> 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/text-summarization/summary-consistency.md).

# Summary Consistency

**Objective:** 

Summary Consistency evaluates the factual alignment between the generated summary and the source content. It checks if the summary maintains the same facts, figures, and core messages as the input without introducing any hallucinations or errors. This metric is crucial for ensuring that no factual distortions occur when compressing the information.

**Required Columns in Dataset:**

`LLM Summary`, `Original Document`

**Interpretation:**

* **High values**: Indicate that the summary is factually accurate and reflects the original information without alterations.
* **Low values**: Suggest factual inconsistencies, errors, or hallucinations introduced in the summary.

**Execution via UI:**

<figure><img src="/files/9oReX3M5bseq96mDiRFc" alt=""><figcaption></figcaption></figure>

**Execution via SDK:**

```python
metrics=[
    {"name": "Summary Consistency", "config": {"model": "gpt-4o-mini", "provider": "openai"}, "column_name": "your-text", "schema_mapping": schema_mapping}
]
```


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## 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/text-summarization/summary-consistency.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.