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| """ | |
| AI Resume Studio – Hugging Face Space | |
| Author: Oluwafemi Idiakhoa | |
| Last update: 2025‑06‑27 | |
| Features | |
| ──────── | |
| 1. Generate resume → Word & PDF downloads | |
| 2. Score resume against job description | |
| 3. AI Section Co‑Pilot (rewrite, quantify, bulletize…) | |
| 4. Cover‑letter generator | |
| 5. Job‑description scraper by URL | |
| 6. Multilingual export via DeepL (free & pro keys supported) | |
| """ | |
| # ────────────────────────────────────────────────────────────────────────────── | |
| # Imports & setup | |
| # ────────────────────────────────────────────────────────────────────────────── | |
| import os, tempfile | |
| import requests | |
| import gradio as gr | |
| import google.generativeai as genai | |
| from dotenv import load_dotenv | |
| from bs4 import BeautifulSoup | |
| from docx import Document # python‑docx | |
| from reportlab.lib.pagesizes import LETTER | |
| from reportlab.pdfgen import canvas | |
| import deepl # DeepL translation | |
| load_dotenv() | |
| # Gemini model (make sure key has access to this version) | |
| genai.configure(api_key=os.getenv("API_KEY")) | |
| GEMINI_MODEL = genai.GenerativeModel("gemini-1.5-pro-latest") | |
| # DeepL translator | |
| DEEPL_KEY = os.getenv("DEEPL_API_KEY") | |
| DEEPL_TRANSLATOR = deepl.Translator(DEEPL_KEY) if DEEPL_KEY else None | |
| # Supported DeepL target languages (code → label) | |
| LANGS = { | |
| "EN": "English", | |
| "DE": "German", | |
| "FR": "French", | |
| "ES": "Spanish", | |
| "IT": "Italian", | |
| "NL": "Dutch", | |
| "PT-PT": "Portuguese", | |
| "PT-BR": "Portuguese (BR)", | |
| "PL": "Polish", | |
| "JA": "Japanese", | |
| "ZH": "Chinese", | |
| } | |
| # ────────────────────────────────────────────────────────────────────────────── | |
| # Helpers | |
| # ────────────────────────────────────────────────────────────────────────────── | |
| def ask_gemini(prompt: str, temperature: float = 0.6) -> str: | |
| try: | |
| rsp = GEMINI_MODEL.generate_content( | |
| prompt, generation_config={"temperature": temperature} | |
| ) | |
| return rsp.text.strip() | |
| except Exception as err: | |
| return f"[Gemini Error] {err}" | |
| def translate_if_needed(text: str, target_code: str) -> str: | |
| if target_code == "EN" or not DEEPL_TRANSLATOR: | |
| return text # already English or DeepL key missing | |
| try: | |
| res = DEEPL_TRANSLATOR.translate_text(text, target_lang=target_code) | |
| return res.text | |
| except Exception as err: | |
| return f"[DeepL Error] {err}\n\n{text}" | |
| def save_docx(text: str) -> str: | |
| tmp = tempfile.NamedTemporaryFile(delete=False, suffix=".docx") | |
| doc = Document() | |
| for line in text.splitlines(): | |
| doc.add_paragraph(line) | |
| doc.save(tmp.name) | |
| return tmp.name | |
| def save_pdf(text: str) -> str: | |
| tmp = tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") | |
| c = canvas.Canvas(tmp.name, pagesize=LETTER) | |
| width, height = LETTER | |
| y = height - 72 | |
| for line in text.splitlines(): | |
| c.drawString(72, y, line) | |
| y -= 14 | |
| if y < 72: | |
| c.showPage() | |
| y = height - 72 | |
| c.save() | |
| return tmp.name | |
| # ────────────────────────────────────────────────────────────────────────────── | |
| # Core AI functions | |
| # ────────────────────────────────────────────────────────────────────────────── | |
| def generate_resume(name, email, phone, summary, experience, education, skills, lang): | |
| prompt = f""" | |
| Create a professional resume in Markdown. **Do not use first‑person pronouns.** | |
| Target language: {LANGS[lang]} | |
| Name: {name} | |
| Email: {email} | |
| Phone: {phone} | |
| Professional Summary: | |
| {summary} | |
| Experience: | |
| {experience} | |
| Education: | |
| {education} | |
| Skills: | |
| {skills} | |
| """ | |
| resume_md = ask_gemini(prompt) | |
| return translate_if_needed(resume_md, lang) | |
| def score_resume(resume_md, job_desc): | |
| prompt = f""" | |
| Evaluate the RESUME against the JOB DESCRIPTION. Return *only* compact Markdown: | |
| ### Match Score | |
| <integer 0‑100> | |
| ### Suggestions | |
| - <bullet 1> | |
| - <bullet 2> | |
| - <bullet 3> | |
| """ | |
| return ask_gemini(prompt.format(resume_md=resume_md, job_desc=job_desc), temperature=0.4) | |
| def refine_section(section_text, instruction, lang): | |
| prompt = f""" | |
| Perform the following instruction on the resume section. Respond in {LANGS[lang]}. | |
| Instruction: {instruction} | |
| Text: | |
| {section_text} | |
| """ | |
| refined = ask_gemini(prompt) | |
| return translate_if_needed(refined, lang) | |
| def generate_cover_letter(resume_md, job_desc, tone, lang): | |
| prompt = f""" | |
| Draft a one‑page cover letter (≤ 300 words) in {tone} tone, aligning the RESUME | |
| to the JOB DESCRIPTION. Use {LANGS[lang]} throughout. Salutation: "Dear Hiring Manager,". | |
| RESUME: | |
