Welcome to PAIAssistant 👋

PAIAssistant is a AI tool designed for users interact with emails via natural language queries. This demo showcases its ability to organize emails using a vector database. It features various Retrieval-Augmented Generation (RAG) methods including Basic Retrieval, Sentence Window Retrieval, and Auto-Merging Retrieval. These methods enhance the processing of user queries, which are then handled by a Large Language Model (LLM) like OpenAI's. The AI generates responses that can be either displayed on-screen or read aloud, offering a comprehensive and user-friendly email management experience.

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Demo clip

Installation and Setup

The steps below can be used to setup the enviroment for this demo to run on Ubuntu 20.04.6 LTS. Alternatively you can setup the python3.10 environment on a windows machine with Nvidia gpu card with necessary drivers. The install will run with or without GPU. Running locally would be very slow on CPU inference. Running with OpenAI support could be alternative if GPU is not available. Check flag/api key settings in documentation to use OpenAI.

Optional: If you already have access to ubuntu instance, you can skip this section.

NOTE: This example VM setup will work for OpenAI inference. Local inference will be very slow due to lack of GPU. For local inference use a machine with GPU, windows or linux.

Download Ubuntu 20.04.6 LTS server ISO image.
Download Oracle VirtualBox.
Create a new virtual machine with the ubuntu image downloaded above. Sample configuration is 4gb ram, 2 vcpu, bridged network settting, 25 gb disk.
Signup for platform.openai.com and generate OpenAI api key

Install net-tools and update fresh linux vm.

    sudo apt install net-tools
    sudo apt update && sudo apt upgrade

Install Python 3.10

    sudo apt install software-properties-common -y
    sudo add-apt-repository ppa:deadsnakes/ppa -y
    sudo apt update
    sudo apt install python3.10
    sudo apt install python-is-python3

Setup Python 3.10 as default

    sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.10 1
    sudo update-alternatives --config python3

Setup Pip

    curl https://bootstrap.pypa.io/get-pip.py | python
    sudo apt install python3.10-distutils

Install npm & reboot

    sudo apt install npm
    sudo reboot now

Clone repository and update config

Change directory to web. If necessary update host/port parameter in config.json
Change directory to web/public. Update the completion.apiendpoint to the ip address of your instance.
Change directory to api. Update config.ini to update host/port parameters if needed.

Data set and index

Current version has 250 random emails in email folder ready for indexing. Basic and sentence indexes are also provided so you can start playing with demo without further indexing work. If you need to index with your own custom data follow these steps.

You can use your own email data in plain text format or use the data set used in this example and random sample from Kaggle
Copy these emails to emails folder and run createindex.py to create the vector index (basic/sentence/automerge) for query.

    cd api    
    export OPENAI_API_KEY=<YOUR OPENAI API KEY>    
    python createindex.py

Choose index to query

Choose which version of index to query by updating the config.ini in api folder [api] section.

Bring up the website and api service

    cd web
    npm install
    npm start

    cd api
    pip install -r requirements.txt
    export OPENAI_API_KEY=<YOUR OPENAI API KEY>
    python api.py

Running locally vs using openai

To use openai set the following attribute in api/config.ini. By default it is set to false.

useopenai=true

Visit in chrome browser

https://[ipaddress]:4000 in chrome browser to use the demo.
https://[ipaddress]:7860 gradio text input/response interface.

TODO

Create a jupyter notebook
Create google colab notebook
Create Docker image
Create git workflow to post to hosting platform to visualize it.

📝 License

This project is Apache-2.0 licensed.

ShadNygren / PAIAssistantAPI