> ## Documentation Index
> Fetch the complete documentation index at: https://assembly-preview.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Summarize Your Audio Data

> Learn how to summarize your audio using LeMUR

In this guide, you'll learn how to use LeMUR to summarize your audio data with key takeaways.

<Tip>
  If you want a Quickstart, see [Apply LLMs to audio files](/docs/getting-started/apply-llms-to-audio-files).
</Tip>

<Info>
  Before you start

  To use LeMUR, you need an [AssemblyAI account](https://www.assemblyai.com/dashboard/signup) with a credit card set up.
</Info>

## Basic summary example

If you want to send a custom prompt to the LLM, you can use the [LeMUR Task](https://assemblyai.com/docs/api-reference/lemur/task) and apply the model to your transcribed audio files.

To summarize the content in your audio data, define a summarization prompt and call `transcript.lemur.task()`. The underlying `transcript` is automatically used as additional context for the model.

<CodeGroup>
  ```python Python theme={"system"}
  import assemblyai as aai

  aai.settings.api_key = "YOUR_API_KEY"

  # Step 1: Transcribe an audio file.
  # audio_file = "./local_file.mp3"
  audio_file = "https://assembly.ai/sports_injuries.mp3"

  transcriber = aai.Transcriber()
  transcript = transcriber.transcribe(audio_file)

  # Step 2: Define a summarization prompt.
  prompt = "Provide a brief summary of the transcript."

  # Step 3: Apply LeMUR.
  result = transcript.lemur.task(
      prompt, final_model=aai.LemurModel.claude3_5_sonnet
  )

  print(result.response)
  ```

  ```typescript Typescript theme={"system"}
  import { AssemblyAI } from 'assemblyai'

  const client = new AssemblyAI({
    apiKey: 'YOUR_API_KEY'
  })

  const run = async () => {
    // Step 1: Transcribe an audio file.
    //const audioFile = './local_file.mp3'
    const audioFile =
      'https://assembly.ai/sports_injuries.mp3'
    const transcript = await client.transcripts.transcribe({ audio: audioFile })

    // Step 2: Define a summarization prompt.
    const prompt = 'Provide a brief summary of the transcript.'

    // Step 3: Apply LeMUR.
    const { response } = await client.lemur.task({
      transcript_ids: [transcript.id],
      prompt,
      final_model: 'anthropic/claude-3-5-sonnet'
    })

    console.log(response)
  }

  run()
  ```

  ```go Go theme={"system"}
  package main

  import (
      "context"
      "fmt"

      aai "github.com/AssemblyAI/assemblyai-go-sdk"
  )

  func main() {
      ctx := context.Background()

      client := aai.NewClient("YOUR_API_KEY")

      // Step 1: Transcribe an audio file. For local files see our Getting Started guides.
      audioURL := "https://assembly.ai/sports_injuries.mp3"
      transcript, _ := client.Transcripts.TranscribeFromURL(ctx, audioURL, nil)

      // Step 2: Define a summarization prompt.
      prompt := "Provide a brief summary of the transcript."

      // Step 3: Apply LeMUR.
