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LocalAI/docs/content/features/systemone.md
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Ettore Di Giacinto b3d65fd538 fix(systemone): route NER models to the NER path and refuse decision models on permute and separate
vllm_decide refuses NER architectures and the NER entry point refuses decision
architectures, so each model kind 500ed on half of the routes. A token_classify
model now goes to the NER path on /v1/systemone, and /permute and /separate
return 400 for decision models. Docs and instructions state which kind serves
which route.

Assisted-by: Claude Code:claude-sonnet-5-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-09-30 11:55:26 +00:00

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4.1 KiB
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+++
disableToc = false
title = "SystemOne decisions"
weight = 66
url = "/features/systemone/"
+++
SystemOne is an API for fast, typed decisions. You send a piece of text (the
*state*) and a set of named questions. A decision model answers each question
with a value and a confidence, in one pass. The model does not generate text, so
there is nothing to parse and no free-form output to validate.
The request and response shapes follow the [kev](https://github.com/jaredpalmer/kev)
project and match the `/v1/systemone` endpoint that Ollama added in 0.35.
## Endpoints
| Endpoint | Method | Description |
|---|---|---|
| `/v1/systemone` | POST | Answer all questions in one pass |
| `/v1/systemone/permute` | POST | Re-run one choice question under `n_perm` option orders |
| `/v1/systemone/separate` | POST | Answer each question in its own pass |
Which route a model can serve depends on its kind:
| Model kind | `/v1/systemone` | `/permute` and `/separate` |
|---|---|---|
| Decision model (`systemone`), such as Laya or GLiNER2.5-Decide | Yes | No, returns `400` |
| Zero-shot NER model (`token_classify`), such as GLiNER2.5 | Yes, through the NER path | Yes |
## Question types
| Type | Answer | Fields in the answer |
|---|---|---|
| `choice` | One option out of a named set | `choice`, `probabilities`, `confidence` |
| `noul` | Yes, no or unknown for a statement | `noul` (0 to 1), `entities` |
| `score` | One level on a scale | `score`, `legend`, `probabilities`, `confidence` |
## Example
```bash
curl http://localhost:8080/v1/systemone -H "Content-Type: application/json" -d '{
"model": "laya-vllm-cpp",
"state": "My order arrived broken and I want my money back. This is the second time.",
"questions": {
"team": {
"type": "choice",
"instructions": "Which team should handle this ticket?",
"criteria": {
"billing": "Payments, invoices and refunds",
"shipping": "Delivery and damaged goods",
"product": "Questions about how the product works"
}
},
"refund_requested": {
"type": "noul",
"instructions": "The customer explicitly asks for a refund"
},
"urgency": {
"type": "score",
"instructions": "How urgent is this ticket?",
"criteria": ["not urgent", "somewhat urgent", "urgent", "critical"]
}
}
}'
```
Answers from a decision model carry a `confidence` value, and the response
reports token usage and `latency_ms`. The NER path does not report token usage.
## Choosing a model
A model can serve SystemOne only if it is a decision model. Declare the usecase
in the model config:
```yaml
name: laya
backend: vllm-cpp
known_usecases:
- systemone
parameters:
model: convaiinnovations/laya
```
`systemone` is never guessed, and a model that declares it is not listed as a
chat, completion or embeddings model. A model that declares usecases without
`systemone` or `token_classify` gets a `400` from these endpoints that names the
missing usecase. A model that declares `token_classify` and not `systemone` is
served by the zero-shot NER path. A vllm-cpp config that declares no usecases is
treated as a decision model, so setups that predate the flag keep working, but a
config that declares only `chat` (as an older `laya` gallery entry did) now gets
the `400` and needs `known_usecases: [systemone]`.
Install one from the gallery and filter on the `systemone` tag:
| Gallery entry | Model | Notes |
|---|---|---|
| `laya-vllm-cpp` | Laya | ModernBERT-large, non-autoregressive, about 800 MB |
| `gliner25-decide-vllm-cpp` | GLiNER2.5-Decide | DeBERTa-v3-large with a classification head, about 2 GB |
The engine, [vllm.cpp]({{% relref "features/vllm-cpp" %}}), also supports the
kev, CLM and xor decision models. Those checkpoints need a conversion step, so
they are not gallery entries yet.
Tev1 is an autoregressive decision model. It answers through chat completions
and does not serve `/v1/systemone` yet.
## Access control
When authentication is on, the three routes need the `systemone` feature. It is
on by default for every user, like the other API features, and an administrator
can turn it off per user.