app.py

from flask import Flask, render_template, request, jsonify
import numpy as np
import faiss
from sentence_transformers import SentenceTransformer
import os
import numpy as np


app = Flask(__name__)

# Create a cache directory if it doesn't exist
#cache_dir = '/code/cache'  # Or another suitable location
#os.makedirs(cache_dir, exist_ok=True)



indexIVFPQ = faiss.read_index("indexIVFPQ .index")

from sentence_transformers import SentenceTransformer
model = SentenceTransformer('bert-base-nli-mean-tokens')

import json
with open('wiki_entries.json') as json_file:
    data = json.load(json_file)
lines=[]
for key in data:
    #print(key)
    doc=data[key]
    for k in doc:
        lines.append(doc[k])


@app.route('/')
def home():
    return render_template('index.html')

@app.route('/search', methods=['POST'])
def search():
    query = request.form['query']

    if not query:
        return render_template('index.html', error='Query is required')
    k = 10
    xq = model.encode([query])
    D, I = indexIVFPQ .search(xq, k) 
    line=[]
    for i in I[0]:
    	sen=lines[i]
    	line.append(sen)
    return render_template('index.html', query=query, top_n_docs=line)

if __name__ == '__main__':
    app.run(debug=True)