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It is a fast, open source text processor and publishing toolchain for converting AsciiDoc content to HTML5, DocBook, PDF, and other formats. Asciidoctor is written in Ruby and runs on all major operating systems

That transforms AI-generated content into natural, undetectable human-like writing. Bypass AI detection systems with intelligent text humanization technology

It is a framework built around LLMs. It can be used for chatbots, generative question-answering, summarization, and much more. The core idea of the library is that we can “chain” together different components to create more advanced use cases around LLMs.

It allows you to run open-source large language models, such as Llama 2, locally.

It is a project that provides a central interface to connect your LLMs with external data. It offers you a comprehensive toolset trading off cost and performance.

It is a library for building stateful, multi-actor applications with LLMs, built on top of (and intended to be used with) LangChain. It extends the LangChain Expression Language with the ability to coordinate multiple chains (or actors) across multiple steps of computation in a cyclic manner.

Transform basic prompts into expert-level AI instructions. Enhance, benchmark & optimize prompts for ChatGPT, Claude, Gemini & more.

Find what caused your AI bill. Opsmeter gives endpoint, user, model, and prompt-level AI cost attribution in one view.

It is a platform for building production-grade LLM applications. It lets you debug, test, evaluate, and monitor chains and intelligent agents built on any LLM framework and seamlessly integrates with LangChain, the go-to open source framework for building with LLMs.
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