Prompt-Engineering-Intro

This repository contains a starter python notebook to get one started with basic Prompt engineering using OpenAI's GPT3 models. This accompanies the medium blog: An Introduction to Prompt Engineering for OpenAI GPT LLMs

Setup

1. Create a new environment using conda

   conda create -n genai python=3.10

2. intall required packages

   pip install -r requirements.txt

You also need to create couple of api keys

• OpenAI Api Key - signup and generate one here - https://platform.openai.com/signup
• SerpApi Key - Setup Search capability to be able to search using Google and various other services. Visit this link and follow instructions to create an api key - https://serpapi.com/

One of the example uses Sqlite database - chinook, a database representing a digital media store, including tables for artists, albums, media tracks, invoices and customers.

References

Libraries used:

1. openai
2. LangChain

Papers referenced

1. Chain of Thoughts Prompting - https://arxiv.org/pdf/2201.11903.pdf
2. Self Consistency Prompting - https://arxiv.org/pdf/2203.11171.pdf
3. ReAct - Reason and Act prompting - https://arxiv.org/pdf/2210.03629.pdf
4. PAL - Program aided Language Models - https://arxiv.org/pdf/2211.10435.pdf
5. MRKL Systems - Modular Reasoning, Knowledge and Language  - https://arxiv.org/pdf/2205.00445.pdf
6. Self Ask with Search - https://arxiv.org/pdf/2210.03350.pdf

Misc other references

1. https://learnprompting.org/
2. https://github.com/dair-ai/Prompt-Engineering-Guide