Kev Model Deploy
Deploys the Kev decision model as a private HTTPS endpoint on Modal.
Install
npx skills add jaredpalmer/kev --skill kev-deploy -g -a claude-code -y- Repository
- jaredpalmer/kev9.8k
- Category
- DevOps
- Updated
- 8d ago
- License
- Apache-2.0
- Context cost
- Mediumabout 2,986 tokens
- Runs scripts
- Yes, review before use
What it does
Deploy a Kev decision model (the open Jev-style System One model) as the user's own TypeSafe-compatible HTTPS endpoint on Modal with one command, wire it into their code, and take it down. Use when someone wants to host Kev, get a Kev API URL, replace Jev / TypeSafe calls with a self-hosted model, pick a Kev size or GPU, add an API key, keep an endpoint warm, or stop and remove a Kev deployment.
Deploy Kev on Modal
scripts/kev_serve.py is a single self-contained Modal app. modal deploy on it builds an image with the kev package at
a pinned commit, loads a Kev checkpoint from the Hugging Face Hub on a GPU sized for it, and serves TypeSafe's System One
protocol (POST /v1/systemone, GET /v1/models) at https://<workspace>--kev-api.modal.run. It scales to zero when idle.
The file is short on purpose: if the user's case does not fit, read it and edit it.
1. Check the prerequisites
pip install modal==1.5.5
modal profile current 2>/dev/null || modal setup # opens a browser to sign in; the user must do this step
modal skills install -y # optional: Modal's own agent skill + docs (into .agents/, or -g for home)
If modal setup is needed, tell the user and wait; do not try to authenticate for them. modal skills install gives you
Modal's official skill and documentation, which helps with anything beyond this file: GPUs, secrets, volumes, logs, billing.
2. Pick the model
KEV_MODEL | GPU (automatic; fallbacks in parentheses) | $/h while up | Model time, 6 questions (new / repeated state) | Cold start (cached weights) | When |
|---|---|---|---|---|---|
jaredpalmer/kev-0.8b | L4 (L40S) | 0.80 | 23 / 16 ms | ~40 s | cheapest, prototyping |
jaredpalmer/kev-4b (default) | L40S (H100) | 1.95 | 42 / 28 ms (H100: 18 / 13 ms) | ~35 s | the default: best quality per dollar |
jaredpalmer/kev-9b | H100 (H200, L40S) | 3.95 | 24 / 17 ms | ~55 s | accuracy on smaller GPUs |
jaredpalmer/kev-27b | B200 (H200, H100) | 6.25 | 47 / 32 ms (H200: 67 / 50 ms) | ~50 s | best released accuracy; 51 GB of full weights |
