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v1.14.0-ce — Native Vision

Released: 2026-07-29 · Tag: v1.14.0-ce · Docker: synapcores/community:v1.14.0-ce

Your database can see now. v1.14.0-ce ships native, in-process multimodal vision — send an image, ask a question, get an answer, generated on your own hardware with no cloud key and no second service to run.

Native vision — POST /v1/multimodal/describe

A new REST endpoint interprets an image with a vision LLM, entirely inside the gateway process:

curl -X POST http://127.0.0.1:8080/v1/multimodal/describe \
  -H "Authorization: Bearer $TOKEN" -H "Content-Type: application/json" \
  -d '{
    "prompt": "Describe this image in one sentence.",
    "image": "<base64 image>",
    "provider": "local",
    "model": "llava"
  }'
# → { "text": "…", "model": "llava" }
  • Native + in-process. The vision model runs in the same process as your database via a safe libmtmd / LLaVA binding. No cloud round-trip, no external daemon, no API key. The image never leaves the box.
  • CPU-friendly. Validated on commodity, non-AVX-512 hardware — no GPU required.
  • Bring your own model, or ours. Defaults to LLaVA; set model per request or AIDB_VISION_MODEL to point at the vision model you prefer. Cloud providers (openai, anthropic, ollama) still work when configured.

Pull a vision model into the in-process registry once, then it's available with no daemon:

docker run --rm -v synapcores-data:/var/lib/synapcores \
  synapcores/community:v1.14.0-ce pull llava

Why it matters

Vision used to mean shipping your images to someone else's server, per-call billing, and hoping the data was allowed to leave. Now SynapCores does it locally, privately, on hardware you already run — alongside the SQL, vectors, knowledge graph, native LLMs, and agents already in the engine. Give an in-database AGENT_RUN workflow eyes; read scanned documents where they land; triage inspection photos next to the rows that describe the asset.

Validation

On the published artifact: CI build of 4 Linux targets with the native libmtmd compile; feature_validator 88/88; recipe certification 158/162, zero regressions vs v1.13.0.1-ce; non-AVX-512 canary (i5-10400F) boots and runs all-minilm + llava with no illegal-instruction (ZMM instructions cpuid-gated); native vision end-to-end described a test image in-process on CPU on both the raw binary and the published Docker image.

Install

docker pull synapcores/community:v1.14.0-ce
# or:
curl -fsSL https://get.synapcores.com | SYNAPCORES_VERSION=v1.14.0-ce sh

Drop-in upgrade — no schema migration. The vision route is additive; the existing REST / WebSocket / SDK / MySQL-wire paths are unchanged.