Update app.py

app.py

@@ -29,6 +29,17 @@ def method_get_text_chunks(text):
     text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=100)
     doc_splits = text_splitter.split_documents(text)
     return doc_splits
+
+def method_get_vectorstore(document_chunks):
+    #convert text chunks into embeddings and store in vector database
+
+    # create the open-source embedding function
+    #embeddings = NomicEmbeddings(model="nomic-embed-text-v1.5")
+    embeddings = HuggingFaceEmbeddings()
+
+    # create a vectorstore from the chunks
+    vector_store = Chroma.from_documents(document_chunks, embeddings)
+    return vector_store
     
 def get_context_retriever_chain(vector_store,question):
     # Initialize the retriever