This is a small app that uses the EvaDB ChatGPT utility to convert unstructured data to a provided stuctured format. For the timebeing we focus on user hardware and software complaints. The data/user_complaints.csv file contains some example queries.
We run them through ChatGPT via a crafted prompt which classifies the Issue category and Issue Component along with displaying the raw issue string. The default format is the following
DEFAULT_STRUCTURE_FORMAT = [
[
"Issue Category",
"What category the issue belongs to",
"One of (hardware, software)",
],
[
"Raw Issue String",
"Raw String containing the exact input given by the user",
"string",
],
["Issue Component", "Component that is causing the issue", "string"],
]
Query : The keyboard on my laptop is typing the wrong letters and it's driving me crazy!
✅ Answer:
{
"Issue Category": "hardware",
"Raw Issue String": "The keyboard on my laptop is typing the wrong letters and it's driving me crazy!",
"Issue Component": "keyboard"
}
✅ Answer:
Query : My headphones won't connect to my phone anymore, even though they used to work just fine.
{
"Issue Category": "hardware",
"Raw Issue String": "My headphones won't connect to my phone anymore, even though they used to work just fine.",
"Issue Component": "headphones"
}
Clone the project
git clone https://github.com/hershd23/eva-structure-gpt.git
cd eva-structure-gpt
Create a new python environment in conda or venv, and activate that environement (Optional but recommended)
python3 -m venv /env
source env/bin/activate
Install the dependencies
pip install -r requirements.txt
Simply run the main.py file and input the query, openai key and any additional inputs you want to add to the prompt
python3 main.py
- Currently the prompt and and the structure are kind of static. Allow user to add their own structure and paradigm of data.
- More experimentation required with the prompt