Update agent.py

agent.py

@@ -410,11 +410,18 @@ docs = [
 ]
 
 
+# Now extract texts
+texts = [doc.page_content for doc in docs]
+
+# Generate embeddings
+embeddings = [embedding_model.encode(text) for text in texts]
+
+
 # Initialize the embedding model
-embedding_model = BERTEmbeddings()
+#embedding_model = BERTEmbeddings()
 
 # Generate embeddings for each document
-embeddings = [embedding_model.encode(text) for text in texts]
+#embeddings = [embedding_model.encode(text) for text in texts]
 
 # Create the FAISS index
 vector_store = FAISS.from_documents(docs, embedding_model)