      var params aai.LeMURTaskParams
      params.Prompt = aai.String(prompt)
      params.TranscriptIDs = []string{aai.ToString(transcript.ID)}
      params.FinalModel = "anthropic/claude-3-5-sonnet"

      result, _ := client.LeMUR.Task(ctx, params)

      fmt.Println(*result.Response)
  }
  ```

  ```java Java theme={"system"}
  import com.assemblyai.api.AssemblyAI;
  import com.assemblyai.api.resources.transcripts.types.*;
  import com.assemblyai.api.resources.lemur.requests.*;
  import java.util.List;

  public final class App {
      public static void main(String[] args) {

          AssemblyAI client = AssemblyAI.builder()
                  .apiKey("YOUR_API_KEY")
                  .build();

          // Step 1: Transcribe an audio file. For local files see our Getting Started guides.
          String audioUrl = "https://assembly.ai/sports_injuries.mp3";
          Transcript transcript = client.transcripts().transcribe(audioUrl);

          // Step 2: Define a summarization prompt.
          String prompt = "Provide a brief summary of the transcript.";

          // Step 3: Apply LeMUR.
          var params = LemurTaskParams.builder()
                  .prompt(prompt)
                  .transcriptIds(List.of(transcript.getId()))
                  .finalModel(LemurModel.ANTHROPIC_CLAUDE3_5_SONNET)
                  .build();

          var response = client.lemur().task(params);

          System.out.println(response.getResponse());
      }
  }
  ```

  ```csharp C# theme={"system"}
  using AssemblyAI;
  using AssemblyAI.Lemur;
  using AssemblyAI.Transcripts;

  var client = new AssemblyAIClient("YOUR_API_KEY");

  // Step 1: Transcribe an audio file. For local files see our Getting Started guides.
  var transcript = await client.Transcripts.TranscribeAsync(new TranscriptParams
  {
      AudioUrl = "https://assembly.ai/sports_injuries.mp3"
  });

  // Step 2: Define a summarization prompt.
  const string prompt = "Provide a brief summary of the transcript.";

  // Step 3: Apply LeMUR.
  var lemurTaskParams = new LemurTaskParams
  {
      Prompt = prompt,
      TranscriptIds = [transcript.Id],
      FinalModel = LemurModel.AnthropicClaude3_5_Sonnet
  };

  var response = await client.Lemur.TaskAsync(lemurTaskParams);

  Console.WriteLine(response.Response);
  ```

  ```ruby Ruby theme={"system"}
  require 'assemblyai'

  client = AssemblyAI::Client.new(api_key: 'YOUR_API_KEY')

  # Step 1: Transcribe an audio file. For local files see our Getting Started guides.
  audio_url = 'https://assembly.ai/sports_injuries.mp3'
  transcript = client.transcripts.transcribe(audio_url: audio_url)

  # Step 2: Define a summarization prompt.
  prompt = 'Provide a brief summary of the transcript.'

  # Step 3: Apply LeMUR.
  response = client.lemur.task(
    prompt: prompt,
    transcript_ids: [transcript.id],
    final_model: AssemblyAI::Lemur::LemurModel::ANTHROPIC_CLAUDE3_5_SONNET
  )
  ```
</CodeGroup>

