@nlux/langchain-react
v2.17.1
Published
The LangServe adapters for nlux React, the React JS library for building conversational AI interfaces.
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NLUX React LangChain Adapter
This package enables the integration between NLUX React and LangChain, the LLM framework.
More specifically ― the package includes the adapter to connect NLUX React to backends built
using LangServe.
Features:
- Support for both
/invoke
and/stream
endpoints to allow for responses to be streamed back as they are generated. - Can utilize the
/input_schema
to construct a matching payload. - Ability to customize the payloads, both sent and received.
For more information on how to use this package, please visit: docs.nlkit.com/nlux/reference/adapters/langchain-langserve
Vanilla JS 🟨 vs React JS ⚛️
This package @nlux/langchain-react
is meant for use with the React JS version of NLUX.
If you're looking for the vanilla JS version, please check
the @nlux/langchain
package.
About NLUX
NLUX (for Natural Language User Experience) is an open-source JavaScript library that makes it simple to integrate powerful large language models (LLMs) like ChatGPT into your web app or website. With just a few lines of code, you can add conversational AI capabilities and interact with your favorite LLM.
Key Features 🌟
- Build AI Chat Interfaces In Minutes ― High quality conversational AI interfaces with just a few lines of code.
- React Components & Hooks ―
<AiChat />
for UI anduseChatAdapter
hook for easy integration. - LLM Adapters ― For
ChatGPT
/LangChain
🦜 LangServe /HuggingFace
🤗 Inference. - A flexible interface to Create Your Own Adapter for any LLM or API.
- Assistant and User Personas ― Customize the assistant and user personas with names, images, and more.
- Streaming LLM Output ― Stream the chat response to the UI as it's being generated.
- Customizable Theme - Easily customize the look and feel of the chat interface using CSS variables.
- Event Listeners - Listen to messages, errors, and other events to customize the UI and behaviour.
- Zero Dependencies ― Lightweight codebase, with zero-dep except for LLM front-end libraries.
Docs & Examples 📖
For developer documentation, examples, and API reference ― you can visit: docs.nlkit.com/nlux