Chatbot to answer your questions as a conversational agent from a Notion knowledge base

Purpose

An experimental RAG chatbot using Notion database as knowledge base. The chatbot is built using

• Streamlit web app for the chatbot
• Qdrant for vector search
• OpenAI for text generation and embeddings
• Notion for fetching content and metadata from Notion database

Article with step-by-step details.

Features

• Chatbot using OpenAI models for RAG text generation and embeddings
• Uses Notion database documents for document embeddings
• Uses Qdrant for vector search
• Streamlit web app for the chatbot
• Settings for search are configurable
• Search result embeddings from Notion database are shown

Example

Example of the chatbot answering questions from a Notion database. The database is a knowledge base about SAP Commerce (Hybris) - an eCommerce platform by SAP.

HOW TO RUN THE APP LOCALLY

Follow these steps to set up and run the python app locally :

Prerequisites

• Python 3.8 or higher
• Git
• Poetry

Installation

Clone the repository :

git clone https://github.com/johntday/notion-chat.git

Navigate to the project directory :

cd notion-chat
# now at project root

Create a virtual environment and install requirements using Poetry :

poetry install

Setup Environment Variables :

# at project root
cp notion_chat/.streamlit/secrets.toml.example notion_chat/.streamlit/secrets.toml

# edit the "secrets.toml" file and add your OpenAI API key

Run the app locally :

cd notion_chat
streamlit run chat.py

Pycharm Run Configuration

If you are using Pycharm, you can create a run configuration to run the app locally :

References

• Streamlit
• Qdrant
• OpenAI
• Notion
• Langchain
• Using Poetry
• Article with Step by Step Details