docs: post-ship doc sweep for v0.42.57.0 provider-agnostic gateway wave

- KEY_FILES.md types.ts entry: document EmbeddingTouchpoint.trust_custom_dims
  (#2271 passthrough tier, runs after dims_options + Matryoshka allowlists)
- ENGINES.md: embedding design-choice note now names the provider-agnostic
  gateway delegation instead of the stale OpenAI-only parenthetical
- embedding-providers.md: drop an exact-duplicate doctor-8c paragraph
- llms-full.txt regenerated (ENGINES.md is inlined in the bundle)

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

docs/ENGINES.md

@@ -94,7 +94,7 @@ export interface BrainEngine {
 
 **Slug-based API, not ID-based.** Every method takes slugs, not numeric IDs. The engine resolves slugs to IDs internally. This keeps the interface portable... slugs are strings, IDs are database-specific.
 
-**Embedding is NOT in the engine.** The engine stores embeddings and searches by vector, but it doesn't generate embeddings. `src/core/embedding.ts` handles that. This is intentional: embedding is an external API call (OpenAI), not a storage concern. All engines share the same embedding service.
+**Embedding is NOT in the engine.** The engine stores embeddings and searches by vector, but it doesn't generate embeddings. `src/core/embedding.ts` handles that (a thin delegation to the provider-agnostic AI gateway in `src/core/ai/gateway.ts`). This is intentional: embedding is an external API call (OpenAI, Voyage, a local Ollama — whichever provider you configured), not a storage concern. All engines share the same embedding service.
 
 **Chunking is NOT in the engine.** Same logic. `src/core/chunkers/` handles chunking. The engine stores and retrieves chunks. All engines share the same chunkers.
 

docs/integrations/embedding-providers.md

@@ -187,5 +187,3 @@ The supported paths:
 - **Postgres (Supabase / self-hosted):** follow the SQL recipe in `docs/embedding-migrations.md` (drop the HNSW index, ALTER COLUMN TYPE, clear stale embeddings, recreate the index conditionally, then `gbrain init --supabase --embedding-model X --embedding-dimensions N` to update the file plane and re-embed).
 
 `gbrain doctor` 8c "alternative_providers" surfaces unconfigured providers whose env is already set — useful when you've configured OpenAI but also have e.g. `VOYAGE_API_KEY` exported and want to know you can switch without extra setup.
-
-`gbrain doctor` 8c "alternative_providers" surfaces unconfigured providers whose env is already set — useful when you've configured OpenAI but also have e.g. `VOYAGE_API_KEY` exported and want to know you can switch without extra setup.

llms-full.txt

@@ -2039,7 +2039,7 @@ export interface BrainEngine {
 
 **Slug-based API, not ID-based.** Every method takes slugs, not numeric IDs. The engine resolves slugs to IDs internally. This keeps the interface portable... slugs are strings, IDs are database-specific.
 
-**Embedding is NOT in the engine.** The engine stores embeddings and searches by vector, but it doesn't generate embeddings. `src/core/embedding.ts` handles that. This is intentional: embedding is an external API call (OpenAI), not a storage concern. All engines share the same embedding service.
+**Embedding is NOT in the engine.** The engine stores embeddings and searches by vector, but it doesn't generate embeddings. `src/core/embedding.ts` handles that (a thin delegation to the provider-agnostic AI gateway in `src/core/ai/gateway.ts`). This is intentional: embedding is an external API call (OpenAI, Voyage, a local Ollama — whichever provider you configured), not a storage concern. All engines share the same embedding service.
 
 **Chunking is NOT in the engine.** Same logic. `src/core/chunkers/` handles chunking. The engine stores and retrieves chunks. All engines share the same chunkers.