Changelog

With this new feature, you're able to use the output of a large language model like GPT-4 as the reference for another model like Gemma-7b and Mistal-large (see image).

Instead of manually adding your data sets or uploading them through a CSV file in experiments, you can now import them from the files you stored in Resources. This allows you to store and access your files in a quick and efficient manner.

Save your data sets, variables, and evaluators in the newly added resources tab.

We have added Evaluators to our platform. With a wide range of industry-standard metrics and other relevant evaluators, you can check whether or not the output of your LLM is accurate, reliable, and contextually relevant.

In our latest SDK update, we're thrilled to share a series of enhancements that significantly boost the performance and capabilities of our platform.

You could already select models such as Llama from Meta and Mixtral from Mistral in the model garden. But with this release, it is now possible to connect your own API key for AnyScale. This way you can use your own account and rate limits without having to rely on a shared key. Soon you'll be able to use your own private models and finetuning on AnyScale.

You could already test out different models and configurations using our playground. However, with the introduction of Experiments, you are able to do this on a much larger scale.

We improved our SDKs to support more types of models. Now, it's possible to use completion, chat, and image models through our unified API.

For a better UX on Orquesta, we improve how to handle function calling in the Playground and the Prompt Studio.