fix(models): support DeepSeek V4.1 vision and max effort

Refresh the generated capability catalog from command-code@1.44.0 to
1.53.1. deepseek/deepseek-v4.1-flash now advertises image input and its
low, high, and max reasoning efforts, so pi forwards attached images and
exposes the full thinking-level selector instead of reporting the model
as text-only without selectable levels. The sync also adds gpt-6-astra,
xai/grok-4.6, and inclusionai/ling-3.0-flash-sante:free metadata.

Drop the now-obsolete manual Meta Muse Spark effort overrides because
upstream publishes efforts for meta/muse-spark-1.1 through 1.3-contributor
and MiniMaxAI/MiniMax-M3, and add a regression test for the V4.1
capabilities.

README.md

@@ -88,7 +88,7 @@ Other extensions that stream with the active Command Code model, such as backgro
 
 ### Reasoning support
 
-Reasoning capability and selectable effort levels follow the official CLI catalog independently. Models can therefore be marked as reasoning-capable even when Command Code chooses their depth automatically. Models with explicit effort support register a model-specific `thinkingLevelMap`, so pi and OMP expose only valid levels. For a few reasoning models the CLI catalog ships no effort levels although the endpoint accepts `reasoning_effort`; `src/commandcode-catalog-overrides.ts` adds a manual level set for those (currently `meta/muse-spark-1.1`, `meta/muse-spark-1.2`, and `meta/muse-spark-1.2-contributor`) on top of the generated catalog, and the tests fail once upstream publishes its own levels so the override gets removed. Pi's native OpenAI- and Anthropic-compatible providers translate the selected level for Provider API accounts; the existing Command Code generate transport sends the matching `reasoning_effort` for Go accounts.
+Reasoning capability and selectable effort levels follow the official CLI catalog independently. Models can therefore be marked as reasoning-capable even when Command Code chooses their depth automatically. Models with explicit effort support register a model-specific `thinkingLevelMap`, so pi and OMP expose only valid levels, including the opt-in `xhigh` and `max` levels. `src/commandcode-catalog-overrides.ts` can add a manual level set for reasoning models that the CLI catalog ships without efforts; it is currently empty because upstream publishes efforts for every selectable model, and the tests fail once upstream publishes levels for a model that still has a manual override. Pi's native OpenAI- and Anthropic-compatible providers translate the selected level for Provider API accounts; the existing Command Code generate transport sends the matching `reasoning_effort` for Go accounts.
 
 List Command Code models from the terminal:
 
@@ -139,7 +139,7 @@ The following environment variables are intended for tests, local mocks, and com
 
 ## Image input
 
-The provider advertises image input only for models marked with the `image` input modality in the official Command Code CLI model catalog. The capability snapshot currently follows `command-code@1.44.0`; unknown models default to text-only until their upstream metadata is reviewed. A daily GitHub Actions job synchronizes the CLI version, image capabilities, reasoning flags, reasoning efforts, and model-specific output limits with the latest published CLI package and opens or updates a reviewable pull request when they change. Pricing remains manually reviewed because temporary promotions and long-context tiers require explicit review.
+The provider advertises image input only for models marked with the `image` input modality in the official Command Code CLI model catalog. The capability snapshot currently follows `command-code@1.53.1`; unknown models default to text-only until their upstream metadata is reviewed. A daily GitHub Actions job synchronizes the CLI version, image capabilities, reasoning flags, reasoning efforts, and model-specific output limits with the latest published CLI package and opens or updates a reviewable pull request when they change. Pricing remains manually reviewed because temporary promotions and long-context tiers require explicit review.
 
 For vision-capable models, Pi's native provider adapters forward image blocks from user messages and tool results using the documented OpenAI or Anthropic message schema. Unknown and text-only models remain marked text-only in Pi.