/notion-qa

a bit expensive and time consuming... need optimize to get relevant content

Primary LanguagePythonMIT LicenseMIT

Notion Question-Answering

πŸ€–Ask questions to your Notion database in natural languageπŸ€–

πŸ’ͺ Built with LangChain

🌲 Environment Setup

In order to set your environment up to run the code here, first install all requirements:

pip install -r requirements.txt

Then set your OpenAI API key (if you don't have one, get one here)

export OPENAI_API_KEY=....

πŸ“„ What is in here?

  • Example data from Blendle
  • Python script to query Notion with a question
  • Code to deploy on StreamLit
  • Instructions for ingesting your own dataset

πŸ“Š Example Data

This repo uses the Blendle Employee Handbook as an example. It was downloaded October 18th so may have changed slightly since then!

πŸ’¬ Ask a question

In order to ask a question, run a command like:

python qa.py "is there food in the office?"

You can switch out is there food in the office? for any question of your liking!

This exposes a chat interface for interacting with a Notion database. IMO, this is a more natural and convenient interface for getting information.

πŸš€ Code to deploy on StreamLit

The code to run the StreamLit app is in main.py. Note that when setting up your StreamLit app you should make sure to add OPENAI_API_KEY as a secret environment variable.

πŸ§‘ Instructions for ingesting your own dataset

Export your dataset from Notion. You can do this by clicking on the three dots in the upper right hand corner and then clicking Export.

export

When exporting, make sure to select the Markdown & CSV format option.

export-format

This will produce a .zip file in your Downloads folder. Move the .zip file into this repository.

Run the following command to unzip the zip file (replace the Export... with your own file name as needed).

unzip Export-d3adfe0f-3131-4bf3-8987-a52017fc1bae.zip -d Notion_DB

Run the following command to ingest the data.

python ingest.py

Boom! Now you're done, and you can ask it questions like:

python qa.py "is there food in the office?"