feat: add PrimingGroup and MLPipeline SDK methods

[brandon-wada]

Summary

Adds SDK methods for the new PrimingGroup public API. Priming Groups are groupings of detectors that share a common semantic query and can utilize a common base model. In the future, priming groups may allow for cross detector learning and other multi-task and meta-learning techniques.

In introducing priming groups, we also expose MLPipelines. Every detector has one active MLPipeline but constantly runs multiple MLPipelines under the hood that are compared against the top performing active model. Whenever Groundlight determines that there is a better performing model, we will switch that model to be the active model.

Currently, a priming group can be created from an existing and trained MLPipeline, which one can get given an active detector. The new PrimingGroup will use a frozen version of the MLPipeline for the first inference on a new detector created using the PrimingGroups. If shadow pipelines are disallowed on the PrimingGroup, that frozen model will be used indefinitely by the detector. Otherwise, the frozen model will be used until one of the other MLPipelines on the detector is evaluated to be a better fit.

We add the following methods in this PR

• list_detector_pipelines(detector) — list all MLPipelines for a detector
• create_priming_group(name, source_ml_pipeline_id, ...) — create a PrimingGroup seeded from an existing trained model
• list_priming_groups() — list all priming groups owned by this account
• get_priming_group(priming_group_id) — retrieve by ID
• delete_priming_group(priming_group_id) — soft-delete

We also add new pydantic models: MLPipeline, PrimingGroup in generated/model.py.

Usage

```python
gl = Groundlight()

pipelines = gl.list_detector_pipelines(detector)
active = next(p for p in pipelines if p.is_active_pipeline and p.cached_vizlogic_key)

pg = gl.create_priming_group(
name="door-detector-primer",
source_ml_pipeline_id=active.id,
canonical_query="Is the door open?",
disable_shadow_pipelines=True,
)

new_detector = gl.create_detector(
name="new-door-detector",
query="Is the door open?",
priming_group_id=pg.id,
)
```