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Ettore Di Giacinto
c7f278dd0d
Assisted-by: Claude Code:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
104 lines
3.5 KiB
Markdown
104 lines
3.5 KiB
Markdown
+++
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disableToc = false
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title = "SystemOne decisions"
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weight = 66
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url = "/features/systemone/"
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+++
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SystemOne is an API for fast, typed decisions. You send a piece of text (the
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*state*) and a set of named questions. A decision model answers each question
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with a value and a confidence, in one pass. The model does not generate text, so
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there is nothing to parse and no free-form output to validate.
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The request and response shapes follow the [kev](https://github.com/jaredpalmer/kev)
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project and match the `/v1/systemone` endpoint that Ollama added in 0.35.
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## Endpoints
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| Endpoint | Method | Description |
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|---|---|---|
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| `/v1/systemone` | POST | Answer all questions in one pass |
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| `/v1/systemone/permute` | POST | Re-run one choice question under `n_perm` option orders |
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| `/v1/systemone/separate` | POST | Answer each question in its own pass |
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## Question types
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| Type | Answer | Fields in the answer |
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|---|---|---|
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| `choice` | One option out of a named set | `choice`, `probabilities`, `confidence` |
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| `noul` | Yes, no or unknown for a statement | `noul` (0 to 1), `entities` |
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| `score` | One level on a scale | `score`, `legend`, `probabilities`, `confidence` |
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## Example
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```bash
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curl http://localhost:8080/v1/systemone -H "Content-Type: application/json" -d '{
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"model": "laya-vllm-cpp",
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"state": "My order arrived broken and I want my money back. This is the second time.",
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"questions": {
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"team": {
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"type": "choice",
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"instructions": "Which team should handle this ticket?",
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"criteria": {
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"billing": "Payments, invoices and refunds",
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"shipping": "Delivery and damaged goods",
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"product": "Questions about how the product works"
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}
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},
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"refund_requested": {
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"type": "noul",
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"instructions": "The customer explicitly asks for a refund"
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},
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"urgency": {
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"type": "score",
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"instructions": "How urgent is this ticket?",
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"criteria": ["not urgent", "somewhat urgent", "urgent", "critical"]
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}
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}
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}'
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```
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Every answer carries a `confidence` value, and the response reports token usage
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and `latency_ms`.
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## Choosing a model
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A model can serve SystemOne only if it is a decision model. Declare the usecase
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in the model config:
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```yaml
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name: laya
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backend: vllm-cpp
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known_usecases:
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- systemone
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parameters:
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model: convaiinnovations/laya
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```
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`systemone` is never guessed, and a model that declares it is not listed as a
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chat, completion or embeddings model. A model that declares usecases without
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`systemone` or `token_classify` gets a `400` from these endpoints that names the
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missing usecase. A config that declares no usecases at all keeps working, so
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setups that predate the flag are not broken. Models that declare `token_classify`
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are served by the zero-shot NER path.
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Install one from the gallery and filter on the `systemone` tag:
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| Gallery entry | Model | Notes |
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|---|---|---|
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| `laya-vllm-cpp` | Laya | ModernBERT-large, non-autoregressive, about 800 MB |
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| `gliner25-decide-vllm-cpp` | GLiNER2.5-Decide | DeBERTa-v3-large with a classification head, about 2 GB |
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The engine, [vllm.cpp]({{% relref "features/vllm-cpp" %}}), also supports the
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kev, CLM and xor decision models. Those checkpoints need a conversion step, so
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they are not gallery entries yet.
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Tev1 is an autoregressive decision model. It answers through chat completions
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and does not serve `/v1/systemone` yet.
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## Access control
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When authentication is on, the three routes need the `systemone` feature. It is
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on by default for every user, like the other API features, and an administrator
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can turn it off per user.
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