app.py

import streamlit as st
import openai
import os
import PyPDF2

# Load OpenAI API Key from environment variables
openai.api_key = os.getenv("OPENAI_API_KEY")

if not openai.api_key:
    st.error("⚠️ OpenAI API key is missing! Please add it in Hugging Face secrets.")
    st.stop()

st.title("📄 AI-Powered Resume Reviewer")
st.write("Upload your resume (PDF/TXT), and AI will provide feedback!")

# File uploader
uploaded_file = st.file_uploader("Upload your resume", type=["txt", "pdf"])

def extract_text_from_file(uploaded_file):
    """Extract text from uploaded TXT or PDF file."""
    if uploaded_file is not None:
        file_extension = uploaded_file.name.split(".")[-1]
        
        if file_extension == "txt":
            return uploaded_file.read().decode("utf-8")
        
        elif file_extension == "pdf":
            pdf_reader = PyPDF2.PdfReader(uploaded_file)
            text = "\n".join([page.extract_text() for page in pdf_reader.pages if page.extract_text()])
            return text
        
    return ""

def analyze_resume(resume_text):
    """Send resume text to OpenAI for feedback."""
    response = openai.chat.completions.create(
        model="gpt-4",
        messages=[{"role": "user", "content": f"Review this resume and provide constructive feedback:\n\n{resume_text}"}]
    )
    return response.choices[0].message.content.strip()

if uploaded_file:
    st.write("✅ **Resume Uploaded Successfully!**")
    resume_text = extract_text_from_file(uploaded_file)
    
    if st.button("Analyze Resume"):
        with st.spinner("Analyzing... ⏳"):
            feedback = analyze_resume(resume_text)
            st.subheader("📌 AI Feedback:")
            st.write(feedback)