File size: 3,446 Bytes
f316ad5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 | import streamlit as st
import os
from langchain_community.llms import HuggingFaceHub
from PyPDF2 import PdfReader
import docx2txt
# Set Hugging Face token (Get yours from https://huggingface.co/settings/tokens)
os.environ["HUGGINGFACEHUB_API_TOKEN"] = st.secrets["HUGGINGFACEHUB_API_TOKEN"]
# Initialize Mistral 7B model
repo_id = "mistralai/Mistral-7B-v0.1"
llm = HuggingFaceHub(
repo_id=repo_id,
model_kwargs={"temperature": 0.5, "max_length": 4096}
)
def extract_text(uploaded_file):
"""Extract text from PDF or DOCX files"""
if uploaded_file.type == "application/pdf":
pdf_reader = PdfReader(uploaded_file)
return "\n".join([page.extract_text() for page in pdf_reader.pages])
elif uploaded_file.type == "application/vnd.openxmlformats-officedocument.wordprocessingml.document":
return docx2txt.process(uploaded_file)
return ""
def analyze_resume(resume_text, job_desc):
"""Analyze resume using Mistral 7B"""
prompt = f"""
Analyze this resume against the job description below. Provide:
1. Top 5 missing keywords from job description
2. Three suggested improvements
3. ATS compatibility score (0-100)
Resume:
{resume_text[:3000]}
Job Description:
{job_desc[:2000]}
Format output using markdown with clear sections.
"""
return llm.invoke(prompt)
def check_ats_compliance(text):
"""Basic ATS formatting checks"""
forbidden_elements = ["table", "image", "column", "graphic"]
return all(element not in text.lower() for element in forbidden_elements)
def generate_ats_version(text):
"""Convert text to ATS-friendly format"""
return text.replace("\n", " ").strip()
# Streamlit UI
st.set_page_config(page_title="ATS Resume Optimizer", layout="wide")
st.title("📄 Free ATS Resume Optimizer")
st.markdown("Upload your resume and job description to get AI-powered optimization tips!")
col1, col2 = st.columns(2)
with col1:
uploaded_file = st.file_uploader("Upload Resume (PDF/DOCX)", type=["pdf", "docx"])
job_description = st.text_area("Paste Job Description", height=200)
with col2:
if uploaded_file and job_description:
if st.button("Analyze and Optimize"):
with st.spinner("Processing with Mistral 7B..."):
resume_text = extract_text(uploaded_file)
# Perform analysis
analysis = analyze_resume(resume_text, job_description)
ats_compliant = check_ats_compliance(resume_text)
optimized_text = generate_ats_version(resume_text)
# Display results
st.subheader("Analysis Results")
st.markdown(analysis)
st.subheader("ATS Compliance Check")
st.metric("Format Status", "Pass ✅" if ats_compliant else "Fail ❌")
# Download optimized version
st.download_button(
label="Download ATS-Optimized Resume",
data=optimized_text,
file_name="optimized_resume.txt",
mime="text/plain"
)
else:
st.info("👈 Upload your resume and paste a job description to get started")
st.markdown("---")
st.caption("Note: This tool uses Mistral 7B AI model for analysis. Always review suggestions before submitting applications.")
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