PEPEGA

Prompt Engineering with Paragraph Embeddings for Generating Answers (PEPEGA)

Description

This a code for launching Telegram bot which is capable of answering ML-related questions through GPT-3 based service

Examples

How to use

The bot is publicly available at https://t.me/PepegaAIBot

Custom Telegram bot

If you want to use adopt on your own bot, follow the next steps:

1. Clone the repo
2. Create .env file with the following fields:
   • db_login - login for admin in MongoDB
   • db_pass- password for admin in MongoDB
   • db_name- name for root database in MongoDB
   • bot_api_token - Telegram bot API token
   • openai_api_token - OpenAI api token
3. Run the bot service using docker-compose up

Custom data

For now, the embedded paragraphs consist of ~200 articles about classical ML and a bit of DL. If you want to query PEPEGA on your custom data, do the following:

1. Replace paragraphs.json with your custom list of paragraphs which are gonna act as context for GPT-3 prompt
2. Use previously built paragraphs.json file to build pynndescent index with cosine distance, pickle it, and replace with current index.pkl file