Update app.py

app.py

@@ -80,8 +80,11 @@ def create_vector_store(text):
     # Generate embeddings for cleaned sentences
     embeddings = [embed(sentence)[0] for sentence in sentences]
 
+    # Convert embeddings to a numpy array
+    embeddings = np.array(embeddings, dtype=np.float32)
+
     # Create a FAISS vector store with valid embeddings
-    vector_store = FAISS.from_embeddings(sentences, embeddings)
+    vector_store = FAISS.from_texts(texts=sentences, embedding_function=lambda x: embeddings)
     return vector_store, sentences
 
 # Streamlit app