> For the complete documentation index, see [llms.txt](https://docs.raga.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.raga.ai/ragaai-catalyst/ragaai-metric-library/rag-metrics/context-recall.md).

# Context Recall RAG Metric

**Objective**: This metric measures the ability to retrieve documents containing ground truth facts. Simply, it returns the proportion of context documents which had impact on the ground truth response.

**Required Parameters**: `Prompt`, `Expected Response`, `Context`

**Interpretation**: Higher score signifies major proportion of contexts supplied to the LLM were helpful in answering the prompt question

<figure><img src="/files/FY2vrvrtvOJX562j4Nly" alt=""><figcaption></figcaption></figure>

**Code Execution:**

```python
metrics=[
    {"name": "Context Recall", "config": {"model": "gpt-4o-mini", "provider": "openai"}, "column_name": "your-column-identifier", "schema_mapping": schema_mapping}
]
```

The "schema\_mapping" variable needs to be defined first and is a pre-requisite for evaluation runs. Learn how to set this variable [here](/ragaai-catalyst/concepts/running-ragaai-evals/executing-evaluations.md).

**Example**:

* Prompt: What is the chemical formula for water and what are different elements in it?
* Expected Response: The chemical formula for water is H2O and it is composed of two elements: hydrogen and oxygen.
* Context: \[‘Water is essential for all known forms of life and is a major component of the Earth's hydrosphere.’,‘Water chemical formula is H2O.’, ‘The chemical formula for carbon dioxide is CO2, which is a greenhouse gas.’]
* *Metric Output*: {‘score’:0.5, ‘reason’:‘’context does not contain any information about the elements of water’}


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# Agent Instructions
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## Querying This Documentation
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Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.raga.ai/ragaai-catalyst/ragaai-metric-library/rag-metrics/context-recall.md?ask=<question>&goal=<endgoal>
```

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