https://github.com/noluyorabi/openaiscientist
AI analysis R package for generating comprehensive scientific reports and plots using OpenAI's API.
https://github.com/noluyorabi/openaiscientist
ai analysis api gpt gpt4 httr openai openai-api r r-package readr scie summarizer useful
Last synced: 8 months ago
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AI analysis R package for generating comprehensive scientific reports and plots using OpenAI's API.
- Host: GitHub
- URL: https://github.com/noluyorabi/openaiscientist
- Owner: noluyorAbi
- License: gpl-3.0
- Created: 2024-07-08T13:14:17.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-07-13T21:58:50.000Z (over 1 year ago)
- Last Synced: 2024-07-13T22:46:33.918Z (over 1 year ago)
- Topics: ai, analysis, api, gpt, gpt4, httr, openai, openai-api, r, r-package, readr, scie, summarizer, useful
- Language: R
- Homepage:
- Size: 250 KB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# openAIScientist 🧪🔬
`openAIScientist` is an R package that generates comprehensive scientific analysis using OpenAI's API. The analysis is output in markdown format, making it easy to integrate into various documentation workflows.
`openAIScientist` was designed to provide users with a quick overview and analysis of their datasets, helping them to understand and interpret their data more efficiently.
## Table of Contents
- [Installation](#installation-)
- [Other Dependencies](#other-dependencies-)
- [Usage](#usage-)
- [Function Arguments](#function-arguments-)
- [Example](#example-)
- [Setting Up Your API Key](#setting-up-your-api-key-)
- [Step-by-Step Instructions](#step-by-step-instructions-)
- [Note on API Key Usage](#note-on-api-key-usage-)
- [Documentation](#documentation-)
- [Disclaimer](#disclaimer-)
- [Contributing](#contributing-)
- [License](#license-)
## Installation 💻
First, install the package along with its dependencies if you haven't already:
```r
library(devtools)
install_github("noluyorAbi/openaAIScientist")
```
## Other Dependencies 📦
The `openAIScientist` package relies on the following R packages, which will be installed automatically:
- `httr`: For HTTP requests.
- `utils`: For utility functions like capturing output.
- `readr`: For reading and writing data.
## Usage 🚀
To use the `openAIScientist` package, follow these steps:
1. Load the package.
2. Load your API key from `.Renviron`.
3. Use the `openAIScientist_generate_scientific_analysis` or `openAIScientist_generate_visualization_rmd` function to generate the analysis.
### Function Arguments 📊
#### `openAIScientist_generate_scientific_analysis`
- `data` (mandatory): A data frame containing the dataset to analyze.
- `api_key` (mandatory): Your OpenAI API key as a string.
- `output_name` (optional): The name of the output markdown file (default is "Analysis").
- `additional_prompt` (optional): Additional instructions for the OpenAI API.
#### `openAIScientist_generate_visualization_rmd`
- `data` (mandatory): A data frame containing the dataset to analyze.
- `api_key` (mandatory): Your OpenAI API key as a string.
- `output_name` (optional): The name of the output RMarkdown file (default is "Visualization").
- `additional_prompt` (optional): Additional instructions for the OpenAI API.
### Example 📝
```r
# Load the package
library(openAIScientist)
# Load environment variables from the .Renviron file
readRenviron(".Renviron")
# Example data
data <- data.frame(
var1 = rnorm(100),
var2 = rnorm(100),
outcome = sample(c(0, 1), 100, replace = TRUE)
)
# Retrieve the API key from environment variables
api_key <- Sys.getenv("OPENAI_API_KEY")
# Generate scientific analysis
analysis <- openAIScientist_generate_scientific_analysis(data, api_key, "Analysis")
# Generate scientific analysis with additional prompt
analysis <- openAIScientist_generate_scientific_analysis(data, api_key, "Analysis-ADDITIONAL-PROMPT","Write the analysis in German")
# Generate visualization RMarkdown
visualization <- openAIScientist_generate_visualization_rmd(data, api_key, "Visualization")
# Generate visualization RMarkdown with additional prompt
visualization <- openAIScientist_generate_visualization_rmd(data, api_key, "Visualization-ADDITIONAL-PROMPT", "make the visualizations for red-green colorblind")
```
## Setting Up Your API Key 🔑
To securely store and load your OpenAI API key, you should use the `.Renviron` file. This file allows you to set environment variables that R can access.
### Step-by-Step Instructions 📝
1. **Create/Edit `.Renviron` File:**
- Open your `.Renviron` file. If it doesn't exist, create it in your home directory or in the root of your project folder.
- Add your OpenAI API key in the following format:
```plaintext
OPENAI_API_KEY=your_openai_api_key
```
2. **Save and Reload Environment Variables:**
- Save the `.Renviron` file.
- In R, use the following command to reload the environment variables:
```r
readRenviron("~/.Renviron")
```
3. **Access the API Key in Your R Script:**
- Retrieve the API key using `Sys.getenv` as shown in the usage example above.
```r
api_key <- Sys.getenv("OPENAI_API_KEY")
```
### Note on API Key Usage ℹ️
While you can directly paste your API key as an argument in the `generate_scientific_analysis` function, it is considered bad practice and results in “smelly” code. Using environment variables via `.Renviron` is a more secure and clean approach.
#### Example of "Smelly" Code ❌
```r
# Directly pasting the API key as an argument (not recommended)
analysis <- openAIScientist_generate_scientific_analysis(data, "your_openai_api_key", "Analysis")
```
Using environment variables as demonstrated in the previous examples is the recommended approach.
## Documentation 📖
For detailed documentation, please refer to the function documentation generated by Roxygen2. You can access the documentation within R:
```r
?openAIScientist_generate_scientific_analysis
?openAIScientist_generate_visualization_rmd
```
## Disclaimer ⚠️
The analysis is created with GPT-4, a very powerful and fast AI. However, there can still be inaccuracies and formatting issues as AIs can be unpredictable sometimes. For formatting issues, try reanalyzing the dataset.
## Contributing 🤝
If you find any issues or have suggestions for improvements, please create an issue or a pull request on GitHub.
## License 📜
This package is licensed under the GPL-3 License.
---
Made with ♥ by [noluyorAbi](https://github.com/noluyorAbi) for FortStaSoft @ LMU Munich, July 2024.