Update app.py

app.py

@@ -15,18 +15,19 @@ import pinecone
 import streamlit as st
 import shutil
 
+
 OPENAI_API_KEY = ''
 PINECONE_API_KEY = ''
 PINECONE_API_ENV = ''
 pinecone_index_name = ''
 chroma_collection_name = ''
 persist_directory = ''
-chat_history = []
 docsearch_ready = False
 directory_name = 'tmp_docs'
 langchain.verbose = False
 
 
+@st.cache_data()
 def save_file(files):
     # Remove existing files in the directory
     if os.path.exists(directory_name):
@@ -46,6 +47,7 @@ def save_file(files):
                 shutil.copyfileobj(file, f)
 
 
+@st.cache_data()
 def load_files():
     all_texts = []
     n_files = 0
@@ -76,13 +78,14 @@ def load_files():
     return all_texts, n_texts
 
 
-def ingest(all_texts, use_pinecone, embeddings, pinecone_index_name, chroma_collection_name, persist_directory):
+@st.cache_resource()
+def ingest(_all_texts, use_pinecone, _embeddings, pinecone_index_name, chroma_collection_name, persist_directory):
     if use_pinecone:
         docsearch = Pinecone.from_texts(
-            [t.page_content for t in all_texts], embeddings, index_name=pinecone_index_name)  # add namespace=pinecone_namespace if provided
+            [t.page_content for t in _all_texts], _embeddings, index_name=pinecone_index_name)  # add namespace=pinecone_namespace if provided
     else:
         docsearch = Chroma.from_documents(
-            all_texts, embeddings, collection_name=chroma_collection_name, persist_directory=persist_directory)
+            _all_texts, _embeddings, collection_name=chroma_collection_name, persist_directory=persist_directory)
     return docsearch
 
 
@@ -165,6 +168,7 @@ with col3:
             persist_directory = "./vectorstore"
 
 if pinecone_index_name or chroma_collection_name:
+    chat_history = []
     if r_ingest.lower() == 'yes':
         files = st.file_uploader('Upload Files', accept_multiple_files=True)
         if files:
@@ -188,7 +192,8 @@ if docsearch_ready:
 
     st.title('Chatbot')
     # Get user input
-    query = st.text_input('Enter your question; enter "exit" to exit')
+    query = st.text_area('Enter your question:', height=10,
+                         placeholder='Summarize the context.')
     if query:
         # Generate a reply based on the user input and chat history
         reply, source = get_response(query, chat_history)