Enforce real-time token budgets and spending limits for OpenAI, Anthropic Claude, and Google Gemini API calls in Node.js
Typescript bindings for langchain
Display language model outputs in your React project.
[llm-ui](https://llm-ui.com) markdown block.
LLM eval & testing toolkit
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
[llm-ui](https://llm-ui.com) JSON blocks for building custom components.
Detox driver for Wix Pilot usage
micromark extension to support math (`$C_L$`, `\(C_L\)`)
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
<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
JavaScript obfuscator
The best library to work with LLMs
Superfast runtime validators with only one line
[](https://dl.circleci.com/status-badge/redirect/gh/taneliang/coerce-llm-output/tree/main) [, 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.
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
PrReview collects PR data from GitHub (description, commits, comments, linked issues, and code changes) and formats it as XML. Paste this XML into any LLM like ChatGPT or Claude to get helpful code reviews.
Detect prompt injection, content violations, data leakage, and unknown links in LLM inputs and outputs.
A comprehensive Ruby tool for building and optimizing documentation for Large Language Models. Features include: generating llms.txt files from documentation directories with automatic file prioritization, transforming individual markdown files by expanding relative links to absolute URLs, bulk transforming entire documentation trees with customizable exclusion patterns, comparing content sizes to measure context window savings, and serving LLM-optimized documentation. Provides both CLI and Ruby API with configuration file support.
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