Update app.py

app.py

@@ -47,12 +47,19 @@ combined_documents = recursive_framework_document + recursive_blueprint_document
 #embeddings = AutoModel.from_pretrained("Cheselle/finetuned-arctic-sentence")
 #tokenizer = AutoTokenizer.from_pretrained("Cheselle/finetuned-arctic-sentence")
 
-ai_framework_text = ai_framework_document.get_text("text")
-ai_blueprint_text = ai_blueprint_document.get_text("text")
+# Assuming ai_framework_document is a list of documents or pages
+ai_framework_text = "".join([doc.get_text("text") for doc in ai_framework_document])
+
+# Similarly for ai_blueprint_document
+ai_blueprint_text = "".join([doc.get_text("text") for doc in ai_blueprint_document])
+
+# Now you can use these text variables
+embeddings = embedding_model.encode(ai_framework_text + ai_blueprint_text)
+
 
 from sentence_transformers import SentenceTransformer
 embedding_model = SentenceTransformer("Cheselle/finetuned-arctic-sentence")
-embeddings = embedding_model.encode(ai_framework_text + ai_blueprint_text)
+#embeddings = embedding_model.encode(ai_framework_text + ai_blueprint_text)
 #embeddings = embedding_model.encode(ai_framework_document + ai_blueprint_document)
 
 vectorstore = Qdrant.from_documents(