Update app.py

app.py

@@ -4,12 +4,9 @@ import py_vncorenlp
 import os
 
 app = Flask(__name__)
-save_dir_vncore = os.path.join(os.path.dirname(os.path.abspath(__file__)), "reranking", "vncorenlp01")
-py_vncorenlp.download_model(save_dir=save_dir_vncore)
+save_dir_vncore = "/home/user/app/reranking/vncorenlp"
 rdrsegmenter = py_vncorenlp.VnCoreNLP(annotators=["wseg"], save_dir=save_dir_vncore)
 
-# Initialize vncorenlp with the JAR file path
-word_segmenter = py_vncorenlp.VnCoreNLP(vncorenlp_path, annotators=["wseg"])
 
 # Load your cross-encoder model
 model_name = "truong1301/reranker_pho_BLAI"  # Replace with your actual model if different
@@ -19,7 +16,7 @@ cross_encoder = CrossEncoder(model_name, max_length=256, num_labels=1)
 def preprocess_text(text):
     if not text:
         return text
-    segmented_text = word_segmenter.word_segment(text)
+    segmented_text = rdrsegmenter.word_segment(text)
     # Join tokenized sentences into a single string
     return " ".join([" ".join(sentence) for sentence in segmented_text])