| from src.services.utils import * | |
| from src.services.processor import * | |
| dataset = load_data() | |
| def process_input(data, dataset, data_type): | |
| if data_type == "problem": | |
| prompt = set_prompt(data.problem) | |
| constraints = retrieve_constraints(prompt) | |
| elif data_type == "constraints": | |
| constraints = data | |
| constraints_stemmed = stem(constraints, "constraints") | |
| result_similarities, matrix = get_contrastive_similarities(constraints_stemmed, dataset) | |
| save_to_pickle(result_similarities) | |
| best_combinations = find_best_list_combinations(constraints_stemmed, dataset, matrix) | |
| best_technologies_id = select_technologies(best_combinations) | |
| best_technologies = get_technologies_by_id(best_technologies_id, dataset) | |
| return best_technologies | |
| def process_prior_art(technologies, data, data_type, techno_type): | |
| try: | |
| prior_art_reponse = search_prior_art(technologies, data, data_type, techno_type) | |
| prior_art_search = add_citations_and_collect_uris(prior_art_reponse) | |
| except Exception as e: | |
| print(f"An error occured during the process, trying again : {e}") | |
| prior_art_reponse = search_prior_art(technologies, data, data_type, techno_type) | |
| prior_art_search = add_citations_and_collect_uris(prior_art_reponse) | |
| print("PRIOR ART SEARCH") | |
| print(prior_art_reponse) | |
| print(prior_art_search) | |
| return prior_art_search |