app.py

import gradio as gr
import pandas as pd
from retrieval import *
import os


hf_writer = gr.HuggingFaceDatasetSaver('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', "Pavankalyan/chitti_data")

df = pd.read_csv("Responses.csv")
text = list(df["text"].values)


def chitti(query):
    re_table = search(query, text)
    with open(query[0:5]+'.txt', 'w') as f:
        f.writelines(["Question: "+query,"Ans 1 : "+ re_table[0][0],"Ans 2 : "+ re_table[1][0]])
    return [re_table[0][0],re_table[1][0]]

demo = gr.Interface(
    fn=chitti,
    inputs=["text"],
    outputs=["text","text"],
    allow_flagging = "manual",
    flagging_options = ["0","1","None"],
    flagging_callback=hf_writer
)
demo.launch()