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

# LLM Integration Guide

> Learn how to enhance your transcriptions using Salad Transcription API with Large Language Model (LLM) features. This guide covers advanced parameters like `summarize`, `llm_translation`, `custom_prompt`, `classification_labels`, `overall_classification`, and `overall_sentiment_analysis` to extract deeper insights from your audio content.


*Last Updated: November 18, 2024*

## Introduction

Salad Transcription API now offers integration with Large Language Models (LLMs) to provide advanced features such as
summarization, translation, custom prompts, and sentiment analysis. By leveraging LLMs, you can gain richer insights and
perform complex language processing tasks on your transcriptions. *(Only available in Salad Transcription API)*

This guide covers the key LLM-related parameters you can use to enhance your transcription outputs:

* **Summarization**:
  * `summarize`
* **LLM-Based Translation**:
  * `llm_translation`
  * `srt_translation`
* **Custom Prompts**:
  * `custom_prompt`
* **Overall Classification and Sentiment Analysis**:
  * `overall_classification`
  * `overall_sentiment_analysis`

By properly utilizing these parameters, you can unlock the full potential of LLMs in your transcription workflows.

## LLM Integration Parameters

### 1. `summarize`

#### Description

The `summarize` parameter enables you to generate a concise summary of your transcription using an LLM. You can specify
the maximum word count for the summary.

* **Default**: `0` (No summarization)
* **Type**: `integer`

#### Usage

Set `"summarize": word_limit` in your request to receive a summary with the specified word limit.

**Example:**

```json theme={null}
"input": {
  "url": "https://example.com/path/to/file.mp3",
  "summarize": 100
}
```

**Output**

The summary will be included in the `summary` field of the output.

```json theme={null}
"summary": "This meeting discussed project timelines, budget allocations, and assigned tasks to team members for the next quarter."
```

### 2. `llm_translation`

#### Description

Use the `"llm_translation"` parameter to translate your transcription into one or more specified languages using an LLM.

* **Type**: `string` (Comma-separated list of languages)

**Usage**

Set `"llm_translation": "Language1, Language2"` to translate the transcription into the specified languages.

**Example:**

```json theme={null}
"input": {
  "url": "https://example.com/path/to/file.mp3",
  "llm_translation": "german, italian, french"
}
```

**Output**

Translations will be included in the `llm_translation` object.

```json theme={null}
"llm_translation": {
  "French": "Votre transcription en français.",
  "German": "Ihre Transkription auf Deutsch."
}
```

Check [translation page](/transcription/how-to-guides/features/translation) for more details.

### 3. `srt_translation`

#### Description

Translate the generated SRT subtitles into specified languages using an LLM.

* **Type**: `string` (Comma-separated list of languages)

**Usage**

Set `"srt_translation": "Language1, Language2"` to translate the transcription into the specified languages.

**Example:**

```json theme={null}
"input": {
  "url": "https://example.com/path/to/file.mp3",
  "srt_translation": "spanish"
}
```

**Output**

Translations will be included in the `srt_translation` object.

```json theme={null}
"llm_translation": {
  "Spanish": "1\n00:00:01,000 --> 00:00:04,000\nSu transcripción en español.\n\n..."
}
```

Check [translation page](/transcription/how-to-guides/features/translation) for more details.

### 4. `custom_prompt`

#### Description

Provide a `custom prompt` to guide the LLM in performing specific tasks, such as generating a tailored summary,
extracting key information, improve result, or answering questions based on the transcription.

* **Type**: `string`

**Usage**

Set `"custom_prompt": "Your custom instruction here"` to direct the LLM. As a result the LLM model will receive a prompt
in the following format: `custom instruction:transcription`

**Example:**

```json theme={null}
"input": {
  "url": "https://example.com/path/to/file.mp3",
  "custom_prompt": "List all action items discussed in the meeting."
}
```

**Output**

The LLM will generate a response based on the custom prompt. The result will be included in the `llm_result` field.

json Copy code

```json theme={null}
"llm_result": "- Prepare the project proposal by Friday.\n- Schedule a follow-up meeting next Monday.\n- Allocate resources for the development team."
```

### 5. `classification_labels ` and `overall_classification`

#### Description

Use the `classification_labels` parameter in conjunction with `overall_classification` to classify the entire
transcription into specified categories using an LLM.

* **`classification_labels`**:
  * **Type**: `string` (Comma-separated list of labels)
* **`overall_classification`**:
  * **Default**: `false`
  * **Type**: `boolean`

#### Usage

Set `"overall_classification": true` and provide your labels in `"classification_labels": "Label1, Label2"` to classify
the entire transcription.

**Example:**

```json theme={null}
"input": {
  "url": "https://example.com/path/to/file.mp3",
  "overall_classification": true,
  "classification_labels": "Interview, Meeting, Presentation"
}
```

**Output**

The classification result will be included in the `overall_classification` field.

```json theme={null}
"overall_classification": "Meeting"
```

**Notes**

* **`Custom Labels:`**: You can define any categories relevant to your use case.
* **`Multiple Labels:`**: The LLM will select the most appropriate label from the list provided

### 6. `overall_sentiment_analysis`

#### Description

Analyze the overall sentiment of the transcription using an LLM.

* **Default**: `false`
* **Type**: `boolean`

#### Usage

Set `"overall_sentiment_analysis"`: true to perform sentiment analysis.

**Example:**

```json theme={null}
"input": {
  "url": "https://example.com/path/to/file.mp3",
  "overall_sentiment_analysis": true
}
```

**Output**

The result will be included in the `overall_sentiment` field.

json Copy code

```json theme={null}
"overall_sentiment": "Positive"
```

### 7. `custom_vocabulary`

#### Description

Improve transcription accuracy by providing a custom vocabulary of terms that are specific to your domain, such as
industry jargon, acronyms, or proper nouns.

* **Type**: `string` (Comma-separated list of terms)

#### Usage

Set `"custom_vocabulary": "Term1, Term2"` to include custom terms in the transcription process.

**Example:**

```json theme={null}
"input": {
  "url": "https://example.com/path/to/file.mp3",
  "custom_vocabulary": "SaladCloud, AI Transcription, LLM Integration"
}
```

**Notes**

* The custom vocabulary helps the LLM update domain-specific terms.
* Result will have both the original transcrioption and updated under `llm_custom_vocabulary`.