Typed decisions (choice, score, yes/no) from Laya, Julia-1 and clef-flash on your own GPU
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.
| Model | By | Size | Reads | Picked when |
|---|---|---|---|---|
| Laya | Convai Innovations | 3 checkpoints, ~1.2B in all | text, JSON | by default; its router picks English, multilingual or typed-decisions |
| Julia-1 | Supersonic Labs | 144M | text, JSON | the request names julia-1 |
| clef-flash | Cloudflare | 9B | text, JSON, images, video | the request names clef-flash |
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.
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 Code
codex 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.
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.JEVJAM_API_KEY) for both endpoints.| Guide | What is in it |
|---|---|
| Configuration | Running, settings, the model cache, sleeping on idle |
| MCP server | Tools, auth, client setup, reverse proxies |
| HTTP API | /health, /v1/systemone, question types, JSON Schema, errors |
| Models | Laya, Julia-1 and clef-flash: sizes, VRAM, limits |
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.
Bug reports and pull requests are welcome; see CONTRIBUTING.md. Report security problems privately, as SECURITY.md describes.
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.
Source-derived launch command. Check the maintainer’s required arguments and credentials before running:
docker run -i --rm ghcr.io/beremaran/jevjam:0.3.3Merge this template into ~/Library/Application Support/Claude/claude_desktop_config.json. Keep existing servers. Add any arguments, credentials, and permissions required by the maintainer; this template has not been install-tested.
{
"mcpServers": {
"io-github-beremaran-jevjam": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/beremaran/jevjam:0.3.3"
]
}
}
}Restart Claude Desktop completely for changes to take effect. Confirm the server appears connected in the client’s tool list, then try a read-only example from its documentation.
Claude Desktop setup referenceghcr.io/beremaran/jevjam:0.3.3dockerjevjam works with any MCP-compatible client. Copy the config snippet from the Configuration section above and add it to the file shown for your client, then restart the application.
~/Library/Application Support/Claude/claude_desktop_config.jsonRestart Claude Desktop completely for changes to take effect.~/.cursor/mcp.jsonRestart Cursor for changes to take effect..vscode/mcp.jsonReload VS Code window for changes to take effect.~/.codeium/windsurf/mcp_config.jsonRestart Windsurf for changes to take effect..mcp.jsonSave at the project root, then start Claude Code in that project and review the MCP server approval prompt. Keep real credentials out of shared files.