Learn how to build a robust resume parser with Lovable. Our step-by-step guide covers setup, integration, and customization for a seamless hiring process.
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Setting Up Your Lovable Project for a Resume Parser
Start by creating a new project in Lovable. In the project dashboard, click on "New Project" and give it a meaningful name (for instance, "ResumeParser"). Since Lovable does not have a terminal, all dependency management will be handled through code configuration files.
Declaring Dependencies
Create a new file in your project called dependencies.txt
. In Lovable, this file will act as your configuration file for installing dependencies. Add the following lines to instruct Lovable which Python libraries to load:
Flask
python-docx
regex
# You may add any other dependencies required for resume parsing here.
Lovable will automatically read this file and install the listed dependencies when your project runs.
Creating the Main Application File
Create a new file called app.py
. This file will serve as the primary entry point for your resume parser application. Insert the following code into app.py
:
from flask import Flask, request, render\_template, jsonify
import re
from docx import Document
app = Flask(name)
Function to extract basic information from a resume
def parse_resume(file_content, filename):
text = ""
if filename.endswith('.docx'):
document = Document(file_content)
for para in document.paragraphs:
text += para.text + "\n"
else:
# Assuming plain text resume
text = file_content.read().decode("utf-8")
# Use simple regex to extract email address as an example
email_pattern = r"[a-zA-Z0-9+._%-]+@[a-zA-Z0-9.-]+.[a-zA-Z]{2,4}"
emails = re.findall(email\_pattern, text)
# Extract full name based on a heuristic (first line as name if words are capitalized)
lines = text.splitlines()
name = lines[0] if len(lines) > 0 and lines[0].istitle() else "Not Found"
return {
"name": name,
"emails": emails,
"raw\_text": text
}
@app.route("/", methods=["GET", "POST"])
def index():
if request.method == "POST":
if "resume" not in request.files:
return "No resume file provided", 400
file = request.files["resume"]
parsed_data = parse_resume(file, file.filename)
return jsonify(parsed_data)
return render_template("index.html")
if name == "main":
# Lovable will automatically bind to the appropriate host and port.
app.run()
This code sets up a basic Flask application with an endpoint to upload a resume. The parse_resume
function shows an example of how to process both .docx
files and plain text uploads.
Creating the HTML Template for Resume Upload
Create a new folder in your project named templates
. Inside the templates
folder, create a file called index.html
and add the following HTML code:
Resume Parser
Upload Your Resume
This HTML file creates a simple user interface for uploading resumes. The form sends a POST request to the root endpoint, which is handled by the Flask application.
Integrating and Running Your Application on Lovable
Since Lovable does not support terminal commands, all dependency installations and server initializations are automatically handled by the platform using the dependencies.txt
file and the app.py
's entry point. To run your application:
dependencies.txt
, app.py
, and templates/index.html
) are saved in your project.If any errors occur, review the error messages in the Lovable console pane to debug and make necessary adjustments in your code.
Testing the Resume Parser
Access the live URL generated by Lovable in your browser. The home page should display the resume upload form. Perform the following test:
.docx
or .txt
format.parse\_resume
function if needed.This completes the setup of your resume parser in Lovable.
const express = require('express');
const multer = require('multer');
const { parseResume } = require('lovable-resume-parser'); // Hypothetical library
const app = express();
const upload = multer();
app.post('/api/parse-resume', upload.single('resume'), async (req, res) => {
if (!req.file) {
return res.status(400).json({ error: 'No file uploaded' });
}
try {
const resumeBuffer = req.file.buffer;
const parsedData = await parseResume(resumeBuffer);
const structuredResume = {
personal\_info: {
name: parsedData.name || '',
email: parsedData.email || '',
phone: parsedData.phone || ''
},
work\_experience: parsedData.experiences ? parsedData.experiences.map(exp => ({
company: exp.company,
role: exp.title,
start\_date: exp.start,
end\_date: exp.end,
description: exp.summary
})) : [],
education: parsedData.education ? parsedData.education.map(edu => ({
institution: edu.institution,
degree: edu.degree,
start\_date: edu.start,
end\_date: edu.end
})) : []
};
return res.json(structuredResume);
} catch (error) {
console.error(error);
