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")
    
    global_tech, global_tech_embeddings = load_technologies()
    
    #global_tech, keys, original_tech = preprocess_tech_data(df)
    
    save_dataframe(global_tech, "global_tech.xlsx")
    
    result_similarities, matrix = get_contrastive_similarities(constraints_stemmed, global_tech, global_tech_embeddings, )
    
    save_to_pickle(result_similarities)
    
    print(f"Matrix : {matrix} \n Constraints : {constraints_stemmed} \n Gloabl tech : {global_tech}")
    
    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