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import fitz # PyMuPDF for PDF processing
import requests
import json
import re
from io import BytesIO
import supabase
from config import SUPABASE_URL, SUPABASE_KEY, HF_API_TOKEN, HF_API_URL, HF_HEADERS
def parse_resume(pdf_file):
"""Extracts text from a resume PDF."""
doc = fitz.open(stream=pdf_file.read(), filetype="pdf")
text = "\n".join([page.get_text("text") for page in doc])
return text
def extract_email(resume_text):
"""Extracts an email address from resume text."""
match = re.search(r"[\w\.-]+@[\w\.-]+", resume_text)
return match.group(0) if match else None
def score_candidate(resume_text, job_description):
"""Sends resume and job description to Hugging Face for scoring."""
payload = {"inputs": f"Resume: {resume_text}\nJob Description: {job_description}"}
response = requests.post(HF_API_URL, headers=HF_HEADERS, data=json.dumps(payload))
return response.json().get("score", 0)
# Debugging: Print response
if response.status_code != 200:
print(f"Error: {response.status_code}, {response.text}") # Log any errors
return 0 # Return default score if API fails
try:
return response.json().get("score", 0)
except requests.exceptions.JSONDecodeError:
print("Failed to decode JSON response:", response.text) # Debugging output
return 0 # Return default score if JSON decoding fails
def store_in_supabase(resume_text, score, candidate_name):
"""Stores resume data in Supabase."""
email = extract_email(resume_text)
data = {
"name": candidate_name,
"resume": resume_text,
"score": score,
"email": email
}
supabase.table("candidates").insert(data).execute()
def generate_pdf_report(shortlisted_candidates):
"""Generates a PDF summary of shortlisted candidates."""
pdf = BytesIO()
doc = fitz.open()
for candidate in shortlisted_candidates:
page = doc.new_page()
page.insert_text((50, 50), f"Candidate: {candidate['name']}\nEmail: {candidate['email']}\nScore: {candidate['score']}\nSummary: {candidate['summary']}")
doc.save(pdf)
pdf.seek(0)
return pdf
def process_resumes(uploaded_files, job_description):
"""Processes uploaded resumes and returns shortlisted candidates."""
candidates = []
for pdf_file in uploaded_files:
resume_text = parse_resume(pdf_file)
score = score_candidate(resume_text, job_description)
email = extract_email(resume_text)
candidates.append({
"name": pdf_file.name,
"resume": resume_text,
"score": score,
"email": email
})
store_in_supabase(resume_text, score, pdf_file.name, email)
return sorted(candidates, key=lambda x: x["score"], reverse=True)[:5] |