| from src.services.utils import * | |
| from src.services.processor import * | |
| def process_input(data): | |
| prompt = set_prompt(data.problem) | |
| constraints = retrieve_constraints(prompt) | |
| constraints_stemmed = stem(constraints, "constraints") | |
| save_dataframe(constraints_stemmed, "constraints_stemmed.xlsx") | |
| df = load_technologies() | |
| global_tech, keys, original_tech = preprocess_tech_data(df) | |
| save_dataframe(global_tech, "global_tech.xlsx") | |
| result_similarities, matrix = get_contrastive_similarities(global_tech, constraints_stemmed) | |
| save_to_pickle(result_similarities) | |
| best_combinations = find_best_list_combinations(constraints_stemmed,global_tech, matrix) | |
| best_technologies_id = select_technologies(best_combinations) | |
| best_technologies = get_technologies_by_id(best_technologies_id,global_tech) | |
| return best_technologies |