Saving Layer Configs as JSON or YAML config files by representing the LayerConfig object as a dict and then turning into JSON/YAML wasn't working.

See issue here: https://github.com/aurelio-labs/semantic-router/issues/144

The issue was that, by attempting this, we were attempting to serialize all objects included in the Layer, including Routes, and the LLMs that those Routes use.

In the case of the above issue, the LLM was a Cohere one, which included a Client as one of its attributes, and this Client is not serializable.

So, instead of attempting to represent the entire LLM object a dict, to then be converted into JSON/YAML, we only keep key information about the LLM:

'module': self.llm.__module__,
'class': self.llm.__class__.__name__,
'model': self.llm.name

This is what's saved in route.py, and then sent to layer.py to be serialized (in LayerConfig.to_file()).

Then, when it comes time to load from the file via LayerConfig.from_file, the LLM is re-initialized dynamically.

Mostly just trying to make MyPy happy!

Rather than is_index_populated.

installed poetry and ran make.  added mistralai to the pyproject.toml (first time using poetry, nice tool)

the __call__ method of the Zure class to make it more informative

new encoder and a new LLMS. The encoder is a
simple wrapper around the MistralAI API, and the
LLMS is a simple wrapper around the encoder.
The encoder is tested with a simple unit test,
and the LLMS is tested with a simple unit test.

It's defined in the BaseIndex which LocalIndex inherits anyway

Also fixed bug in layer.py where we weren't:
a) Setting the index_name to a default value.
b) Weren't using index_name.

Making pydantic leave me alone and giving the correct index name.