Automatic Item Generation and Validation via Network-Integrated Evaluation


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Documentation for package ‘AIGENIE’ version 2.1.2

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AIGENIE Generate, Validate, and Check Items using AI-GENIE
build_item_attributes_from_items Build item.attributes Object from Items Data Frame
chat Chat with an LLM via API Calls
check_for_default_APIs Check for users who pasted the example code but didn't add an API key
check_local_llm_setup Check Local LLM Setup
embeddings.gpt5.4.example GPT-5.4 Example Item Embeddings
embedding_matrix_validate_GENIE Validate Embedding Matrix for GENIE
ensure_aigenie_python Ensure AI-GENIE Python Environment is Ready
final_community_detection Run Final Community Detection with EGA
GENIE The use of the psychometric reduction component of AIGENIE on your pre-existing item pool
get_local_llm Download a Local LLM Model
install_gpu_support Install GPU Support for AI-GENIE
install_local_llm_support Install Local LLM Support
item.examples_validate Validate and Clean 'item.examples' Against Cleaned 'items.attributes'
item.type.definitions_validate Validate and Clean 'item.type.definitions'
items.attributes_validate Validate 'items.attributes'
items.gpt5.4.example GPT-5.4 Example Item Pool
items_validate_GENIE Validate Items Data Frame for GENIE
iterative_stability_check Iteratively run BootEGA to ensure structural stability of items
list_available_models List Available Models
local_AIGENIE Generate and Validate Psychometric Scale Items Using Local Models
local_chat Chat with a local LLM (no API calls)
local_GENIE Local Generative Network-Integrated Evaluation (local_GENIE)
main.prompts_validate Validate and Normalize 'main.prompts'
max.tokens_validate Check that max.tokens is an integer
plot_comparison Plot Comparisons
plot_stability_comparison Plot Stability Comparison (network + item stability dotplot, side by side)
print_results Print Results
python_env_info Get AI-GENIE Python Environment Info
reduce_redundancy_uva Reduce Redundancy via Iterative UVA (with Redundant Pair Logging)
reinstall_python_env Reinstall AI-GENIE Python Environment
resolve_model_name Resolve and Normalize Model Name
response.options_validate Validate and Clean 'response.options'
run_flags_validate Check that the 'run.overall' and 'all.together' flags are logically consistent with the number of item types.
run_item_reduction_pipeline Run reduction pipeline for all item types
run_pipeline_for_item_type Run full pipeline for a single item type
select_optimal_embedding Select Optimal Embedding and EGA Model Based on NMI
set_huggingface_token Set Hugging Face Token
sparsify_embeddings Sparsify Embedding Matrix
target.N_validate Validate and Expand 'target.N' for Each Item Attribute
temperature_validate Validate 'temperature' for Text Generation
top.p_validate Validate 'top.p' for Text Generation
uva.cut.off_validate Validate 'uva.cut.off'
validate_booleans Validate Boolean Arguments
validate_ega_params Validate EGA Parameters
validate_local_embedding_model Validate Local Embedding Model
validate_local_embedding_params Validate Local Embedding Parameters
validate_local_llm_params Validate Local LLM Generation Parameters
validate_model.path Validate Local Model Path
validate_prompt.notes Validate and Normalize 'prompt.notes'
validate_reps Check that reps is an integer
validate_strings Validate That Inputs Are Strings
validate_system.role_prompts Checks 'system.role' and 'prompts' for the 'chat' function
validate_user_input_AIGENIE Validate All User Inputs for AI-GENIE
validate_user_input_GENIE Validate All User Inputs for GENIE
validate_user_input_local_AIGENIE Validate All User Inputs for Local AI-GENIE
validate_user_input_local_GENIE Validate All User Inputs for Local GENIE