version: 0.27.1 title: Voyage multimodal embeddings + image ingestion date: 2026-05-05 feature_pitch: | gbrain remembers what you SAW, not just what you typed. Drop a screenshot, whiteboard photo, or iPhone HEIC into your brain repo, run sync, and the image lands as a first-class page with a 1024-dim Voyage multimodal embedding. Optionally turn on OCR and gpt-4o-mini extracts the visible text — whiteboard captures become keyword-searchable in one move.

v0.27.1 migration

gbrain upgrade runs gbrain apply-migrations --yes automatically, which applies migration v36. Most users need no manual action.

What changes

Schema: content_chunks.modality TEXT NOT NULL DEFAULT 'text' and content_chunks.embedding_image vector(1024) with a partial HNSW index. Existing text + code chunks continue to work unchanged (modality defaults to 'text', embedding_image is NULL on those rows).
Schema (PGLite): the files table that v0.18 deliberately omitted is added on PGLite. Postgres has had it since v0.18; this is parity.
Schema (both): pages.page_kind CHECK constraint widened to admit 'image'. The migration drops + recreates the auto-named constraint idempotently.
Off by default: nothing changes at runtime until you flip embedding_multimodal: true (DB plane via gbrain config set or env via GBRAIN_EMBEDDING_MULTIMODAL=true).

Verification

gbrain apply-migrations --yes
gbrain doctor                # schema_version should be 36+

If gbrain doctor reports a schema_version warning, run apply-migrations manually and check ~/.gbrain/upgrade-errors.jsonl for details.

Enabling multimodal ingestion

The feature is opt-in. To turn it on:

# Required: switch to Voyage 1024-dim embeddings (or keep your existing
# 1024-dim Voyage brain).
gbrain config set embedding_model voyage:voyage-3-large
gbrain config set embedding_dimensions 1024

# Required: flip the multimodal gate.
gbrain config set embedding_multimodal true

# Optional: enable OCR via gpt-4o-mini (~$0.0003 per image).
gbrain config set embedding_image_ocr true

Drop image files (PNG, JPG, JPEG, GIF, WEBP, HEIC, AVIF) into your brain repo and run gbrain sync. The image lands as a type: image page with:

1024-dim Voyage multimodal embedding in content_chunks.embedding_image
File metadata in the files table (storage_path, mime_type, content_hash)
EXIF metadata in frontmatter (captured_at, gps, camera, dims)
Optional OCR text in compiled_truth (when the OCR flag is on)
Auto-linked image_of graph edge to a sibling text page if one exists

pgvector requirement

Migration v36 requires pgvector >= 0.5.0 on Postgres (HNSW partial indexes). PGLite ships a recent pgvector inside its WASM bundle, so this gate only applies to managed-Postgres brains (Supabase, RDS, etc.).

If your provider runs pgvector < 0.5, the migration handler refuses BEFORE running any DDL with this fix hint:

ALTER EXTENSION vector UPDATE;

Then re-run gbrain apply-migrations --yes. If your provider doesn't ship pgvector >= 0.5 at all, request an upgrade or migrate to PGLite for v0.27.1 multimodal support.

Cost expectations

Voyage multimodal: free tier covers 200K calls/month. 1 call = 1 image (or up to 32 images batched). Beyond the free tier: see Voyage's pricing.
OCR via gpt-4o-mini: ~$0.0003 per image. Off by default; only runs when embedding_image_ocr=true.
Storage: image bytes never enter the DB. They live on disk in your brain repo (the same place markdown lives). Only metadata + embeddings go to the database.

What's NOT included (for v0.27.2+)

gbrain query --image <path> flag for image-similarity search.
Cross-modal text→image fusion (text query → image hits via RRF).
PDF page rasterization.
Video keyframe extraction (waits on Voyage 3.5 multimodal video model).
OpenAI / Cohere multimodal embed support.