RAGSystem / app.py
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import gradio as gr
import pandas as pd
from chatbot.bot import QuestionAnsweringBot
import os
current_dir = os.path.dirname(os.path.abspath(__file__))
data_path = os.path.join(current_dir, 'data', 'chunked_data_corpus.csv')
chunked_data_corpus_df = pd.read_csv(data_path)
bot = QuestionAnsweringBot(chunked_data_corpus_df)
def message_respond(message, history):
answer = bot.form_response(message)
return answer
gr.ChatInterface(
fn=message_respond,
type="messages",
title="RAG System for 'The Count of Monte Cristo' book",
description="Here you can ask any questions in the context of the book 'The Count of Monte Cristo'. API key is already provided.",
theme=gr.themes.Monochrome(font='Lora', text_size='lg', radius_size='sm'),
examples=["Who is Monte Cristo?",
"What is the title of Chapter 93",
"Why Edmond Dantes was in prison?",
"How many years does Edmon Dantes spent in prison?",
"Who said this sentence to whom 'Wait and hope_ (Fac et spera)'?",
"What is the title of Chapter 64?",
"Who is the president of the USA?",
"Who is the author of the book The Count of Monte Cristo?",
"Tell me about all the main identites in Monte Cristo?"
],
cache_examples=False,
).launch()