jevjam

[jevjam: typed decisions from small models, as MCP tools and a Jev-compatible HTTP API]

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jevjam

Self-hosted MCP server and Jev-compatible HTTP API for small decision models, on one GPU, in Docker.

Ask a model typed questions about a piece of text, JSON, an image or a video, and get calibrated answers back in milliseconds: pick a label (choice), rate on a scale (score), or answer yes or no (noul). Agents call it as MCP tools; services call POST /v1/systemone, the same protocol as TypeSafe Jev, so a Jev client only needs a new base URL.

Use it to route tickets, flag abuse, guard tool calls, pick a model for a prompt, or any other decision you would rather not spend a large LLM call on.

Models

One checkpoint stays in VRAM at a time, and it is freed after five idle minutes. See docs/models.md for sizes, quantization and limits.

Quick start

You need Docker, an NVIDIA GPU, and the NVIDIA Container Toolkit.

docker run -d --name jevjam --gpus all -p 127.0.0.1:8000:8000 \  -v jevjam-models:/models ghcr.io/beremaran/jevjam:latest

Or, from a clone, docker compose up -d. No model downloads at boot; the first request fetches what it needs into the jevjam-models volume, which takes minutes once.

Ask over HTTP:

curl -s http://127.0.0.1:8000/v1/systemone -H 'Content-Type: application/json' -d '{  "state": "We were billed twice for March. Refund it today or we cancel.",  "questions": {    "department": {"type": "choice", "instructions": "Who should handle this?",                   "criteria": {"billing": "payments, refunds", "technical": "bugs, outages"}},    "churn_risk": {"type": "noul", "instructions": "Does the user threaten to leave?"}  }}'

The answer, trimmed:

{  "answers": {    "department": {"type": "choice", "choice": "billing", "probabilities": {"billing": 0.97, "technical": 0.03}, ...},    "churn_risk": {"type": "noul", "noul": 0.82, ...}  },  "routing": {"model": "english", "reason": "English Latin text", ...}}

Or connect an agent over MCP, at http://127.0.0.1:8000/mcp:

claude mcp add --transport http jevjam http://127.0.0.1:8000/mcp   # Claude Codecodex mcp add jevjam --url http://127.0.0.1:8000/mcp                 # Codex

Agents get four tools: jevjam_predict, jevjam_preset (guard, moderation, triage, model_router), jevjam_route and jevjam_status. The MCP guide covers OpenCode, Pi, remote access and reverse proxies.

Features

• One process, two doors. The HTTP API and MCP share one queue and one resident model, so neither starves the other of VRAM.
• Sleeps when idle. After JEVJAM_IDLE_TIMEOUT seconds (300 by default) every checkpoint is freed and the GPU memory goes back to the driver. The next request loads only what it needs; Laya wakes in 0.6 s on an RTX 4070 Ti SUPER.
• Fits the card it finds. clef-flash loads in BF16, 8-bit, 4-bit, or split across GPU and CPU, whichever fits.
• Drop-in for Jev. Same request and response shapes; unknown fields are ignored.
• Locked down by default. Runs as non-root, binds to loopback in Compose, and takes an optional bearer key (JEVJAM_API_KEY) for both endpoints.

Docs

Moving from laya-docker

This repo used to be laya-docker. The old image, ghcr.io/beremaran/laya-docker, gets no more updates; switch to ghcr.io/beremaran/jevjam. Old LAYA_* settings still work and log a warning; see Configuration.

Contributing

Bug reports and pull requests are welcome; see CONTRIBUTING.md. Report security problems privately, as SECURITY.md describes.

License

jevjam is licensed under Apache-2.0. The image also contains the Apache-2.0 Laya package and checkpoints by Convai Innovations, the Apache-2.0 Julia-1 code and checkpoint by Supersonic Labs, and the Apache-2.0 clef-flash code and checkpoint by Cloudflare. The clef-flash code is copied into src/jevjam/vendor/ with its license.