Import Yera

At the end of this tutorial you'll have been introduced to Yera's single-import design and how to explore your available models via the model atlases.

Import

Yera is designed so its entire Python API lives behind a single import. Just import yera

import yera as yr

We conventionally alias it as yr. This will be used through the rest of the docs.

That's it. yr is the entry point for everything you want to use. If you inspect it with tab completion or dir(yr) you'll see a whole bunch of stuff. We'll work our way through them throughout these tutorials, but I'd like to draw your attention to one of them in particular.

Model Atlases

Yera contains model atlases at the top-level import. For now the only one there is the one containing all your LLMs, but in future Yera will support various other models types such as text-to-speech, speech-to-text, embeddings and more.

An atlas is the means by which you explore and use models in your Yera apps. It contains all the models available to your current profile. Try printing yr.llm

print(yr.llm)

and you should see like this

┌─[llm]

├─ Default: ollama.gemma4.gemma4-31b

│

├── anthropic/

│   └── ...

├── ollama/

│   ├── gemma4/

│   │   └── gemma4-31b

│   └── ...

└── openai/

└── ...

showing the different providers and the models available in them as well as your configured default.

The models and groupings all live as attributes on the atlas. Have an explore to see what you can use.

We'll come to how to use models via atlases at a later tutorial, just note that your configured default will be what the apps you build will run with.

Summary

You now know about the Yera top-level import, its design and the LLM model atlas. In the next tutorial you'll build your first app.