Skip to content

Latest commit

 

History

History

GG

Folders and files

NameName
Last commit message
Last commit date

parent directory

..
main.py
main.py
 
 
prompts.py
prompts.py
 
 
readme.md
readme.md
 
 
test.py
test.py
 
 
utils.py
utils.py
 
 

readme.md

Graph Generation with Large Language Models (GG Subtask)

Important Update

Note: The gpt-3.5-turbo-0613 model is deprecated and replaced with gpt-3.5-turbo. Consequently, results obtained using gpt-3.5-turbo may differ from those reported in earlier experiments using gpt-3.5-turbo-0613.

Installation

  1. Clone the repository:
git clone https://github.com/HLR/BLInD.git
cd BLInD
  1. Install the required dependencies:
python -m pip install --upgrade pip
pip install -r requirements.txt
cd GG

Usage

To query LLMs for GG, use the main.py script:

python main.py [--testdataset TESTDATASET] [--outputdataset OUTPUTDATASET] 
[--openaikey OPENAIKEY] [--openaiorg OPENAIORG] [--replicatekey REPLICATEKEY]
[--samplenum SAMPLENUM] [--models MODELS [MODELS ...]] [--maxattempt MAXATTEMPT]

Arguments:

  • --testdataset: Input test dataset (default: "../datasets/Colored_1000_examples.csv")
  • --outputdataset: Dataset folder to save the results (default: "../datasets/")
  • --openaikey: OpenAI API key (required for GPT models)
  • --openaiorg: OpenAI organization key
  • --replicatekey: Replicate.ai API key (required for non-GPT models)
  • --samplenum: Number of instances of the dataset to read (default: 2)
  • --models: Choose one or more models (choices: "gpt-3.5-turbo", "gpt-4-0613", "meta/meta-llama-3-70b-instruct", "mistralai/mistral-7b-instruct-v0.2", "meta/llama-2-70b-chat")
  • --maxattempt: Max number of attempts after a failed prompt (default: 10)

Note: For non-GPT models (Llama, Mistral), you need to provide a Replicate.ai API key using the --replicatekey argument.

This program saves every answer after each prompt. If it terminates, run it again, and it will pick up where it left off.

Testing LLMs for Bayesian Inference

To test LLMs for GG, use the test.py script:

python test.py [--testdataset TESTDATASET] [--outputdataset OUTPUTDATASET]
[--models MODELS [MODELS ...]]
  • --testdataset: Input test dataset (default: "../datasets/Colored_1000_examples.csv")
  • --outputdataset: Dataset folder that has saved the results (default: "../datasets/")
  • --models: Choose one or more models from the available options

Dataset

The code uses a test dataset specified by the --testdataset argument. By default, it uses the "../datasets/Colored_1000_examples.csv" dataset.

Models

The code supports running Bayesian inference with the following LLMs:

  • GPT-3.5-turbo
  • GPT-4-0613
  • Meta Llama 3 70B Instruct
  • Mistral 7B Instruct v0.2
  • Llama 2 70B Chat

Output

The results of running Bayesian inference are saved in the dataset folder specified by the --outputdataset argument. The output files are named based on the arguments set in main.py.