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import streamlit as st | |
import pandas as pd | |
from streamlit_gsheets import GSheetsConnection | |
def load_data(): | |
GSheetsConnection = "https://docs.google.com/spreadsheets/d/1Ui9gZoSKxSIW0B7fG8ryuN0nhkVhAckFxl2hWf6CaJQ/edit?usp=sharing" | |
conn = st.connection("gsheets", type=GSheetsConnection) | |
df = conn.read() | |
return df | |
def case_insensitive_search(data, query, column): | |
if query: | |
return data[data[column].str.lower().str.contains(query.lower())] | |
return data | |
def display_table(data, rows_per_page=10): | |
container = st.container() | |
with container: | |
height = min(40 + rows_per_page * 38, 800) | |
st.dataframe(data, height=height) | |
def main(): | |
st.title("Multihop-RAG Benchmark π‘") | |
data = load_data() | |
st.sidebar.header("Search Options") | |
chat_model_query = st.sidebar.text_input("Chat Model") | |
embedding_model_query = st.sidebar.text_input("Embedding Model") | |
chunk_query = st.sidebar.text_input("Chunk") | |
frame_query = st.sidebar.text_input("Framework") | |
if chat_model_query: | |
data = case_insensitive_search(data, chat_model_query, 'chat_model') | |
if embedding_model_query: | |
data = case_insensitive_search(data, embedding_model_query, 'embedding_model') | |
if chunk_query: | |
data = case_insensitive_search(data, chunk_query, 'chunk') | |
if frame_query: | |
data = case_insensitive_search(data, frame_query, 'framework') | |
st.write("Displaying results across different frameworks, embedding models, chat models, and chunks.") | |
st.info("Retrieval Stage: MRR@10 and Hit@10; Response Stage: Accuracy ") | |
display_table(data) | |
st.sidebar.header("Citation") | |
st.sidebar.info( | |
"Please cite this dataset as:\n" | |
"Tang, Yixuan, and Yi Yang. MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop Queries. ArXiv, 2024, /abs/2401.15391." | |
) | |
st.markdown("---") | |
st.caption("For citation, please use: 'Tang, Yixuan, and Yi Yang. MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop Queries. ArXiv, 2024, /abs/2401.15391. '") | |
st.markdown("---") | |
st.caption("For results self-reporting, please send an email to [email protected]") | |
if __name__ == "__main__": | |
main() |