Spaces:
Running
Running
import pickle | |
from config import ( | |
MODEL_NAME, | |
SENTENCE_EMBEDDING_FILE, | |
STANDARD_NAME_MAP_DATA_FILE, SUBJECT_DATA_FILE | |
) | |
from sentence_transformer_lib.sentence_transformer_helper import SentenceTransformerHelper | |
from data_lib.subject_data import SubjectData | |
from data_lib.standard_name_map_data import StandardNameMapData | |
class SentenceTransformerService: | |
def __init__(self): | |
self.sentenceTransformerHelper = None | |
self.dic_standard_subject = None | |
self.anchor_name_sentence_embeddings = None | |
self.sampleData = None | |
def load_model_data(self): | |
"""Load model and data only once at startup""" | |
if self.sentenceTransformerHelper is not None: | |
print("Model already loaded. Skipping reload.") | |
return # Kh么ng load l岷 n岷縰 膽茫 c贸 model | |
print("Loading models and data...") | |
# Load sentence transformer model | |
self.sentenceTransformerHelper = SentenceTransformerHelper( | |
convert_to_zenkaku_flag=True, replace_words=None, keywords=None | |
) | |
self.sentenceTransformerHelper.load_model_by_name(MODEL_NAME) | |
# Load standard subject dictionary | |
self.dic_standard_subject = SubjectData.create_standard_subject_dic_from_file(SUBJECT_DATA_FILE) | |
# Load pre-computed embeddings and similarities | |
with open(SENTENCE_EMBEDDING_FILE, "rb") as f: | |
self.anchor_name_sentence_embeddings = pickle.load(f) | |
# Load and process sample data | |
self.standardNameMapData = StandardNameMapData() | |
self.standardNameMapData.load_data_from_csv(STANDARD_NAME_MAP_DATA_FILE) | |
self.standardNameMapData.process_data(self.anchor_name_sentence_embeddings) | |
print("Models and data loaded successfully") | |
# Global instance (singleton) | |
sentence_transformer_service = SentenceTransformerService() | |