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

# chapters

> Auto-detect topic chapters in audio with timestamps.

Detects where the topic changes in your audio and splits it into chapters with timestamps.

***

## Example

**Request:**

```json theme={null}
{
  "audio_path": "/Users/you/Downloads/lecture.webm"
}
```

**Response:**

```json theme={null}
{
  "chapters": [
    {
      "chapter_number": 1,
      "start": 0.0,
      "end": 245.3,
      "start_timestamp": "0:00",
      "end_timestamp": "4:05",
      "text": "Welcome everyone. Today we'll cover three main topics...",
      "segment_count": 12
    },
    {
      "chapter_number": 2,
      "start": 245.3,
      "end": 892.1,
      "start_timestamp": "4:05",
      "end_timestamp": "14:52",
      "text": "Let's start with neural network architectures...",
      "segment_count": 35
    },
    {
      "chapter_number": 3,
      "start": 892.1,
      "end": 1523.7,
      "start_timestamp": "14:52",
      "end_timestamp": "25:23",
      "text": "Now moving on to training techniques...",
      "segment_count": 28
    }
  ],
  "total_chapters": 3,
  "duration": 1523.7,
  "model_used": "tiny"
}
```

***

## Parameters

| Parameter     | Required | Default | Description                                                                         |
| ------------- | -------- | ------- | ----------------------------------------------------------------------------------- |
| `audio_path`  | Yes      | —       | Path to the audio/video file                                                        |
| `model_size`  | No       | `tiny`  | Whisper model size for transcription                                                |
| `sensitivity` | No       | `0.4`   | Chapter detection sensitivity (0.0 = many small chapters, 1.0 = few large chapters) |

***

## Notes

<Tip>Chapters are detected by measuring how much the topic shifts between consecutive segments. A large similarity drop = new chapter.</Tip>

<Tip>Adjust `sensitivity` to control granularity. Lower values produce more chapters, higher values produce fewer.</Tip>

<Tip>Embeddings are shared with `deep_search`. If one has already run on a file, the other reuses the stored embeddings.</Tip>

<Tip>Works great on long-form content like lectures, podcasts, and meetings. Short clips under 5 minutes rarely produce meaningful chapter splits.</Tip>