app.py

import streamlit as st
import pandas as pd

def display_csv(file_path):
    # Load the CSV file using pandas
    df = pd.read_csv(file_path)
    # Display the dataframe as a table
    st.write(df, height=500, width=1000)  # Adjust height and width as needed

def main():
    # Hardcoded file path
    file_path = "merged-averaged-model_timings_2.1.0_12.1_NVIDIA_A10G_False.csv"
    
    # Add a text caption
    st.header("CLIP benchmarks - retrieval and inference")
    st.write("CLIP benchmarks for inference and retrieval performance. Image size, context length and output dimensions are also presented. A10G, CUDA 12.1, Torch 2.1.0")

    # Call the display_csv function with the hardcoded file path
    display_csv(file_path)

if __name__ == "__main__":
    main()