03.28.2024
New Releases, Enhancements, + Changes
Last updated
New Releases, Enhancements, + Changes
Last updated
Arize now supports LLM assisted evals that have been generated by the Arize Phoenix evals package. Use evals to determine the performance of your LLM application across dimensions such as Hallucination, Toxicity, QA Correctness and more. Evals can also be run on a job and sent to Arize on a regular cadence. See our docs here to get started with Evals in Arize, with more releases coming to Evals soon.
This update allows users to self-serve data deletion through GraphQL. Learn more →
We now support AUC in custom metrics. Learn more →
Users can now send evals and spans together via the log_spans method of the Arize Pandas Client
On-prem users can pass a path to certificate files or disable the TLS verification.
Learn about Python SDK fixes and improvements here.
The latest paper readings, ebooks, self-guided learning modules, and technical posts:
Tutorial: Everything You Need to Set Up a SQL Router Query Engine for Text-To-SQL
LLM Task Evaluations vs Model Evals
Anthropic Claude 3: Performance and Review
Cerebral Valley on "How Arize Is Expanding the Field of AI Observability"
Paper Read: Reinforcement Learning In An Era of LLMs