https://github.com/narenkhatwani/arkouda-chatbot

This repository provides a Python-based API that uses OpenAI's GPT-3.5 model to answer queries related to the Arkouda distributed data processing library.
https://github.com/narenkhatwani/arkouda-chatbot

arkouda gpt-3 high-performance-computing hpc

Last synced: 3 months ago
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This repository provides a Python-based API that uses OpenAI's GPT-3.5 model to answer queries related to the Arkouda distributed data processing library.

• Host: GitHub
• URL: https://github.com/narenkhatwani/arkouda-chatbot
• Owner: narenkhatwani
• Created: 2023-03-24T18:12:41.000Z (about 2 years ago)
• Default Branch: main
• Last Pushed: 2023-04-15T03:55:29.000Z (about 2 years ago)
• Last Synced: 2025-02-06T05:18:23.089Z (4 months ago)
• Topics: arkouda, gpt-3, high-performance-computing, hpc
• Language: Python
• Homepage: https://narenkhatwani-arkouda-chatbot-app-fyqztk.streamlit.app/
• Size: 525 KB
• Stars: 0
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Arkouda Chatbot using Open AI's GPT-3.5 API

![banner](https://github.com/narenkhatwani/arkouda-chatbot/blob/main/resources/image.png)

This repository provides a Python-based API that uses OpenAI's GPT-3.5 model to answer queries related to the Arkouda distributed data processing library. The API is based solely on the official Arkouda documentation, and aims to provide accurate and informative responses to a wide range of user questions.

Whether you're a seasoned Arkouda user or just getting started, the Arkouda GPT-3.5 Query API is a convenient and powerful tool for getting the answers you need.

In order to create your own customized Assistant, you can just FORK this repository and change the rules as per your need in `app.py` and follow the steps given below

Prerequisites and procedure to run this:

- You should have an API key from Open AI to use the GPT 3.5 Turbo Model - [link](https://platform.openai.com/)

#### Step 1

`pip install streamlit`

`pip install openai`

#### Step 2

Open up a terminal over this repository and run 

`streamlit run app.py`

Fun Fact: The above description was also written using GPT 

The code was inspired by my friend Advait's tweet [link](https://twitter.com/lifeofadvait/status/1637457907942817793?s=20)