Update app.py

app.py

@@ -1,3 +1,4 @@
+
 import gradio as gr
 from langchain_community.document_loaders.pdf import PyPDFLoader
 from langchain_community.embeddings import HuggingFaceEmbeddings
@@ -11,24 +12,11 @@ from collections import Counter
 import numpy as np
 import tempfile
 import os
-import requests
-from bs4 import BeautifulSoup
 
 load_dotenv()
 groq_api_key = os.getenv("GROQ_API_KEY")
 os.environ["GROQ_API_KEY"] = groq_api_key
 
-def scrape_skills_from_jd_link(url):
-    try:
-        response = requests.get(url, timeout=10)
-        soup = BeautifulSoup(response.text, 'html.parser')
-        text = soup.get_text(separator=' ', strip=True)
-        skills_list = ["Python", "SQL", "Machine Learning", "Deep Learning", "NLP", "Cloud", "TensorFlow", "Java", "C++", "HTML", "CSS", "JavaScript"]
-        extracted_skills = [skill for skill in skills_list if skill.lower() in text.lower()]
-        return extracted_skills if extracted_skills else ["No skills detected."]
-    except Exception as e:
-        return [f"Error fetching JD: {str(e)}"]
-
 def extract_text_from_pdf(pdf_file):
     with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as temp:
         temp.write(pdf_file)
@@ -102,14 +90,9 @@ def create_pdf(full_report_text):
     pdf.output(output_path)
     return output_path
 
-def process_skill_gap(resume_pdf, jd_pdfs, jd_link_url):
+def process_skill_gap(resume_pdf, jd_pdfs):
     if resume_pdf is None or jd_pdfs is None:
-        return "", "", "", "", "", None, "", "", "", ""
-
-    scraped_skills_text = ""
-    if jd_link_url:
-        scraped_skills = scrape_skills_from_jd_link(jd_link_url)
-        scraped_skills_text = ", ".join(scraped_skills)
+        return "", "", "", "", "", None, "", "", ""
 
     resume_text = extract_text_from_pdf(resume_pdf)
     user_skills = extract_skills(resume_text)
@@ -149,17 +132,11 @@ def process_skill_gap(resume_pdf, jd_pdfs, jd_link_url):
     pdf_path = create_pdf(full_report_clean)
     progress_display = generate_circular_progress(overall_match)
 
-    return progress_display, "✅ Analysis done across all JDs", ", ".join(set(all_missing_skills)), "Multi-JD Comparison Completed", full_report, pdf_path, top_missing_skills_text, resources, certifications, scraped_skills_text
+    return progress_display, "✅ Analysis done across all JDs", ", ".join(set(all_missing_skills)), "Multi-JD Comparison Completed", full_report, pdf_path, top_missing_skills_text, resources, certifications
 
 with gr.Blocks() as demo:
-    gr.HTML("""<style>body{background: linear-gradient(135deg, #0d1b2a, #1b263b, #415a77);background-size: 300% 300%;animation: gradientShift 15s ease infinite;overflow-x: hidden;position: relative}@keyframes gradientShift{0%{background-position:0% 50%}50%{background-position:100% 50%}100%{background-position:0% 50%}.floating-circle{position:fixed;border-radius:50%;background:rgba(0,255,255,0.08);box-shadow:0 0 20px rgba(0,255,255,0.2);animation:floatUp linear infinite;z-index:-1;filter:blur(2px)}@keyframes floatUp{0%{transform:translateY(100vh);opacity:0}10%{opacity:.2}90%{opacity:.2}100%{transform:translateY(-200px);opacity:0}}.floating-circle:nth-child(1){width:80px;height:80px;left:20%;animation-duration:25s}.floating-circle:nth-child(2){width:100px;height:100px;left:50%;animation-duration:30s;animation-delay:5s}.floating-circle:nth-child(3){width:60px;height:60px;left:70%;animation-duration:20s;animation-delay:10s}.floating-circle:nth-child(4){width:90px;height:90px;left:35%;animation-duration:35s;animation-delay:15s}.floating-circle:nth-child(5){width:120px;height:120px;left:80%;animation-duration:40s;animation-delay:20s}h1,h2,h3,p,label{color:#00f7ff!important;text-shadow:0 0 8px rgba(0,255,255,0.3)}</style><div class='floating-circle'></div><div class='floating-circle'></div><div class='floating-circle'></div><div class='floating-circle'></div><div class='floating-circle'></div>""")
-
-    gr.Markdown("# 🧠 TALENTPATCH with Multi-JD Comparison and AI Skill Gap Analysis")
-
     resume_file = gr.File(label="📄 Upload Resume (PDF)", type="binary")
     jd_files = gr.File(label="📄 Upload Multiple Job Descriptions (PDFs)", type="binary", file_types=[".pdf"], file_count="multiple")
-    jd_link_input = gr.Textbox(label="🔗 Optional: Paste JD URL for Real-Time Skill Extraction")
-
     match_progress = gr.HTML(label="Skill Match Progress")
     skill_match_text = gr.Textbox(label="Status", interactive=False)
     missing_skills_text = gr.Textbox(label="All Missing Skills", interactive=False)
@@ -169,13 +146,10 @@ with gr.Blocks() as demo:
     top_skills_output = gr.Textbox(label="Top Missing Skills Across JDs", interactive=False)
     learning_resources = gr.Markdown(label="📚 AI Learning Resource Recommendations")
     certification_output = gr.Textbox(label="🎓 Recommended Certifications", interactive=False)
-    scraped_skills_output = gr.Textbox(label="🔍 Skills Extracted from JD Link", interactive=False)
-
     submit_btn = gr.Button("🚀 Analyze Skill Gap")
-
     submit_btn.click(
         fn=process_skill_gap,
-        inputs=[resume_file, jd_files, jd_link_input],
+        inputs=[resume_file, jd_files],
         outputs=[
             match_progress,
             skill_match_text,
@@ -185,9 +159,7 @@ with gr.Blocks() as demo:
             download_pdf,
             top_skills_output,
             learning_resources,
-            certification_output,
-            scraped_skills_output
+            certification_output
         ]
     )
-
-demo.launch()
+demo.launch()