ipylangchat 0.0.1

Serverless chat UI Jupyter widget for langchain conversational AIs

ipylangchat 💬

A minimal Chat UI Jupyter Widget for language models. Built with anywidget 💪.

Lets you talk to a LangChain runnable or agent, such as a conversational RAG, directly in a Jupyter environment (Notebook, Lab, Google Colab, VSCode). No need to serve a web application.

See the RAG example notebook.

Installation

pip install ipylangchat

Development installation

Create a virtual environment and and install ipylangchat in editable mode with the optional development dependencies:

python -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"

Open example.ipynb in JupyterLab, VS Code, or your favorite editor to start developing. Changes made in src/ipylangchat/static/ will be reflected in the notebook.

Usage

Note: This is still a very basic implementation that demonstrates the power of the anywidget framework to bring custom UIs into Jupyter.

Right now, the widget accepts a chain using a prompt template that takes in human input as {input} and keeps track of chat history through a {chat_history} message placeholder. See the langchain docs and our example of a conversational RAG on the anywidget documentation.

import ipylangchat

ipylangchat.ChatUIWidget(chain)