added option to use hypothetical embeddings, added "compare" page to streamlit app, compare performance of hypothetical vs normal embeddings

main.py

@@ -68,6 +68,7 @@ def chat():
     dir_or_doc = st.radio('Select a chat method', ('Document', 'Directory'))
     st.title('Chat')
     model_name = st.radio('Select a model', ('gpt-3.5-turbo', 'gpt-4'))
+    hypothetical = st.checkbox('Use hypothetical embeddings', value=False)
     if dir_or_doc == 'Document':
         if 'text_input' not in st.session_state:
             st.session_state.text_input = ''
@@ -111,7 +112,7 @@ def chat():
     user_input = st.text_input('Enter your question', key='text_input')
 
     if st.button('Ask') and 'db' in st.session_state and validate_api_key(model_name):
-        answer = generate_answer(st.session_state.db, model_name)
+        answer = generate_answer(st.session_state.db, model_name, hypothetical)
 
     if 'history' not in st.session_state:
         st.session_state.history = []
@@ -137,17 +138,66 @@ def documents():
         st.write('No documents found in documents folder. Add some documents first!')
 
 
+def compare_results():
+    st.title('Compare')
+    st.write("Compare retrieval results using hypothetical embeddings vs. normal embeddings. Support for comparing multiple models coming soon.")
+    model_name = 'gpt-3.5-turbo'
+
+    if 'text_input' not in st.session_state:
+        st.session_state.text_input = ''
+    directory = 'documents'
+    files = os.listdir(directory)
+    files = [file for file in files if file.endswith(tuple(accepted_filetypes))]
+    selected_file = st.selectbox('Select a file', files)
+    st.write('You selected: ' + selected_file)
+    selected_file_path = os.path.join(directory, selected_file)
+
+    if st.button('Load file (first time might take a second...) pressing this button will reset the chat history'):
+        db = load_db_from_file_and_create_if_not_exists(selected_file_path)
+        st.session_state.db = db
+        st.session_state.history = []
+
+
+
+
+    user_input = st.text_input('Enter your question', key='text_input')
+
+    if st.button('Ask') and 'db' in st.session_state and validate_api_key(model_name):
+        st.markdown('Question: ' + user_input)
+        answer_a, sources_a = generate_answer(st.session_state.db, model_name, hypothetical=True)
+        answer_b, sources_b = generate_answer(st.session_state.db, model_name, hypothetical=False)
+
+        col1, col2 = st.columns(2)
+
+        with col1:
+            st.header('Hypothetical embeddings')
+            st.markdown(answer_a)
+            with st.expander('Sources', expanded=False):
+                st.markdown(sources_a)
+        with col2:
+            st.header('Normal embeddings')
+            st.markdown(answer_b)
+            with st.expander('Sources', expanded=False):
+                st.markdown(sources_b)
+
+        st.session_state.history = []
+        st.session_state.sources = []
+
+
+
 
 PAGES = {
     "Chat": chat,
     "Summarize": summarize,
     "Documents": documents,
+    "Compare": compare_results
 }
 
 st.sidebar.title("Navigation")
 selection = st.sidebar.radio("Go to", list(PAGES.keys()))
 st.sidebar.markdown(' [Contact author](mailto:ethanujohnston@gmail.com)')
 st.sidebar.markdown(' [Github](https://github.com/e-johnstonn/docGPT)')
+st.sidebar.markdown('[More info on hypothetical embeddings here](https://arxiv.org/abs/2212.10496)', unsafe_allow_html=True)
 page = PAGES[selection]
 page()