return res.status(500).json({ error: 'Failed to parse resume' });
}
});
app.listen(3000, () => {
console.log('Resume parser API running on port 3000');
});
const express = require('express');
const multer = require('multer');
const axios = require('axios');
const { parseResume } = require('lovable-resume-parser-ex'); // Hypothetical Lovable extendable parser library
const app = express();
const upload = multer();
app.post('/api/enrich-resume', upload.single('resume'), async (req, res) => {
if (!req.file) {
return res.status(400).json({ error: 'Resume file is required.' });
}
try {
const resumeBuffer = req.file.buffer;
const parsedResume = await parseResume(resumeBuffer);
// Send parsed resume data to an external enrichment API for personality and skills insights
const enrichmentResponse = await axios.post('https://api.external-enrichment.com/insights', {
email: parsedResume.email,
skills: parsedResume.skills
});
const enrichedInsights = enrichmentResponse.data;
const structuredResume = {
personal\_info: {
name: parsedResume.name || '',
email: parsedResume.email || '',
phone: parsedResume.phone || ''
},
work\_experience: parsedResume.experiences || [],
education: parsedResume.education || [],
enriched\_insights: enrichedInsights
};
return res.json(structuredResume);
} catch (error) {
console.error('Error processing resume:', error);
return res.status(500).json({ error: 'Failed to process the resume.' });
}
});
app.listen(3001, () => {
console.log('Resume enrichment API running on port 3001');
});
const express = require('express');
const multer = require('multer');
const jwt = require('jsonwebtoken');
const AWS = require('aws-sdk');
const { streamParseResume } = require('lovable-resume-parser'); // Hypothetical stream-based parser
const app = express();
const upload = multer({ storage: multer.memoryStorage() });
const s3 = new AWS.S3({
accessKeyId: process.env.AWS_ACCESS_KEY,
secretAccessKey: process.env.AWS_SECRET_KEY,
region: process.env.AWS\_REGION
});
function authenticateToken(req, res, next) {
const authHeader = req.headers['authorization'];
const token = authHeader && authHeader.split(' ')[1];
if (!token) return res.status(401).json({ error: 'Missing token' });
jwt.verify(token, process.env.JWT\_SECRET, (err, user) => {
if (err) return res.status(403).json({ error: 'Invalid token' });
req.user = user;
next();
});
}
app.post('/api/secure/parse-s3-resume', authenticateToken, upload.single('resume'), async (req, res) => {
if (!req.file) {
return res.status(400).json({ error: 'No resume provided' });
}
const s3Params = {
Bucket: process.env.AWS_S3_BUCKET,
Key: `resumes/${Date.now()}_${req.file.originalname}`,
Body: req.file.buffer,
ContentType: req.file.mimetype
};
try {
const s3Upload = await s3.upload(s3Params).promise();
const s3Stream = s3.getObject({ Bucket: process.env.AWS_S3_BUCKET, Key: s3Params.Key }).createReadStream();
streamParseResume(s3Stream, (err, parsedData) => {
if (err) {
return res.status(500).json({ error: 'Error parsing resume' });
}
res.json({
s3Location: s3Upload.Location,
parsedResume: {
personal: parsedData.personal || {},
experience: parsedData.experience || [],
education: parsedData.education || []
}
});
});
} catch (error) {
console.error(error);
res.status(500).json({ error: 'Server error processing resume' });
}
});
app.listen(4000, () => {
console.log('Secure resume parser running on port 4000');
});
Book a call with an Expert
Starting a new venture? Need to upgrade your web app? RapidDev builds application with your growth in mind.
Understanding the Resume Parser Challenge
Prerequisites
Planning the Parser Structure
Setting Up the Development Environment
Preprocessing Resume Data
Generating Code with an AI Tool
Writing the Resume Parsing Code
resume\_parser.py
).
import re
def parse_resume(text):
# Define regex patterns for key information
name_pattern = re.compile(r'Name:\s_(._)')
email_pattern = re.compile(r'Email:\s*([\w.-]+@[\w.-]+)')
phone_pattern = re.compile(r'Phone:\s*([\d-]+)')
name = re.search(name\_pattern, text)
email = re.search(email\_pattern, text)
phone = re.search(phone\_pattern, text)
return {
'name': name.group(1).strip() if name else None,
'email': email.group(1).strip() if email else None,
'phone': phone.group(1).strip() if phone else None,
}
if name == "main":
resume_text = """
Name: Jane Doe
Email: jane.doe@example.com
Phone: 123-456-7890
"""
details = parse_resume(resume_text)
print(details)
Enhancing the Parser with AI-Generated Code
Handling Different Resume Formats
import PyPDF2
def extract_text_from_pdf(pdf_path):
with open(pdf_path, 'rb') as file:
reader = PyPDF2.PdfReader(file)
text = ""
for page in reader.pages:
text += page.extract_text()
return text
Testing and Debugging the Parser
Iterating and Improving the Code
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