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import streamlit as st
import torch
from sentence_transformers import SentenceTransformer, util
embedder = SentenceTransformer('all-mpnet-base-v2')
st.title("iSeBetter: Semantic Issue Transformer")
st.caption("Empower Developers with Advanced AI Issue Resolution")
st.markdown('#')
st.subheader("Search for Similar Issues")
form = st.form("Search for Similar Issues")
text_input = form.text_area("Please enter the issue details",
help="Title and description of the issue could be a good start!")
if form.form_submit_button("Run Inference"):
# Perform semantic search
query_embedding = embedder.encode(text_input, convert_to_tensor=True)
corpus_embeddings = torch.load('saved_corpus.pt')
corpus_embeddings_name = torch.load('saved_corpus_list.txt')
cos_scores = util.cos_sim(query_embedding, corpus_embeddings)[0]
top_results = torch.topk(cos_scores, k=5)
st.markdown('#')
# Display results
st.subheader("Top 5 Similar Issues")
for score, idx in zip(top_results[0], top_results[1]):
st.progress(score.item(), f"Issue: {corpus_embeddings_name[idx]}, Score: {score:.4f}")
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