Update app.py

app.py

@@ -1,16 +1,22 @@
 from langchain.embeddings import HuggingFaceInstructEmbeddings
 from langchain.text_splitter import CharacterTextSplitter
 from langchain.vectorstores import Chroma
+import streamlit as st
+
+text = st.'enter some text to start'
 
 full_text = open("state_of_the_union.txt", "r").read()
 text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=100)
 texts = text_splitter.split_text(full_text)
 
-embeddings = HuggingFaceInstructEmbeddings(model_name="hkunlp/instructor-xl")
+embeddings = HuggingFaceInstructEmbeddings(model_name="hkunlp/instructor-base")
 db = Chroma.from_texts(texts, embeddings)
 retriever = db.as_retriever()
 
 retrieved_docs = retriever.invoke(
-    "What did the president say about Ketanji Brown Jackson?"
+    text
 )
-print(retrieved_docs[0].page_content
+
+if text: 
+    st.json(retrieved_docs)
+