fixed readme

README.md

@@ -1,4 +1,23 @@
 # Prompt Engineering Survey
+Generative Artificial Intelligence (GenAI) systems are being increasingly deployed across all parts of
+industry and research settings. Developers and end users interact with these systems through the use of
+prompting or prompt engineering. While prompting is a widespread and highly researched concept, there
+exists conflicting terminology and a poor ontological understanding of what constitutes a prompt due to the
+area’s nascency. This repository is the code for The Prompt Report, our research that establishes a structured 
+understanding of prompts, by assembling a taxonomy of prompting techniques and analyzing their use. This code 
+allows for the automated review of papers, the collection of data, and the running of experiments. Our dataset 
+is available on [Hugging Face](https://huggingface.co/datasets/PromptSystematicReview/ThePromptReport)
+
+## Table of Contents
+- [Prompt Engineering Survey](#prompt-engineering-survey)
+  - [Table of Contents](#table-of-contents)
+  - [Install requirements](#install-requirements)
+  - [Setting up API keys](#setting-up-api-keys)
+  - [Setting up keys for running tests](#setting-up-keys-for-running-tests)
+  - [Structure of the Repository](#structure-of-the-repository)
+  - [Running the code](#running-the-code)
+    - [TLDR;](#tldr)
+  - [Notes](#notes)
 
 ## Install requirements
 
@@ -40,13 +59,26 @@ The core of the repository is in `src/prompt_systematic_review`. The `config_dat
 
 The source folder is divided into 4 main sections: 3 scripts (`automated_review.py`, `collect_papers.py`,`config_data.py`) that deal with collecting the data and running the automated review, the `utils` folder that contains utility functions that are used throughout the repository, the `get_papers` folder that contains the scripts to download the papers, and the `experiments` folder that contains the scripts to run the experiments. 
 
-At the root, there is a `data` folder. It comes pre-loaded with some data that is used for the experiments, however the bulk of the dataset can either be generated by running `main.py` or by downloading the data from huggingface. It is in `data/experiments_output` that the results of the experiments are saved.
+At the root, there is a `data` folder. It comes pre-loaded with some data that is used for the experiments, however the bulk of the dataset can either be generated by running `main.py` or by downloading the data from Hugging Face. It is in `data/experiments_output` that the results of the experiments are saved.
 
 Notably, the keywords used in the automated review/scraping process are in `src/prompt_systematic_review/utils/keywords.py`. Anyone who wishes to run the automated review can adjust these keywords to their liking in that file. 
 
 ## Running the code
+
+### TLDR;
+```bash
+git clone https://github.com/trigaten/Prompt_Systematic_Review.git && cd Prompt_Systematic_Review
+pip install -r requirements.txt
+# create a .env file with your API keys
+nano .env
+git lfs install
+git clone https://huggingface.co/datasets/PromptSystematicReview/ThePromptReport
+mv ThePromptReport/* data/
+python main.py
+```
+
 Running `main.py` will download the papers, run the automated review, and run the experiments.
-However, if you wish to save time and only run the experiments, you can download the data from huggingface and move the papers folder and all the csv files in the dataset into the data folder (should look like `data/papers/*.pdf` and `data/master_papers.csv` etc). Adjust main.py accordingly. 
+However, if you wish to save time and only run the experiments, you can download the data from [Hugging Face](https://huggingface.co/datasets/PromptSystematicReview/ThePromptReport) and move the papers folder and all the csv files in the dataset into the data folder (should look like `data/papers/*.pdf` and `data/master_papers.csv` etc). Adjust main.py accordingly. 
 
 Every experiment script has a `run_experiment` function that is called in `main.py`. The `run_experiment` function is responsible for running the experiment and saving the results. However each script can be run individually by just running `python src/prompt_systematic_review/experiments/<experiment_name>.py` from root.