| {resume_md} | |
| JOB DESCRIPTION: | |
| {job_desc} | |
| """ | |
| letter = ask_gemini(prompt) | |
| return translate_if_needed(letter, lang) | |
| # ────────────────────────────────────────────────────────────────────────────── | |
| # JD scraper | |
| # ────────────────────────────────────────────────────────────────────────────── | |
| def scrape_job_description(url): | |
| try: | |
| headers = {"User-Agent": "Mozilla/5.0"} | |
| page = requests.get(url, headers=headers, timeout=10) | |
| soup = BeautifulSoup(page.text, "html.parser") | |
| # Heuristics for popular boards | |
| selectors = [ | |
| "div.jobsearch-jobDescriptionText", # Indeed | |
| "section.description", # generic | |
| "div.jobs-description__content", # LinkedIn | |
| "div#job-details" # Greenhouse | |
| ] | |
| for sel in selectors: | |
| block = soup.select_one(sel) | |
| if block: | |
| return block.get_text(" ", strip=True) | |
| return soup.get_text(" ", strip=True)[:3000] | |
| except Exception as e: | |
| return f"[Error] {e}" | |
| # ────────────────────────────────────────────────────────────────────────────── | |
| # Wrapper to export resume + files | |
| # ────────────────────────────────────────────────────────────────────────────── | |
| def generate_resume_and_files(name, email, phone, summary, | |
| experience, education, skills, lang): | |
| resume_md = generate_resume(name, email, phone, summary, | |
| experience, education, skills, lang) | |
| return resume_md, save_docx(resume_md), save_pdf(resume_md) | |
| # ────────────────────────────────────────────────────────────────────────────── | |
| # Gradio UI | |
| # ────────────────────────────────────────────────────────────────────────────── | |
| with gr.Blocks(title="AI Resume Studio") as demo: | |
| gr.Markdown("## 🧠 Interactive AI Resume Studio (Gemini × DeepL)") | |
| LANG_CHOICES = [(v, k) for k, v in LANGS.items()] | |
| # ── 1 · Resume generation ──────────────────────────────────────────────── | |
| with gr.Tab("📄 Generate Resume"): | |
| with gr.Row(): | |
| name = gr.Textbox(label="Name") | |
| email = gr.Textbox(label="Email") | |
| phone = gr.Textbox(label="Phone") | |
| summary = gr.Textbox(label="Professional Summary") | |
| experience = gr.Textbox(label="Experience") | |
| education = gr.Textbox(label="Education") | |
| skills = gr.Textbox(label="Skills") | |
| lang_sel = gr.Dropdown(LANG_CHOICES, value="EN", label="Output Language") | |
| resume_md = gr.Markdown(label="Generated Resume") | |
| docx_file = gr.File(label="⬇ Word (.docx)") | |
| pdf_file = gr.File(label="⬇ PDF (.pdf)") | |
| gen_btn = gr.Button("Generate Resume") | |
| gen_btn.click( | |
| generate_resume_and_files, | |
| inputs=[name, email, phone, summary, experience, education, skills, lang_sel], | |
| outputs=[resume_md, docx_file, pdf_file], | |
| ) | |
| # ── 2 · Match score ────────────────────────────────────────────────────── | |
| with gr.Tab("🧮 Score Resume Against Job"): | |
| resume_in = gr.Textbox(label="Resume (Markdown)", lines=12) | |
| jd_in = gr.Textbox(label="Job Description", lines=8) | |
| score_out = gr.Markdown(label="Score & Suggestions") | |
| score_btn = gr.Button("Evaluate") | |
| score_btn.click(score_resume, inputs=[resume_in, jd_in], outputs=score_out) | |
| # ── 3 · AI Section Co‑Pilot ────────────────────────────────────────────── | |
| with gr.Tab("✏️ AI Section Co‑Pilot"): | |
| sec_text = gr.Textbox(label="Section Text", lines=6) | |
| action = gr.Radio( | |
| ["Rewrite", "Make More Concise", "Quantify Achievements", "Convert to Bullet Points"], | |
| label="Action" | |
| ) | |
| sec_lang = gr.Dropdown(LANG_CHOICES, value="EN", label="Language") | |
| sec_out = gr.Textbox(label="AI Output", lines=6) | |
| sec_btn = gr.Button("Apply") | |
| sec_btn.click( | |
| refine_section, inputs=[sec_text, action, sec_lang], outputs=sec_out | |
| ) | |
| # ── 4 · Cover‑letter generator ─────────────────────────────────────────── | |
| with gr.Tab("📧 Cover‑Letter Generator"): | |
| cv_resume = gr.Textbox(label="Resume (Markdown)", lines=12) | |
| cv_jd = gr.Textbox(label="Job Description", lines=8) | |
| cv_tone = gr.Radio(["Professional", "Friendly", "Enthusiastic"], value="Professional", label="Tone") | |
| cv_lang = gr.Dropdown(LANG_CHOICES, value="EN", label="Language") | |
| cv_out = gr.Markdown(label="Cover Letter") | |
| cv_btn = gr.Button("Generate Cover Letter") | |
| cv_btn.click( | |
| generate_cover_letter, | |
| inputs=[cv_resume, cv_jd, cv_tone, cv_lang], | |
| outputs=cv_out, | |
| ) | |
| # ── 5 · Job‑description scraper ────────────────────────────────────────── | |
| with gr.Tab("🌐 Job Description Scraper"): | |
| url_in = gr.Textbox(label="Job URL") | |
| jd_out = gr.Textbox(label="Extracted Description", lines=12) | |
| scrape_btn = gr.Button("Fetch Description") | |
| scrape_btn.click(scrape_job_description, inputs=url_in, outputs=jd_out) | |
| demo.launch(share=False) # HF Spaces already publishes the app | |