Package index • nalanda

All functions

compute_run_ai_metrics(): Compute derived pre/post effect metrics from raw turn-level output
compute_run_ai_metrics_cumulative(): Compute cumulative chapter metrics against the original baseline
compute_run_ai_metrics_one_turn(): Compute one-turn ingroup/outgroup metrics from raw output
evaluate_text_analysis(): Evaluate text-analysis outputs against reference labels
fix_text_file(): Fix text file encoding and normalize punctuation/whitespace
list_book_chapters(): List book chapter files inside a books directory
make_annotation_prompt(): Build a numeric-response prompt for text analysis
make_baseline_prompt(): Build the baseline (Turn 1) prompt
make_post_prompt(): Build the post-intervention (Turn 2) prompt
make_treatment_prompt() build_simulate_treatment_prompt(): Build a concrete prompt for simulate_treatment()
nalanda(): A Random Historical Fact About Nalanda University
plot_chapter_scores_faceted(): Faceted plot of chapter scores
plot_chapter_trajectories(): Plot chapter trajectories by book
plot_chapters_over_time(): Plot chapters over time (multi-timepoint means)
plot_chapters_over_time_one_turn(): Plot chapter trajectories for one-turn simulations
plot_forest_books(): Create a forest plot of book-level polarization reduction effects
prepare_forest_books(): Prepare book-level data for forest plotting
rank_weighted(): Rank rows using a weighted rubric
read_book_texts(): Read book chapters into a nested list
rename_chapters(): Rename chapter text files in a folder to a sequential order
run_ai_cumulative_chapters(): Run AI model on books with cumulative chapter context
run_ai_on_chapters(): Run AI model on book chapters and collect structured responses
run_ai_on_chapters_one_turn(): Run AI model on book chapters with a single prompt per simulation
run_text_analysis(): Run row-wise text analysis with a prompt template
save_forest_plot(): Save a forest plot to PNG and PDF formats
simulate_treatment(): Simulate a generic multi-turn treatment workflow
summarize_chapter_scores(): Summarize simulated chapter scores
summarize_treatment_results(): Summarize generic treatment results
toy_run_ai_turns: Toy raw turn-level AI simulation output
toy_sim_results: Toy simulated chapter results