app.py

# AnjiBot 🤖
### Computer Science Course Representative (Chatbot)

from transformers import pipeline
import pandas as pd
import gradio as gr
import tensorflow_probability

# Load TAPAS model and table
tqa = pipeline(task="table-question-answering", model="google/tapas-base-finetuned-sqa")
table = pd.read_csv('CSLECTURERS.csv', delimiter="::")
table = table.astype('str')

messages = []
responses = []

def anjibot(message, history):
    messages.append(message)
    conversation = {"text": message, "past_user_input": messages, "generated_responses": responses}
    answer = tqa(table=table, query=message)["answer"]
    responses.append(answer)
    return "AnjiBot: " + answer

demo_chatbot = gr.ChatInterface(anjibot, title='AnjiBot', description="Anji is unavailable? That girl! Ask me, I may know!")
demo_chatbot.launch()