# 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: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

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

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.