ArxivChatBot_StreamlitApp GPTSimpleVectorIndex

A Chatbot based on openAI and streamlit for Arxiv

Intro

We create an ArxivChatBot App using Streamlit, llama_index, Langchain and OpenAI.You need to have an account on OpenAI along with its available Api key. The ChatBot is trained on a specific query, the number of files and a specific criterion. This ChatBot is an extension of the previous related Arxiv repos and is trained based on three parameters:

1. Search query
2. Number of files
3. Search criterion:
   • a)Relevance
   • b)Last updated
   • c)Submitt Date

Note this version works locally only on your computer and not on the platform of Streamlit. You can find a working updated version of the the app on platfom . In case you find it useful you can donate on [Stripe (https://buy.stripe.com/cN2dUu44OahXaJO288).

Quick Start

• Input the Open Api-key and press Enter.
• Input Query,number of files and choose Relevance, Last updated or Submitted date and press load.
• The maximum number of files you can enter are 50.
• When you see the message "Arxiv papers are loaded based on the criteria" you are ready to chat as a User.
• Under the User ask the question and press the Submit button, wait a little and the Chatbot will respond you.

We are using the default chat model from OpenAI ChatGPT-4.

Issues

In the case of a free OpenAI API key takes time to index the loaded pdf files since a free API key has a restricted rate limits. To make the process fast, you can use a paid API key. It is not so fast during the training along with the response from the Chatbot engine.

Future Prospectives

We are looking to improve the layout and be more self-explanatory. Also, we will provide option to download the requested pdf files along with their abstracts.

References

1. https://github.com/StanfordVL/arxivbot/
2. https://github.com/emptycrown/llama-hub/blob/main/loader_hub/papers/arxiv/
3. https://llamahub.ai/l/papers-arxiv
4. https://github.com/mmz-001/knowledge_gpt/tree/main
5. https://www.arxiv.org/