Easy test setup without side effects
Provides "ui" for testing frameworks such as mocha/jasmine which allows to define lazy variables and subjects
Jest plugins to emulate RSpec syntax and structure.
Enforce real-time token budgets and spending limits for OpenAI, Anthropic Claude, and Google Gemini API calls in Node.js
Display language model outputs in your React project.
Typescript bindings for langchain
Hardware accelerated language model chats on browsers
[llm-ui](https://llm-ui.com) markdown block.
LLM eval & testing toolkit
[llm-ui](https://llm-ui.com) code block.
[llm-ui](https://llm-ui.com) JSON blocks for building custom components.
Adds context as an alternative to describe to jest.
General-purpose agent with transport abstraction, state management, and attachment support
Adds a Given-When-Then DSL to jasmine as an alternative style for specs
micromark extension to support math (`$C_L$`, `\(C_L\)`)
Detox driver for Wix Pilot usage
A library for working with LLMs in Grafana plugins
Much like tests in traditional software, evals are an important part of bringing LLM applications to production. The goal of this package is to help provide a starting point for you to write evals for your LLM applications, from which you can write more c
Super simple DI for JavaScript, targetted mainly at spec test setup
Distributed test runner using Redis as a work queue. Push file paths to a Redis list, then multiple CI runners atomically steal batches and execute them via a configurable command.
<p align="center"> <img height="100" width="100" alt="LlamaIndex logo" src="https://ts.llamaindex.ai/square.svg" /> </p> <h1 align="center">LlamaIndex.TS</h1> <h3 align="center"> Data framework for your LLM application. </h3>
Package to connect and trace LLM calls.
Opik TypeScript and JavaScript SDK
The best library to work with LLMs
rspec-llm adds first-class RSpec support for testing Large Language Model interactions. Ships LLM-as-judge matchers, JSON Schema validation, semantic similarity matchers, a programmable fake adapter, and a thin DSL for batch evaluations. Works with the ruby_llm and langchainrb gems out of the box.
Define qualitative evaluation criteria and let an LLM judge if responses pass. Perfect for testing AI agents, comparing models, and evaluating subjective qualities.
Chiridion generates documentation optimized for AI agents and LLMs working with Ruby codebases. It extracts documentation from YARD comments, merges RBS type signatures, and produces structured markdown suitable for context injection. Features: - YARD-based documentation extraction - RBS type signature integration (RBS is authoritative) - RSpec example extraction - Obsidian-compatible wikilinks for cross-references - Drift detection for CI/CD pipelines - toys/dx CLI task definitions