pip install spacy
python -m spacy download en_core_web_sm
Then, we created a new service for resume parsing:

# app/services/resume_parser.py
import spacy

nlp = spacy.load("en_core_web_sm")

def parse_resume(text):
    doc = nlp(text)

    parsed_data = {
        "name": [],
        "email": [],
        "phone": [],
        "skills": [],
        "education": [],
        "experience": []
    }

    for ent in doc.ents:
        if ent.label_ == "PERSON":
            parsed_data["name"].append(ent.text)
        elif ent.label_ == "EMAIL":
            parsed_data["email"].append(ent.text)
        # Add more entity extractions here

    # Custom skill extraction (simplified)
    skill_keywords = ["Python", "JavaScript", "Machine Learning", "Data Analysis"]
    parsed_data["skills"] = [keyword for keyword in skill_keywords if keyword.lower() in text.lower()]

    return parsed_data
We also created a new route to handle resume uploads:

# app/routes/resume.py
from flask import Blueprint, request, jsonify
from app.services.resume_parser import parse_resume

resume_bp = Blueprint('resume', __name__)

@resume_bp.route('/upload', methods=['POST'])
def upload_resume():
    if 'file' not in request.files:
        return jsonify({"error": "No file part"}), 400

    file = request.files['file']
    if file.filename == '':
        return jsonify({"error": "No selected file"}), 400

    if file:
        # Read the file content
        resume_text = file.read().decode('utf-8')

        # Parse the resume
        parsed_data = parse_resume(resume_text)

        return jsonify(parsed_data), 200