Update app.py

app.py

@@ -9,16 +9,14 @@ import numpy as np
 index_path = "faiss_index/index.faiss"  # Update with your FAISS index file path
 index = faiss.read_index(index_path)
 
-# Load your embeddings model
-embedding_model = SentenceTransformer("BAAI/bge-large-en-v1.5")
 
 # Load the metadata
 df = pd.read_pickle('df_news (1).pkl')
 
 # Load the Hugging Face model and tokenizer
-hf_model_name = "gpt-2"  # Replace with your desired Hugging Face model
-hf_model = AutoModelForCausalLM.from_pretrained(hf_model_name)
-hf_tokenizer = AutoTokenizer.from_pretrained(hf_model_name)
+model = SentenceTransformer("sentence-transformers/all-mpnet-base-v2")
+hf_tokenizer = AutoTokenizer.from_pretrained('BAAI/bge-large-zh-v1.5')
+hf_model = AutoModel.from_pretrained('BAAI/bge-large-zh-v1.5')
 
 # Define the function for similarity search
 def search(query, k=10):