Update app.py

app.py

@@ -42,7 +42,8 @@ retriever_tokenizer = AutoTokenizer.from_pretrained(retriever_model_name)
 
 # Initialize FAISS index using LangChain
 embedding_dimension = embedding_model.get_sentence_embedding_dimension()
-faiss_index = FAISS(HuggingFaceEmbeddings(embedding_model), dimension=embedding_dimension)
+hf_embeddings = HuggingFaceEmbeddings(model_name='sentence-transformers/all-MiniLM-L6-v2')
+faiss_index = FAISS(embedding_function=hf_embeddings, dimension=embedding_dimension)
 
 # Load or create FAISS index
 index_path = "faiss_index.pkl"
@@ -131,6 +132,3 @@ with gr.Blocks() as demo:
         query_button.click(fn=process_and_query, inputs=[query], outputs=query_output)
 
 demo.launch()
-
-
-