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 💡")

    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 ytangch@connect.ust.hk")
 
if __name__ == "__main__":
    main()