scripts

Generate LLM code

Your first need to set up your API keys. For this, create a keys.cfg file at the root of the repository and add keys as follows:

OPENAI_KEY = 'your_api_key'
ANTHROPIC_KEY = 'your_api_key'
GOOGLE_KEY = 'your_api_key' 

For example, to create model results with gpt-4o and the default settings, go to the root of this repo and run

python eval/scripts/gencode_json.py --model gpt-4o

For results with scientist-annotated background, run

python eval/scripts/gencode_json.py --model gpt-4o --with-background

Command-Line Arguments

• --model - Specifies the model name used for generating responses.
• --output-dir - Directory to store the generated code outputs (Default: eval_results/generated_code).
• --input-path - Directory containing the JSON files describing the problems (Default: eval/data/problems_all.jsonl).
• --prompt-dir - Directory where prompt files are saved (Default: eval_results/prompt).
• --with-background - Include problem background if enabled.
• --temperature - Controls the randomness of the generation (Default: 0).

Evaluate generated code

Download the numeric test results and save them as ./eval/data/test_data.h5

To run the script, go to the root of this repo and use the following command:

python eval/scripts/test_generated_code.py --model "model_name"