app.py

import streamlit as st
import requests
import redis
import psycopg2

# Redis Connection
redis_client = redis.Redis(host='redis-19703.c289.us-west-1-2.ec2.redns.redis-cloud.com', port=19703, db=0, decode_responses=True)

# PostgreSQL Connection
conn = psycopg2.connect(database="screening_db", user="user", password="password", host="localhost", port="5432")
cursor = conn.cursor()

HF_API_URL = "https://api-inference.huggingface.co/models/your-hf-model-id"

st.title("AI Candidate Screening")

resume_text = st.text_area("Paste Candidate Resume")

if st.button("Analyze Resume"):
    cache_key = f"resume:{resume_text[:20]}"  # Hash first 20 chars
    cached_response = redis_client.get(cache_key)
    
    if cached_response:
        st.write("Cached Response:", cached_response)
    else:
        response = requests.post(HF_API_URL, json={"inputs": resume_text}).json()
        redis_client.set(cache_key, response, ex=3600)  # Cache for 1 hour
        
        # Store result in PostgreSQL
        cursor.execute("INSERT INTO screenings (resume_text, result) VALUES (%s, %s)", (resume_text, response))
        conn.commit()

        st.write("AI Response:", response)