Feature Request: Support service_tier (e.g. flex) for Gemini provider

[Twanislas]

Feature Request

Gemini recently launched Flex Inference (service_tier: "flex"), which offers a 50% cost reduction for batch/background workloads where real-time latency isn't critical. This is a perfect match for Hermes's cron jobs and background subagents.

See documentation: https://ai.google.dev/gemini-api/docs/flex-inference

The Problem

Currently, users cannot utilize the Flex tier in Hermes because:

1. The newly merged agent/gemini_native_adapter.py (from feat(providers): route gemini through the native AI Studio API #12674) does not map service_tier from api_kwargs / request_options into the native Google generateContent JSON payload.
2. The open PR Support OpenAI service_tier across direct API and openai-codex routes #5157 proposes restricting service_tier exclusively to OpenAI routes. If merged as-is, it will actively strip the parameter from Gemini calls.

Proposed Solution

1. Update gemini_native_adapter.py: Intercept service_tier from api_kwargs and inject it into the native request body:

json
    {
      "contents": [...],
      "service_tier": "flex"
    }

2. Exempt Gemini from PR Support OpenAI service_tier across direct API and openai-codex routes #5157: Ensure that hermes_cli/runtime_provider.py (or wherever route validation happens) recognizes gemini as a valid provider for service_tier.

Use Case

Hermes heavily utilizes cron jobs and background delegation tasks (via delegate_task). Halving the LLM cost for these asynchronous, non-interactive workflows using Gemini would be a massive efficiency gain for users.

Thank you!