TruEra
Official@truera
Enabling people and machines to make better decisions together.
Agent Skills by TruEra
Showing 8 vetted skills indexed across 1 GitHub repositories.
trueratrulens-blocking-guardrails
Configure TruLens feedback functions as runtime guardrails to block unsafe inputs, outputs, and irrelevant context.
trueratrulens-diagnosis
Diagnose low LLM evaluation scores and generate targeted improvement recommendations.
trueratrulens-evaluation-workflow
Orchestrates end-to-end TruLens evaluation workflows for LLM apps.
trueratrulens-dataset-curation
Create and curate ground-truth evaluation datasets for TruLens.
trueratrulens-instrumentation
Instrument LLM apps to capture traces for evaluation and debugging.
trueratrulens-running-evaluations
Orchestrate TruLens evaluations across apps and versions with TruChain, TruGraph, and TruLlama.
trueratrulens-evaluation-setup
Configure TruLens feedback functions and selectors for LLM output evaluation.
trueratrulens-notebook-execution
Execute and display TruLens notebooks using jupyter nbconvert.
Frequently Asked Questions About TruEra
FAQPage SchemaWhat specific tasks does TruEra enable for model developers?▼
TruEra enables developers to instrument applications for trace capture, configure feedback functions for output validation, and curate ground-truth datasets. It facilitates systematic performance benchmarking across different model versions using integrated components like TruChain, TruGraph, and TruLlama to ensure consistent decision-making quality.
Which technical personas benefit most from these evaluation capabilities?▼
Machine learning engineers, data scientists, and model reliability specialists benefit from these capabilities. These professionals use the framework to monitor production output, debug complex chains, and maintain rigorous quality standards for generative systems through structured evaluation and dataset management.
What are the primary prerequisites for implementing these evaluation functions?▼
Implementation requires an existing model application environment and Jupyter-based notebooks for execution. Users must configure feedback functions and selectors to define evaluation criteria, and ensure the application is instrumented to capture necessary traces for the evaluation engine to process.