Large Language Model Qualitative Coder Application.
Use this to apply pre-made codes with descriptions to pieces of text, for example labelling questionnaire responses.
Loosely based on the methods defined by Tai et al. and Xiao et al.
- Make a copy of
/input_sample
directory named/input
- Update the example files inside the
/input
directory with your own data- Enter your codebook in
codes.csv
- Enter the data you want to code in
responses.csv
- Enter your reference, human-coded lines, if you have any, in
reference.csv
- this is for intercoder reliability calculations
- Enter your codebook in
- Install dependencies with
pip install -r requirements.txt
- Run the Codyan with
python app.py
- Navigate to
http://127.0.0.1:8000
- Obtain and enter your OpenAI API key
- Follow the on-screen instructions to load your input data, your codeset, perform coding and analyse your results
- Find your results in the
/output
folder and on-screen. The used prompts are also saved in/output/prompts.csv
With any questions, feel free to contact me at [email protected]
If you prefer to run Codyan as a docker container, you can build the image and run it as follows:
- Build image with
docker build --tag codyan .
- Run image with
docker run -d -p 8000:5000 codyan
where 8000 is the port you will access the application at