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Custom Metric Skill: Copilot now writes custom metrics! Users can generate their desired metric by having copilot translate natural language descriptions or existing code (e.g., SQL, Python) into AQL.
Embedding Summarization Skill: Copilot now works for embeddings! Users can select embedding data point and Copilot will analyze for patterns and insights.
This widget allows users to integrate experiment data directly into their dashboards for ongoing visibility and analysis. Users can now:
Select dataset of interest
Choose specific evaluations they want to visualize over time
Complete with direct connectivity to experiment details, making it easy to access the individual experiment results
The latest video tutorials, paper readings, ebooks, self-guided learning modules, and technical posts:
Local Explainability is now live, providing both a table view and waterfall style plot for detailed, per-feature SHAP values on individual predictions.
Now users can follow the full from OpenAI and iterate on different functions in different messages from within the Prompt Playground.
Context Attribute Propagation - Arize now has a set of utilities (eg: using_session
) that allow users to set properties on context. All of these properties will be picked up by all of our auto instrumentations and added to spans.
Typescript Trace Configuration - Typescript auto instrumentations now accept a trace configuration which allows for data masking and configuration of attribute values on spans.
Vercel AI SDK - User can now ingest traces created by the Vercel AI SDK into Arize.
LangChain Auto Instrumentation: Arize's LangChain auto instrumentation now supports langchain.js version 0.3 and is backwards compatible with all previous versions.
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New Releases, Enhancements, + Changes