0.11.0 Release Notes

This page includes updates from our 0.11.0 Release, which includes new features, stability and performance improvements.

Deepchecks LLM Evaluation 0.11.0 Release

• 💬 LLM Properties Enhancements: Property Bank & Multi-step LLM Properties
• ✅ Email Upon Completion of Data Processing
• 🎨 Updated Designs: Workspace Settings & Properties
• 🤼 Version Comparison Flow
• 🏛️ Classification Use Case Support

What's New and Improved

• LLM Properties Enhancements

  • LLM Properties "Bank" - enables starting from a builtin llm property template, alongside starting from scratch and building one of your own.

    

  • LLM Properties can now receive any interaction step. If you have more than "Input", "Information Retrieval", and "Output", these steps can be logged to the interaction via our SDK, and then used for feeding the LLM Properties. See the "Interaction Steps for Property" phase inside the LLM Properties Definition.

    

• Email upon completion of data processing after upload

  • Email notifications can now be configured in the "Workspace Settings" notifications tab.

    

  • Selected emails will receive a notification after data upload is completed - whether uploaded by csv or by email, per configured application.

• Updated Designs for Workspace Settings and Properties Screens

  • The "Built-in" Properties can now be disabled, such that they won't be viewable 👁️anywhere across the app, to help you stay focused on the properties that matter.

• Version Comparison Flow

  • Versions can now be selected in the Versions screen, enabling a deeper comparison.

    

  • The comparison enables:

    • Comparing multiple properties across versions.

    • Pinpointing identical Interactions (same user_interaction_id) which differ most between the versions: Different property scores, lowest similarity scores, different annotations.

      

• Classification Use Case Support

  • New application type, for classification:

    

  • Automatically identifies and parses the interaction "Output" as a class, and enables using in-system capabilities (properties, RCA, property based auto-annotation, etc.) for evaluating your LLM Classification app.