# Send a fixed text once

> Register a long, fixed text, such as a policy or a rubric, once as the task's context; on a Mac each request then reads only what changes, and on any engine requests get smaller.

Source: https://opendecisio.com/docs/tasks/context/

Every request of a [task](https://opendecisio.com/docs/glossary/#task) is often read against the same long text: a policy, a rubric, a catalogue, a set of definitions. Register that text once as the task’s context, and each request sends only the part that changes; the server puts the context in front of it. On a Mac, a 1,176-token moderation policy sent as the context took 373 ms a read, against 1,946 ms when every request carried it:

 

[Figure: Save the fixed policy with the task; send only the new message. Register the task: Store the fixed policy as its context, beside the question.. Send a message: Put only the changing message in state.. Answer with context: The model reads the task context with this new message.. Use the result: Your backend reads the typed answer as usual..]

 

## 1 See where it works great

  

| Engine | The policy at the start of every request | The policy as the task’s context |
| --- | --- | --- |
| MLX, an Apple M5 Pro | 1,946 ms a read | 373 ms a read |
| vLLM, an RTX PRO 6000 | 61.4 ms p50 | 60.8 ms p50 |

 

decisio’s measurement with a 1,176-token moderation policy and short comments to judge, the tuned 12B, one question per request, requests one at a time: the MLX conversion on an Apple M5 Pro, the mean of 600 reads; the 12B in bf16 on vLLM 0.31.0 and one RTX PRO 6000, 40 requests, as decisio’s docs/tasks.md states them.

 

- **On a Mac each request computes only its changing part.** MLX’s prefix cache finds only exactly the same prefix, so a policy at the start of every request is computed again each time; as the context it is a cache entry of its own, and each request computes only its changing part.
- **On vLLM the answers are the same, and the requests smaller.** vLLM’s prefix cache already reuses a prefix every request repeats, so the two run at the same speed; the context is held from the task’s first request.
- **A fast table learns from the part that changes,** since it encodes the state alone.

 

## 2 Register it

 

Prepare a complete `task.json` registration with your real examples, as [Teach a task](https://opendecisio.com/docs/tasks/#3-register) shows. Save the fixed policy in `context.txt`; each example’s state contains only the changing input. Run this Python script from the directory containing both files, with `DECISIO_BASE_URL` set to your endpoint:

 

```
import json
import os
import urllib.request

with open("task.json", encoding="utf-8") as source:
    body = json.load(source)
with open("context.txt", encoding="utf-8") as context:
    body["context"] = context.read()

base_url = os.environ.get("DECISIO_BASE_URL", "http://127.0.0.1:8000").rstrip("/")
request = urllib.request.Request(
    base_url + "/v1/tasks", data=json.dumps(body).encode(),
    headers={"Content-Type": "application/json"},
)
with urllib.request.urlopen(request, timeout=300) as response:
    print(json.dumps(json.load(response), indent=2))
```

 

Shown, not run: it needs a complete labelled task.json and a context.txt policy supplied by the reader; transport tests check both files.

 

- **Add `"context"` to the registration:** a string, or an object or array read as compact JSON. Labelled, dynamic-option and learning registrations take it.
- **Send only the changing part as each example’s state.** The server reads each example with the context, so the task is fitted, certified and timed on exactly what it serves.
- **Keep in the context only what is the same on every request.** What changes belongs in the state.

 

## 3 Ask with it

 

- **Send the state without the context.** A state that still starts with the context is read with it twice, and the response carries `x-decisio-warning`.
- **Name the task when several share a [question](https://opendecisio.com/docs/glossary/#question).** The same question with another context is another task, kept beside the first; `"task": "<id>"` on `/v1/systemone` picks one.
- **One request, one context.** Questions whose tasks have different contexts go in separate requests.

 

## 4 Good to know

 

- **A context over the model’s window is refused with 422 before any model work,** on every engine, and so is one that fits but not beside an example’s state.
- **The context is part of the task’s identity:** a certificate made under one context does not hold under another.
- **Status shows the context’s sha256 and length, never its text;** the export holds the text.
- **[Abstention](https://opendecisio.com/docs/glossary/#abstain) tasks take no context.**
- **Upgrade every replica before registering a task with a context.** An earlier release refuses its record rather than serve the task without it.

 

## What next

 

- [Teach a task](https://opendecisio.com/docs/tasks/): register a task and read what it kept.
- [Add a decision fast path](https://opendecisio.com/docs/tasks/fast-table/): a classifier on the server’s CPU, before the model.
- [The HTTP API](https://opendecisio.com/docs/api/): the task routes, field by field.