Update app.py

app.py

@@ -5,12 +5,19 @@ import os
 
 app = Flask(__name__)
 
-# Initialize vncorenlp (point to the JAR file in your folder)
-current_dir = 'reranking/vncorenlp'
-word_segmenter = py_vncorenlp.VnCoreNLP(save_dir=current_dir, annotators=["wseg"])
+# Set the path to the VnCoreNLP JAR file
+current_dir = os.path.dirname(os.path.abspath(__file__))  # Get the directory of app.py
+vncorenlp_path = os.path.join(current_dir, "vncorenlp", "VnCoreNLP-1.2.jar")
 
-# Load your cross-encoder model (replace with your model name or path)
-model_name = "truong1301/reranker_pho_BLAI"  # Example model, replace with yours
+# Check if the JAR file exists (for debugging)
+if not os.path.exists(vncorenlp_path):
+    raise FileNotFoundError(f"VnCoreNLP JAR file not found at {vncorenlp_path}. Please ensure 'vncorenlp/VnCoreNLP-1.2.jar' is in the root directory.")
+
+# 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
 cross_encoder = CrossEncoder(model_name, max_length=256, num_labels=1)
 
 # Function to preprocess text with Vietnamese word segmentation