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nannyml: post-deployment data science in python
The main features of nannyml/nannyml are: Model Evaluation and Benchmarking, Observability And Monitoring.
Open-source alternatives to nannyml/nannyml include: comet-ml/opik — Opik is an observability and evaluation platform designed for generative AI applications and agentic workflows. It… helicone/helicone — Helicone is an AI gateway and observability platform designed to intercept, manage, and monitor interactions with… arize-ai/phoenix — Arize Phoenix is an LLM observability platform and evaluation framework designed to capture execution traces and… evidentlyai/evidently — Evidently is an AI observability platform and evaluation framework designed to quantify the performance of machine… facebookresearch/parlai — ParlAI is a conversational AI research framework designed for training, evaluating, and sharing dialogue models using… infrasys-ai/aiinfra.
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Evidently is an AI observability platform and evaluation framework designed to quantify the performance of machine learning models and large language models. It functions as a monitoring tool for detecting data drift and quality degradation in tabular datasets, while providing a specialized analyzer for the faithfulness and correctness of retrieval augmented generation systems. The project distinguishes itself through an evaluation framework that utilizes judge models and custom rubrics to score language model outputs. It includes tools for iterative prompt optimization and the generation of
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
Helicone is an AI gateway and observability platform designed to intercept, manage, and monitor interactions with large language models. By acting as a reverse-proxy, it provides a centralized layer for routing requests across multiple AI providers, allowing developers to maintain consistent application logic while gaining deep visibility into model performance, usage, and costs. The platform distinguishes itself through a robust suite of traffic management and prompt engineering tools. It enables policy-driven control, including automatic failover between providers, rate limiting, and edge-b