Enforce real-time token budgets and spending limits for OpenAI, Anthropic Claude, and Google Gemini API calls in Node.js
[llm-ui](https://llm-ui.com) markdown block.
LLM eval & testing toolkit
Display language model outputs in your React project.
Typescript bindings for langchain
The best library to work with LLMs
Lightweight, zero-dependency LLM API cost & token usage tracker for OpenAI, Anthropic, Gemini, Mistral, Groq, and DeepSeek
micromark extension to support math (`$C_L$`, `\(C_L\)`)
Detox driver for Wix Pilot usage
Hardware accelerated language model chats on browsers
[llm-ui](https://llm-ui.com) code block.
General-purpose agent with transport abstraction, state management, and attachment support
A library for working with LLMs in Grafana plugins
The Memory Layer For Your AI Apps
[llm-ui](https://llm-ui.com) JSON blocks for building custom components.
Package to connect and trace LLM calls.
Superfast runtime validators with only one line
[](https://dl.circleci.com/status-badge/redirect/gh/taneliang/coerce-llm-output/tree/main) [![codecov](https://codecov.io/github/taneliang/coerce-l
JavaScript obfuscator
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
Client library to connect to the LangSmith Observability and Evaluation Platform.
This package provides OpenInference semantic conventions for tracing of LLM Applications.
A universal LLM client - provides adapters for various LLM providers to adhere to a universal interface - the openai sdk - allows you to use providers like anthropic using the same openai interface and transforms the responses in the same way - this allow
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