/ route, minimal�low normalization, strict-mode rejection of
  unsupported efforts, non-strict effort drop, and that Gemini is not routed
  through the HF router.

Usage

export GEMINI_API_KEY=...            # AI Studio route
ml-intern --model gemini/gemini-2.5-pro
# or, in-session:  /model gemini/gemini-2.5-pro

@lewtun Please review whenever you are free.