feat(gom-53): integrated external model registry for metadata enrichment and cost tracking + Dashboard/Usage page

[SantiagoDePolonia]

Fetch, cache, and merge the ai-model-list registry (models.json) to enrich discovered models with pricing, capabilities, and context limits. Models not in the registry still work — the fetch is best-effort and never gates.

• Add ModelListConfig (URL + timeout) to CacheConfig with env var support
• Add ModelListData to ModelCache for raw JSON persistence across restarts
• Add ModelMetadata/ModelPricing to core.Model (omitempty, pointer numerics)
• New internal/modeldata package: fetcher, 3-layer merger, enricher
• Registry integration: enrich on Initialize, LoadFromCache, and refresh
• Background refresh re-fetches model list alongside provider models
• Add cost fields (InputCost/OutputCost/TotalCost) to UsageEntry
• CalculateCost + variadic pricing param on all three usage extractors

Summary by CodeRabbit

• New Features
  • Usage Analytics page: date picker, tokens/costs toggle, estimated-cost card, charts, per-model aggregation, filters and paginated request logs.
  • Model browsing by category with counts and per-category pricing; external model metadata registry with background fetch and UI enrichment.
  • Granular cost calculation and per-request cost fields surfaced in usage views and logs.
• Documentation
  • API docs updated with new usage and category endpoints and expanded model/usage schemas.
• Tests
  • Large expansion of unit tests across model data, pricing, usage extraction, readers, and storage.
• Chores
  • Removed unused indirect dependencies.