# Access Jupyter AI Features
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You can access Jupyter AI capabilities through two distinct methods: using the chat UI or using magic commands within notebooks.

## From the chat user interface AI assistant
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The chat interface connects you with Jupyternaut, a conversational agent that uses the language model of your choice. 

After launching a JupyterLab application installed with Jupyter AI, you can access the chat interface by choosing the chat icon (![\[Icon of a rectangular shape with a curved arrow pointing to the upper right corner.\]](http://docs.aws.amazon.com/sagemaker/latest/dg/images/studio/icons/jupyterai/jupyterai-chat-ui.png)) in the left navigation panel. First-time users are prompted to configure their model. See [Configure your model provider in the chat UI](sagemaker-jupyterai-model-configuration.md#sagemaker-jupyterai-model-configuration-chatui) for configuration instructions.

**Using the chat UI, you can:**
+ **Answer questions**: For instance, you can ask Jupyternaut to create a Python function that adds CSV files to an Amazon S3 bucket. Subsequently, you can refine your answer with a follow-up question, such as adding a parameter to the function to choose the path where the files are written. 
+ **Interact with files in JupyterLab**: You can include a portion of your notebook in your prompt by selecting it. Then, you can either replace it with the model's suggested answer or manually copy the answer to your clipboard.
+ **Generate entire notebooks** from prompts: By starting your prompt with `/generate`, you trigger a notebook generation process in the background without interrupting your use of Jupyternaut. A message containing the link to the new file is displayed upon completion of the process.
+ **Learn from and ask questions about local files**: Using the `/learn` command, you can teach an embedding model of your choice about local files and then ask questions about those files using the `/ask` command. Jupyter AI stores the embedded content in a local [FAISS vector database](https://github.com/facebookresearch/faiss), then uses retrieval-augmented generation (RAG) to provide answers based on what it has learned. To erase all previously learned information from your embedding model, use `/learn -d`.

**Note**  
Amazon Q developer doesn't have the capability to generate notebooks from scratch.

For a complete list of features and detailed instructions on their usage, see the [Jupyter AI chat interface](https://jupyter-ai.readthedocs.io/en/latest/users/index.html#the-chat-interface) documentation. To learn about how to configure access to a model in Jupyternaut, see [Configure your model provider in the chat UI](sagemaker-jupyterai-model-configuration.md#sagemaker-jupyterai-model-configuration-chatui).

## From notebook cells
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Using `%%ai` and `%ai` magic commands, you can interact with the language model of your choice from your notebook cells or any IPython command line interface. The `%%ai` command applies your instructions to the entire cell, whereas `%ai` apply them to the specific line.

The following example illustrates an `%%ai` magic command invoking an Anthropic Claude model to output an HTML file containing the image of a white square with black borders.

```
%%ai anthropic:claude-v1.2 -f html
Create a square using SVG with a black border and white fill.
```

To learn about the syntax of each command, use `%ai help`. To list the providers and models supported by the extension, run `%ai list`.

For a complete list of features and detailed instructions on their usage, see the Jupyter AI [magic commands](https://jupyter-ai.readthedocs.io/en/latest/users/index.html#the-ai-and-ai-magic-commands) documentation. In particular, you can customize the output format of your model using the `-f` or `--format` parameter, allow variable interpolation in prompts, including special `In` and `Out` variables, and more.

To learn about how to configure the access to a model, see [Configure your model provider in a notebook](sagemaker-jupyterai-model-configuration.md#sagemaker-jupyterai-model-configuration-magic-commands).