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import pandas as pd | |
import streamlit as st | |
from utils import get_similar_questions_with_score | |
LOGO_PATH = 'img/logo.jpg' | |
st.image(LOGO_PATH, width=200) | |
st.title('SF Seeker') | |
st.markdown(""" | |
Sci-Fi Stack Exchange Seeker (aka SF Seeker) is an AI assistant that helps you write better questions and search for | |
semantically similar questions on Sci-Fi Stack Exchange (https://scifi.stackexchange.com/). An all-MiniLM-L6-v2 | |
language model (transformer) was used. | |
**Features** | |
- π Based on a database of 71,013 questions, it searches for the most semantically similar questions to the one entered | |
by the user. This supports the process of fiding the same/similar questions already asked and prevents the creation of | |
duplicate threads. | |
- π¨ββοΈ [IN PROGRESS] Indicates words in a question that have a negative and positive effect on the chance of | |
getting an answer. It supports the process of arranging more precise questions. A model based on gradient | |
reinforcement learned using TF-IDF features was used. | |
""") | |
question_input = st.text_area('Question') | |
k_similar_questions = st.number_input('k similar questions', min_value=1, max_value=100, value=5, step=1) | |
if st.button('Submit'): | |
if not question_input: | |
st.warning('β οΈ No question inputted!') | |
else: | |
question_score_results = get_similar_questions_with_score(question_input, k_similar_questions) | |
question_score_results_df = pd.DataFrame(question_score_results) | |
question_score_results_df.columns = ['Question', 'Similarity score (in %)'] | |
st.dataframe(question_score_results_df) | |