app.py

# app.py
import streamlit as st
import requests
import spacy
from PyPDF2 import PdfReader
from io import BytesIO
import json
import os
import pandas as pd

# Load spaCy model
nlp = spacy.load("en_core_web_sm")

# App Title
st.set_page_config(page_title="AI-Powered Resume Analyzer & Job Adviser", layout="wide")

st.title("💼 AI-Powered Resume Analyzer & Job Adviser")

# Tabs for Candidate and HR
tab1, tab2 = st.tabs(["Candidate", "HR Recruiter"])

# Set your GROQ API details
groq_api_url = "https://api.groq.com/openai/v1/chat/completions"
groq_api_key = os.getenv("wbm2")  # Add this in Hugging Face secrets

# Function to call GROQ LLM
def get_ai_response(prompt):
    headers = {
        "Authorization": f"Bearer {groq_api_key}",
        "Content-Type": "application/json"
    }
    payload = {
        "model": "llama3-70b-8192",
        "messages": [
            {"role": "system", "content": "You are an AI-powered job advisor and resume analyzer."},
            {"role": "user", "content": prompt}
        ]
    }
    response = requests.post(groq_api_url, headers=headers, json=payload)
    try:
        response.raise_for_status()
        data = response.json()
        if 'choices' in data:
            return data['choices'][0]['message']['content']
        else:
            st.error("Unexpected response format from Groq API.")
            st.json(data)
            return "Error: Invalid API response format."
    except requests.exceptions.RequestException as e:
        st.error(f"Request failed: {e}")
        return "Error: Unable to fetch response from the AI model."

# Extract text from PDF resume
def extract_resume_text(uploaded_file):
    reader = PdfReader(uploaded_file)
    resume_text = ""
    for page in reader.pages:
        resume_text += page.extract_text()
    return resume_text

# Country and Experience Inputs
country_list = sorted([
    "Afghanistan", "Albania", "Algeria", "Andorra", "Angola", "Antigua and Barbuda", "Argentina", "Armenia",
    "Australia", "Austria", "Azerbaijan", "Bahamas", "Bahrain", "Bangladesh", "Barbados", "Belarus", "Belgium",
    "Belize", "Benin", "Bhutan", "Bolivia", "Bosnia and Herzegovina", "Botswana", "Brazil", "Brunei", "Bulgaria",
    "Burkina Faso", "Burundi", "Cabo Verde", "Cambodia", "Cameroon", "Canada", "Central African Republic", "Chad",
    "Chile", "China", "Colombia", "Comoros", "Congo (Congo-Brazzaville)", "Costa Rica", "Croatia", "Cuba", "Cyprus",
    "Czech Republic", "Democratic Republic of the Congo", "Denmark", "Djibouti", "Dominica",
    "Dominican Republic", "Ecuador", "Egypt", "El Salvador", "Equatorial Guinea", "Eritrea", "Estonia", "Eswatini",
    "Ethiopia", "Fiji", "Finland", "France", "Gabon", "Gambia", "Georgia", "Germany", "Ghana", "Greece", "Grenada",
    "Guatemala", "Guinea", "Guinea-Bissau", "Guyana", "Haiti", "Honduras", "Hungary", "Iceland", "India",
    "Indonesia", "Iran", "Iraq", "Ireland", "Israel", "Italy", "Jamaica", "Japan", "Jordan", "Kazakhstan", "Kenya",
    "Kiribati", "Kuwait", "Kyrgyzstan", "Laos", "Latvia", "Lebanon", "Lesotho", "Liberia", "Libya", "Liechtenstein",
    "Lithuania", "Luxembourg", "Madagascar", "Malawi", "Malaysia", "Maldives", "Mali", "Malta",
    "Marshall Islands", "Mauritania", "Mauritius", "Mexico", "Micronesia", "Moldova", "Monaco", "Mongolia",
    "Montenegro", "Morocco", "Mozambique", "Myanmar (Burma)", "Namibia", "Nauru", "Nepal", "Netherlands",
    "New Zealand", "Nicaragua", "Niger", "Nigeria", "North Korea", "North Macedonia", "Norway", "Oman",
    "Pakistan", "Palau", "Palestine State", "Panama", "Papua New Guinea", "Paraguay", "Peru", "Philippines",
    "Poland", "Portugal", "Qatar", "Romania", "Russia", "Rwanda", "Saint Kitts and Nevis", "Saint Lucia",
    "Saint Vincent and the Grenadines", "Samoa", "San Marino", "Sao Tome and Principe", "Saudi Arabia",
    "Senegal", "Serbia", "Seychelles", "Sierra Leone", "Singapore", "Slovakia", "Slovenia", "Solomon Islands",
    "Somalia", "South Africa", "South Korea", "South Sudan", "Spain", "Sri Lanka", "Sudan", "Suriname",
    "Sweden", "Switzerland", "Syria", "Taiwan", "Tajikistan", "Tanzania", "Thailand", "Timor-Leste", "Togo",
    "Tonga", "Trinidad and Tobago", "Tunisia", "Turkey", "Turkmenistan", "Tuvalu", "Uganda", "Ukraine",
    "United Arab Emirates", "United Kingdom", "United States", "Uruguay", "Uzbekistan", "Vanuatu",
    "Vatican City", "Venezuela", "Vietnam", "Yemen", "Zambia", "Zimbabwe", "Remote", "Other"
])

