Zeno Build provides a collection of self-contained examples for evaluating generative AI models, targeting developers building LLM-based applications. It aims to simplify the process of setting up common evaluation frameworks, allowing users to quickly adapt existing examples to their specific needs and contribute back new functionalities or examples.

How It Works

This repository showcases various evaluation setups using the Zeno library, which is designed to be architecture-agnostic. It supports integration with different LLM providers and frameworks like OpenAI, LangChain, and Hugging Face, enabling users to evaluate models regardless of their underlying architecture.

Quick Start & Requirements

• Installation: pip install zeno-build
• Prerequisites: Python 3.7+
• Links: Contributing Doc, GitHub Issues, Discord

Highlighted Details

• Architecture-agnostic evaluation for LLM applications.
• Self-contained, easily modifiable examples.
• Encourages community contributions for new examples and features.

Maintenance & Community

• Active community engagement via GitHub Issues and Discord.
• Welcomes pull requests for new examples and core library functionality.

Licensing & Compatibility

• License: Not specified in the README.
• Compatibility: Designed to be compatible with various LLM frameworks (OpenAI, LangChain, Hugging Face).

Limitations & Caveats

The README does not specify the license type, which may impact commercial use or closed-source linking.