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Utilities for inspecting retrieval-augmented generation pipelines, focusing on document relevance and retrieval quality.
Distinct from Retrieval-Augmented Generation: Focuses on debugging the retrieval process specifically, not the general RAG implementation.
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Arize Phoenix is an LLM observability platform and evaluation framework designed to capture execution traces and monitor large language model applications. It serves as a prompt management system for versioning and testing templates, and as a self-hosted AI operations infrastructure for managing telemetry and experiments. The platform differentiates itself through a specialized embedding visualization tool used to detect data drift and optimize vector search. It provides a comprehensive evaluation suite that utilizes judge-based evaluators and ground-truth datasets to score model outputs, and
Provides tools to upload knowledge base corpora and inferences to troubleshoot bugs in retrieval-augmented generation.