country = st.sidebar.selectbox("Select Country", country_list)
years_experience = st.sidebar.slider("Years of Experience", 0, 40, 5)
skills_input = st.sidebar.text_input("Enter Skills (comma separated)")
skills = [skill.strip() for skill in skills_input.split(",") if skill.strip()]

# Candidate Tab
with tab1:
    st.header("👤 Candidate Mode")
    uploaded_file = st.file_uploader("Upload your Resume (PDF only)", type="pdf")

    if uploaded_file:
        resume_text = extract_resume_text(uploaded_file)
        resume_doc = nlp(resume_text)
        st.subheader("Extracted Resume Preview")
        st.text_area("Resume Content", resume_text, height=300)

        if st.button("Analyze Resume & Get Job Advice"):
            prompt = f"Analyze the following resume for a candidate in {country} with {years_experience} years of experience and skills: {skills}. Provide detailed analysis, skill profiling, role suggestions, and tailored job advice.\n\nResume:\n{resume_text}"
            with st.spinner("Analyzing Resume and Fetching Job Market Info..."):
                analysis = get_ai_response(prompt)
                st.markdown("### 💬 AI Analysis & Recommendations")
                st.write(analysis)

# HR Recruiter Tab
with tab2:
    st.header("👥 HR Recruiter Mode")
    uploaded_file = st.file_uploader("Upload Candidate Resume (PDF only)", type="pdf", key="hr")

    if uploaded_file:
        resume_text = extract_resume_text(uploaded_file)
        st.subheader("Extracted Resume Preview")
        st.text_area("Resume Content", resume_text, height=300, key="hrtext")

        if st.button("Score Candidate & Suggest Roles"):
            prompt = f"You are a recruiter assistant. Evaluate this resume from the perspective of an HR professional hiring in {country}. The role requires skills: {skills} and {years_experience} years experience. Provide candidate scoring, skill match analysis, and suggest best-fit roles with insights.\n\nResume:\n{resume_text}"
            with st.spinner("Scoring Candidate and Fetching Suggestions..."):
                analysis = get_ai_response(prompt)
                st.markdown("### 📊 Candidate Evaluation & Suggestions")
                st.write(analysis)

st.markdown("---")
st.caption("© 2025 AI Resume Analyzer & Job Adviser | Powered by Groq + Streamlit + spaCy")
st.caption("Program Developed By waqasbm | AI & ML Practitioner")