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

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ethan
2023-05-31 18:05:29 -07:00
parent 10d9d91210
commit 46938d8959
1 changed files with 51 additions and 1 deletions
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52
main.py
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@@ -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()