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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 |