> ## Documentation Index
> Fetch the complete documentation index at: https://docs.composo.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Context & Knowledge Store

> Ground evaluations in your own documents and example evaluations

Our latest Align model, `align-20260109`, can ground its judgments in **context you provide** — your own
reference material and your own example evaluations. Instead of relying only on the criteria and the trace
being scored, the model draws on what you've uploaded, so its scores reflect your domain knowledge and the
way *you* would grade.

You manage this context on the **[Context page](https://platform.composo.ai/context)** in the platform,
where you can upload two things: **Documents** and **Annotations**.

<Warning>
  Context is only used when you evaluate with **`align-20260109`**. The API defaults to `align-20251111`,
  so you must explicitly select `align-20260109` (see [Using your context](#using-your-context) below) for
  uploaded Documents and Annotations to take effect. `align-20260109` is currently in Beta.
</Warning>

## Documents (knowledge store)

Upload reference material that the model should know about — product documentation, policies, style guides,
support macros, domain glossaries, and so on. When you run an evaluation, the model automatically pulls the
most relevant parts of your documents and uses them to ground its judgment.

This is ideal when correct scoring depends on facts the model can't be expected to know — for example
checking an answer against your own product behaviour, or judging whether a response follows your internal
policy.

* **Supported file types:** PDF, Word, PowerPoint, plain text, and Markdown.
* **Processing:** documents are processed shortly after upload; you'll see each one move to **processed** on
  the Context page when it's ready to use.
* **Duplicates:** uploading a file you've already added is automatically skipped.

## Annotations

Upload **example evaluations** — your own labeled judgments showing how a particular response should be
scored and why. The model uses these as guidance to better match your scoring standards on similar cases.

Annotations are useful when your grading involves nuanced judgment calls that are easier to *show* with
examples than to fully spell out in a criteria sentence.

Annotations take around **24 hours** to be ready after upload. You'll be notified once they're available,
and you can track their status on the Context page.

## Using your context

Once your Documents and Annotations are uploaded, evaluate with `align-20260109` to put them to work. Select
the model when you create the client (or set `model_core` directly in an API request):

<CodeGroup>
  ```python Python wrap theme={null}
  from composo import Composo

  # Select align-20260109 so your uploaded context is used
  composo_client = Composo(api_key="YOUR_API_KEY", model_core="align-20260109")

  result = composo_client.evaluate(
      messages=[
          {"role": "user", "content": "Does the Pro plan include SSO?"},
          {"role": "assistant", "content": "Yes — SSO is included on the Pro plan and above."}
      ],
      criteria="Reward responses that correctly describe what's included in each plan"
  )

  print(f"Score: {result.score}")
  print(f"Analysis: {result.explanation}")
  ```

  ```bash cURL theme={null}
  curl -X POST "https://platform.composo.ai/api/v1/evals/reward" \
    -H "API-Key: YOUR_API_KEY" \
    -H "Content-Type: application/json" \
    -d '{
      "model_core": "align-20260109",
      "messages": [
        {"role": "user", "content": "Does the Pro plan include SSO?"},
        {"role": "assistant", "content": "Yes — SSO is included on the Pro plan and above."}
      ],
      "evaluation_criteria": "Reward responses that correctly describe what'\''s included in each plan"
    }'
  ```
</CodeGroup>

With `align-20260109` selected, the model automatically grounds this evaluation in the relevant parts of
your uploaded context — no extra parameters needed.

## Related

* [Models](/documentation/getting-started/models) — full list of Align model versions
* [Ground Truth Evaluation](/documentation/guides/ground-truths) — insert a known correct answer directly
  into a single criteria