# Quickstart notebook - Summarization

In this notebook, we will look at how you can use Opik to track your LLM calls, chains and agents. We will introduce the concept of tracing and how to automate the evaluation of your LLM workflows.

We will be using a technique called Chain of Density Summarization to summarize Arxiv papers. You can learn more about this technique in the [From Sparse to Dense: GPT-4 Summarization with Chain of Density Prompting](https://arxiv.org/abs/2309.04269) paper.

## Getting started

We will first install the required dependencies and configure both Opik and OpenAI.

```python
%pip install -U opik openai requests PyPDF2 --quiet
```

[Comet](https://www.comet.com/site?from=llm\&utm_source=opik\&utm_medium=colab\&utm_content=langchain\&utm_campaign=opik) provides a hosted version of the Opik platform, [simply create an account](https://www.comet.com/signup?from=llm\&utm_source=opik\&utm_medium=colab\&utm_content=langchain\&utm_campaign=opik) and grab your API Key.

> You can also run the Opik platform locally, see the [installation guide](https://www.comet.com/docs/opik/self-host/overview/?from=llm\&utm_source=opik\&utm_medium=colab\&utm_content=langchain\&utm_campaign=opik) for more information.

```python
import opik