Results for llm-package

This is a sample packge for LLM

LLM Package Manager — download, run, and share AI models from the command line

Enforce real-time token budgets and spending limits for OpenAI, Anthropic Claude, and Google Gemini API calls in Node.js

Hardware accelerated language model chats on browsers

LLM eval & testing toolkit

Lightweight, zero-dependency LLM API cost & token usage tracker for OpenAI, Anthropic, Gemini, Mistral, Groq, and DeepSeek

Opik TypeScript and JavaScript SDK

<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>

micromark extension to support math (`$C_L$`, `\(C_L\)`)

Typescript bindings for langchain

Display language model outputs in your React project.

Package to connect and trace LLM calls.

Superfast runtime validators with only one line

Detox driver for Wix Pilot usage

[llm-ui](https://llm-ui.com) markdown block.

[llm-ui](https://llm-ui.com) code block.

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

Traceloop Software Development Kit (SDK) for Node.js

[llm-ui](https://llm-ui.com) JSON blocks for building custom components.

The best library to work with LLMs

Self-learning LLM runtime — TurboQuant KV-cache (6-8x compression), SONA adaptive learning, FlashAttention, speculative decoding, GGUF inference

Superfast runtime validators with only one line

Client library to connect to the LangSmith Observability and Evaluation Platform.