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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, supabase | |
| #from config import supabase | |
| # These functions will be called in the main.py file | |
| 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, json=payload) | |
| # 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, email, summary): | |
| """Stores candidate data in Supabase""" | |
| data = { | |
| "name": candidate_name, | |
| "resume": resume_text, | |
| "score": score, | |
| "email": email, | |
| "summary": summary # Store summary in Supabase | |
| } | |
| response = supabase.table("candidates").insert(data).execute() | |
| print("Inserted into Supabase:", response) # Debugging output | |
| 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() | |
| summary = candidate.get("summary", "No summary available") # Avoid KeyError | |
| page.insert_text( | |
| (50, 50), | |
| f"Candidate: {candidate['name']}\nEmail: {candidate['email']}\nScore: {candidate['score']}\nSummary: {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) | |
| # Generate summary (replace with actual summarization logic later) | |
| summary = f"{pdf_file.name} has a score of {score} for this job." | |
| candidates.append({ | |
| "name": pdf_file.name, | |
| "resume": resume_text, | |
| "score": score, | |
| "email": email, | |
| "summary": summary | |
| }) | |
| # Store all details including summary in Supabase | |
| store_in_supabase(resume_text, score, pdf_file.name, email, summary) | |
| return sorted(candidates, key=lambda x: x["score"], reverse=True)[:5] # Return top 5 candidates |