open-instruct/scripts/persona_driven_data_gen

Persona-driven Data Generation

To start make sure you have your OpenAI and Anthropic API keys and have installed the libraries listed in requirements.txt:

pip install -r requirements.txt

This folder contains code to synthetically generate data (both prompts and responses) for target skill using a persona-driven approach:

1- Precise Instruction Following:

# Generate Instruction Following prompts
python persona_driven_generate_ifdata.py --model "gpt-4o" --start_index 0 --end_index 1000 --output_path if_prompts.jsonl --openai_key Z --org_id YYY --dataset ai2-adapt-dev/personahub_personas --template instruction_following

# Generate Responses for generated prompts
python persona_driven_generate_ifdata.py --model "gpt-4o" --start_index 0 --end_index 1000 --output_path if_solutions.jsonl --openai_key Z --org_id YYY --dataset if_prompts.jsonl --template instruction_following_solution

# Rewrite prompts to form Rejected Response (used for Presona-IF DPO data)
python persona_driven_generate_ifdata.py --model "gpt-4o" --start_index 0 --end_index 1000 --output_path if_solutions.jsonl --openai_key Z --org_id YYY --dataset if_prompts.jsonl --template rewrite_if_prompt

2- Math World Problems

# Generate math word problems
python persona_driven_generate_math_code.py --model "gpt-4o" --end_index 1000 --output_path <MATH_PROBLEMS> --openai_key XXX --org_id YYY --dataset ai2-adapt-dev/personahub_personas --template math

# Generate math solutions for generated math problems
python persona_driven_generate_math_code.py --model "gpt-4o" --end_index 1000 --output_path <OUTPUT_MATH> --openai_key XXX --org_id YYY --dataset <MATH_PROBLEMS> --template math_solution 

Note that you can change --template to any of ['grade_math', 'math_int_algebra'] to generate other types of math data.

3- Code (python)

# Generate python problems

python persona_driven_generate_math_code.py --model "gpt-4o" --start_index 0 --end_index 1000 --output_path <PYTHON_PROBLEMS> --openai_key XXX --org_id YYY --dataset ai2-adapt-dev/personahub_personas --template code 

# Generate python code
python persona_driven_generate_math_code.py --org_name anthropic --model 'claude-3-5-sonnet-20240620' --start_index 0 --end_index 1000 --output_path <OUTPUT_CODE> --openai_key XXX --org_id YYY --dataset <PYTHON_PROBLEMS> --template code_solution 

Note that we used claude-3-5-sonnet-20240620 to generate python codes.

All generated prompts and solutions will be saved in the messages format ready for supervised finetunig. An example output can be found here