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

# Session context retention

> Learn how to use the session context retention test to evaluate whether the assistant maintains context across turns

## Definition

The session context retention test evaluates whether the assistant **maintains and
correctly uses context** across the turns of a conversation. An LLM-as-a-judge reads
the full session and scores it against four criteria:

* Remembers facts and preferences established in prior turns
* Builds upon previously established context rather than starting fresh each turn
* Avoids asking for information the user has already provided
* Doesn't contradict information given earlier in the session

## Taxonomy

* **Task types**: LLM.
* **Availability**: <Tooltip tip="Continuously evaluate your models and datasets as you iterate on their versions.">development</Tooltip>
  and <Tooltip tip="Monitor a model in production, measure its health, check for drifts and set up alerts.">monitoring</Tooltip>.
* **Evaluation level**: session.
* **Polarity**: higher score = better. `0` = no context retention, `1` = perfect
  context retention.

## Why it matters

* Context-retention failures are a primary driver of user frustration in multi-turn
  assistants — especially re-asking for information already supplied.

## Required columns

* **Input**: The user's message in each turn.
* **Output**: The assistant's response in each turn.
* **Session ID**: Groups turns belonging to the same conversation.
* **Timestamp**: Used to reconstruct turn order within a session.

<Note>
  This metric relies on an LLM evaluator. On Openlayer you can configure the
  underlying LLM used to compute it. Check out the
  [OpenAI](/integrations/openai#openai-llm-evaluator) or
  [Anthropic](/integrations/anthropic#anthropic-llm-evaluator) integration
  guides for details.
</Note>

## Test configuration examples

<CodeGroup>
  ```json Monitoring theme={null}
  [
    {
      "name": "Session context retention above 0.7",
      "description": "Ensure the assistant maintains context across session turns",
      "type": "performance",
      "subtype": "sessionContextRetention",
      "thresholds": [
        {
          "insightName": "sessionContextRetention",
          "measurement": "meanScore",
          "operator": ">=",
          "value": 0.7
        }
      ],
      "subpopulationFilters": null,
      "mode": "monitoring",
      "usesProductionData": true,
      "evaluationWindow": 3600,
      "delayWindow": 0
    }
  ]
  ```
</CodeGroup>

## Related

* [Session coherence](/tests/catalog/session-coherence) — broader consistency signal.