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

# Workflow Agent Examples

<Card title="Prioritize Annotation Tasks" icon="notebook" href="https://colab.research.google.com/github/encord-team/encord-agents/blob/main/docs/notebooks/task_agent_set_priority.ipynb">
  Clicking on this card brings you to the Google Colab notebook.
</Card>

## Workflow Automation & Data Management

<CardGroup>
  <Card title="Prioritize Annotation Tasks" icon="route" href="https://colab.research.google.com/github/encord-team/encord-agents/blob/main/docs/notebooks/task_agent_set_priority.ipynb">
    Assign a priority to each task before advancing the task to the annotation stage.
  </Card>

  <Card title="Route Based on Previous Annotator" icon="route" href="https://colab.research.google.com/github/encord-team/encord-agents/blob/main/docs/notebooks/task_agent_route_on_annotator_name.ipynb">
    Route a task according to the annotator it was annotated by.
  </Card>

  <Card title="Transferring Labels to a Twin Project" icon="route" href="https://colab.research.google.com/github/encord-team/encord-agents/blob/main/docs/notebooks/twin_project_label_transfer.ipynb">
    Transfer checklist labels from Project A and convert them into radio labels in Project B.
  </Card>

  <Card title="Route Tasks Based on Object Attribute" icon="route" href="https://colab.research.google.com/github/encord-team/encord-agents/blob/main/docs/notebooks/AgentRouterBasedOnAttributes.ipynb">
    Route tasks according to object attribute.
  </Card>
</CardGroup>

## Pre-Labeling

<CardGroup>
  <Card title="Pre-Label Videos using Dummy Predictions" icon="tags" href="https://colab.research.google.com/github/encord-team/encord-agents/blob/main/docs/notebooks/prelabel_videos_with_bounding_boxes.ipynb">
    Pre-label videos with dummy predictions.
  </Card>

  <Card title="Pre-Label Videos with Mask R-CNN" icon="tags" href="https://colab.research.google.com/github/encord-team/encord-agents/blob/main/docs/notebooks/mask_rcnn_on_videos.ipynb">
    Pre-label videos with predictions using Mask R-CNN.
  </Card>

  <Card title="Pre-Label Videos with Hugging Face" icon="tags" href="https://colab.research.google.com/github/encord-team/encord-agents/blob/main/docs/notebooks/hugging_face_agent_example.ipynb">
    Pre-label videos with predictions using a Hugging Face model.
  </Card>

  <Card title="Pre-Label Videos with YOLO" icon="tags" href="https://colab.research.google.com/github/encord-team/encord-agents/blob/main/docs/notebooks/yolo_example.ipynb">
    Pre-label videos with predictions using an Ultralytics YOLO model.
  </Card>
</CardGroup>

## Audio Transcription & Analysis

<AccordionGroup>
  <Accordion title="Video Tutorial - Using Audio Transcription Agents">
    <div
      style={{
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    >
      <iframe
        allowFullScreen
        frameBorder="0"
        mozallowfullscreen=""
        src="https://www.loom.com/embed/8ff1c0af6c904eee9b8c3871cf8fa664?sid=43d6b5e9-c8af-4d35-ad44-a294f42ad355"
        style={{
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        webkitallowfullscreen=""
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    </div>
  </Accordion>
</AccordionGroup>

<CardGroup>
  <Card title="Audio Transcription" icon="headset" href="https://colab.research.google.com/github/encord-team/encord-agents/blob/main/docs/notebooks/audio_transcription_agent_multi_speaker.ipynb">
    Transcribe and diarize audio files.
  </Card>

  <Card title="Sentiment Analysis" icon="headset" href="https://colab.research.google.com/github/encord-team/encord-agents/blob/main/docs/notebooks/sentiment_analysis.ipynb">
    Analyze "high confidence" transcriptions.
  </Card>

  <Card title="Sentiment Classifications" icon="headset" href="https://colab.research.google.com/github/encord-team/encord-agents/blob/main/docs/notebooks/speech_sentiment_agent_single_speaker.ipynb">
    Classify the sentiment of single-speaker audio files.
  </Card>
</CardGroup>

## LLM & VLM Agent Use Cases

<CardGroup>
  <Card title="Multimodal LLM as a Judge" icon="pen" href="https://colab.research.google.com/github/encord-team/encord-agents/blob/main/docs/notebooks/llm_as_a_judge.ipynb">
    Use a Large Language Model (LLM) to evaluate and select the better product image description from two different LLM-generated descriptions.
  </Card>

  <Card title="Multistage VLM Video Captioning" icon="pen" href="https://colab.research.google.com/github/encord-team/encord-agents/blob/main/docs/notebooks/multistage_video_summarisation.ipynb">
    Uses a VLM to generate frame-specific captions and compile these into a textual summary using an LLM.
  </Card>

  <Card title="Recaption video frames with an LLM" icon="pen" href="https://colab.research.google.com/github/encord-team/encord-agents/blob/main/docs/notebooks/recaption_video.ipynb">
    Use the Encord Agents Task Runner to recaption videos
  </Card>
</CardGroup>