#### Example output

```text theme={"system"}
The transcript describes several common sports injuries - runner's knee,
sprained ankle, meniscus tear, rotator cuff tear, and ACL tear. It provides
definitions, causes, and symptoms for each injury. The transcript seems to be
narrating sports footage and describing injuries as they occur to the athletes.
Overall, it provides an overview of these common sports injuries that can result
from overuse or sudden trauma during athletic activities
```

## Summary with specialized endpoint

The [LeMUR Summary function](/docs/api-reference/lemur/summary) requires no prompt engineering and facilitates more deterministic and structured outputs. You can use it with `transcript.lemur.summarize()`.

You can add additional context to provide information that is not explicitly referenced in the audio data, as well as specify an answer format. For this, use the optional parameters `context` and `answer_format`.

<CodeGroup>
  ```python Python theme={"system"}
  import assemblyai as aai

  aai.settings.api_key = "YOUR_API_KEY"

  audio_url = "https://assembly.ai/meeting.mp4"
  transcript = aai.Transcriber().transcribe(audio_url)

  result = transcript.lemur.summarize(
      final_model=aai.LemurModel.claude3_5_sonnet,
      context="A GitLab meeting to discuss logistics",
      answer_format="TLDR"
  )

  print(result.response)
  ```

  ```typescript Typescript theme={"system"}
  import { AssemblyAI } from 'assemblyai'

  const client = new AssemblyAI({
    apiKey: 'YOUR_API_KEY'
  })

  const audioUrl = 'https://assembly.ai/meeting.mp4'

  const run = async () => {
    const transcript = await client.transcripts.transcribe({ audio: audioUrl })

    const { response } = await client.lemur.summary({
      transcript_ids: [transcript.id],
      final_model: 'anthropic/claude-3-5-sonnet',
      context: 'A GitLab meeting to discuss logistics',
      answer_format: 'TLDR'
    })

    console.log(response)
  }

  run()
  ```

  ```java Java theme={"system"}
  import com.assemblyai.api.AssemblyAI;
  import com.assemblyai.api.resources.lemur.requests.*;
  import com.assemblyai.api.resources.lemur.types.*;
  import com.assemblyai.api.resources.transcripts.types.*;
  import java.util.List;

  public final class App {
      public static void main(String[] args) {

          AssemblyAI client = AssemblyAI.builder()
                  .apiKey("YOUR_API_KEY")
                  .build();

          String audioUrl = "https://assembly.ai/meeting.mp4";

          Transcript transcript = client.transcripts().transcribe(audioUrl);

          var response = client.lemur().summary(LemurSummaryParams.builder()
                  .transcriptIds(List.of(transcript.getId()))
                  .finalModel(LemurModel.ANTHROPIC_CLAUDE3_5_SONNET)
                  .context(LemurBaseParamsContext.of("A GitLab meeting to discuss logistic"))
                  .answerFormat("TLDR")
                  .build());

          System.out.println(response.getResponse());
      }
  }
  ```

  ```csharp C# theme={"system"}
  using AssemblyAI;
  using AssemblyAI.Lemur;
  using AssemblyAI.Transcripts;

  var client = new AssemblyAIClient("YOUR_API_KEY");

  var transcript = await client.Transcripts.TranscribeAsync(new TranscriptParams
  {
      AudioUrl = "https://assembly.ai/meeting.mp4"
  });

  var response = await client.Lemur.SummaryAsync(new LemurSummaryParams
  {
      TranscriptIds = [transcript.Id],
      FinalModel = LemurModel.AnthropicClaude3_5_Sonnet,
      Context = "A GitLab meeting to discuss logistic",
      AnswerFormat = "TLDR"
  });

  Console.WriteLine(response.Response);
  ```

  ```ruby Ruby theme={"system"}
  require 'assemblyai'

  client = AssemblyAI::Client.new(api_key: 'YOUR_API_KEY')

  audio_url = 'https://assembly.ai/meeting.mp4'

  transcript = client.transcripts.transcribe(audio_url: audio_url)

  response = client.lemur.summary(
    transcript_ids: [transcript.id],
    final_model: AssemblyAI::Lemur::LemurModel::ANTHROPIC_CLAUDE3_5_SONNET,
    context: 'A GitLab meeting to discuss logistic',
    answer_format: 'TLDR'
  )

  puts response.response
  ```
</CodeGroup>

## Custom summary example (Advanced)

In this example, we'll run a custom LeMUR task with an advanced prompt to create custom summaries:

[Cookbook: Custom summary with LeMUR Task](https://github.com/AssemblyAI/cookbook/blob/master/lemur/task-endpoint-custom-summary.ipynb)

## More summarization prompt examples

Try any of these prompts to get started:

| Use case                 | Example prompt                                                                  |
| ------------------------ | ------------------------------------------------------------------------------- |
| Summaries                | *"Summarize key decisions and important points from the phone call transcript"* |
| Summarize audio segments | *"Summarize the key events of each chapter"*                                    |

For more use cases and prompt examples, see [LeMUR examples](/docs/lemur/examples).

## API reference

* [LeMUR Task endpoint](https://assemblyai.com/docs/api-reference/lemur/task)
* [LeMUR Summary endpoint](/docs/api-reference/lemur/summary)

## Improve the results

To improve the results, see the following resources:

* Optimize your prompt with the [prompt engineering guide](/docs/lemur/improving-your-prompt).
* To alter the outcome, see [Change model and parameters](/docs/lemur/customize-parameters).