# Summary Coherence

**Objective:** 

Summary Coherence measures the logical flow and structural integrity of the summary. It examines whether ideas are presented in a logically connected manner, ensuring that the summary follows a clear progression of thoughts. This is especially important in multi-sentence summaries, where disjointed or fragmented ideas can disrupt understanding.

**Required Columns in Dataset:**

`LLM Summary`, `Prompt`

**Interpretation:**

* **High values**: Indicate that the summary presents information in a well-organized, logically connected sequence.
* **Low values**: Suggest that the summary is disorganized or has disconnected thoughts, making it harder to follow.

**Execution via UI:**

<figure><img src="/files/Waul0vH7ZL7BvwgPbtTI" alt=""><figcaption></figcaption></figure>

**Execution via SDK:**

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


---

# 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/text-summarization/summary-coherence.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.