Update app.py

app.py

@@ -11,29 +11,24 @@ 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
 
-import requests
-from bs4 import BeautifulSoup
-
 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)
-
-        # Basic keyword match for now
         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)
@@ -65,38 +60,37 @@ def suggest_certifications(missing_skills):
         "Java": "Oracle Certified Java Programmer",
         "C++": "C++ Nanodegree (Udacity)"
     }
-
     suggestions = []
     for skill in missing_skills:
         if skill in cert_mapping:
             suggestions.append(f"{skill}: {cert_mapping[skill]}")
-
     return "\n".join(suggestions) if suggestions else "No specific certifications recommended."
 
-
+def generate_circular_progress(percentage):
+    html_code = f"""
+    <div style='position: relative; width: 150px; height: 150px; border-radius: 50%; background: conic-gradient(#00f7ff {percentage}%, #2c5364 {percentage}% 100%); display: flex; align-items: center; justify-content: center;'>
+        <div style='position: absolute; color: white; font-weight: bold;'>{percentage}%</div>
+    </div>
+    """
+    return html_code
 
 def generate_skill_gap_report(user_skills, job_skills, missing_skills, match_percent):
     llm = ChatGroq(model="llama3-8b-8192", temperature=0.2)
-
     template = """
     User Skills: {user_skills}
     Job Requirements: {job_skills}
     Missing Skills: {missing_skills}
     Match Percentage: {match_percent}%
-
     Generate a short, friendly skill gap report. Suggest next steps for the user to improve their chances.
     """
-
     prompt = PromptTemplate.from_template(template)
     chain = prompt | llm | StrOutputParser()
-
     report = chain.invoke({
         "user_skills": ", ".join(user_skills),
         "job_skills": ", ".join(job_skills),
         "missing_skills": ", ".join(missing_skills),
         "match_percent": match_percent
     })
-
     return report
 
 def create_pdf(full_report_text):
@@ -108,20 +102,23 @@ def create_pdf(full_report_text):
     pdf.output(output_path)
     return output_path
 
-def process_skill_gap(resume_pdf, jd_pdfs):
+def process_skill_gap(resume_pdf, jd_pdfs, jd_link_url):
     if resume_pdf is None or jd_pdfs is None:
-        return 0, "❌ Please upload Resume and Job Descriptions.", "", "", "", 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)
 
     resume_text = extract_text_from_pdf(resume_pdf)
     user_skills = extract_skills(resume_text)
-
     all_missing_skills = []
     full_report = ""
 
     for idx, jd_pdf in enumerate(jd_pdfs, start=1):
         jd_text = extract_text_from_pdf(jd_pdf)
         job_skills = extract_skills(jd_text)
-
         common = set(user_skills) & set(job_skills)
         match_percent = (len(common) / len(job_skills)) * 100 if job_skills else 0
         missing_skills = list(set(job_skills) - set(user_skills))
@@ -133,15 +130,10 @@ def process_skill_gap(resume_pdf, jd_pdfs):
         similarity_percent = round(similarity_score * 100, 2)
 
         ai_report = generate_skill_gap_report(user_skills, job_skills, missing_skills, match_percent)
-
-        full_report += f"\nJD {idx}:\n"
-        full_report += f"Skill Match: {match_percent}%\n"
-        full_report += f"Missing Skills: {', '.join(missing_skills) if missing_skills else 'None'}\n"
-        full_report += f"Similarity Score: {similarity_percent}%\n"
-        full_report += f"AI Report:\n{ai_report}\n"
-        full_report += "-------------------------\n"
+        full_report += f"\nJD {idx}:\nSkill Match: {match_percent}%\nMissing Skills: {', '.join(missing_skills) if missing_skills else 'None'}\nSimilarity Score: {similarity_percent}%\nAI Report:\n{ai_report}\n-------------------------\n"
 
     resources = generate_learning_resources(list(set(all_missing_skills)))
+    certifications = suggest_certifications(all_missing_skills)
 
     most_common_skills = Counter(all_missing_skills).most_common(3)
     top_missing_skills_text = "Top Missing Skills Across JDs: " + ", ".join(
@@ -153,162 +145,48 @@ def process_skill_gap(resume_pdf, jd_pdfs):
         2
     ) if user_skills else 0
 
-    # Clean full_report to remove emojis for PDF saving
     full_report_clean = full_report.encode('ascii', 'ignore').decode('ascii')
     pdf_path = create_pdf(full_report_clean)
+    progress_display = generate_circular_progress(overall_match)
 
-    return overall_match, "✅ Analysis done across all JDs", ", ".join(set(all_missing_skills)), "Multi-JD Comparison Completed", full_report, pdf_path, top_missing_skills_text, resources
+    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
 
 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 circles (professional, subtle glowing particles) */
-.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: 0.2;
-    }
-    90% {
-        opacity: 0.2;
-    }
-    100% {
-        transform: translateY(-200px);
-        opacity: 0;
-    }
-}
-
-/* Add 5 floating circles with different sizes, positions, and speeds */
-.floating-circle:nth-child(1) {
-    width: 80px;
-    height: 80px;
-    left: 20%;
-    animation-duration: 25s;
-    animation-delay: 0s;
-}
-.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;
-}
-
-/* Text styling */
-h1, h2, h3, p, label {
-    color: #00f7ff !important;
-    text-shadow: 0 0 8px rgba(0, 255, 255, 0.3);
-}
+    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>""")
 
-/* Input, buttons, etc */
-input, textarea, .gr-textbox, .gr-slider, .gr-button, .gr-file, .gr-markdown, .gr-image {
-    background: rgba(255, 255, 255, 0.05) !important;
-    color: #ffffff !important;
-    border-radius: 8px !important;
-    border: 1px solid rgba(255, 255, 255, 0.1) !important;
-    backdrop-filter: blur(6px);
-    box-shadow: 0 4px 12px rgba(0, 0, 0, 0.2);
-}
+    gr.Markdown("# 🧠 TALENTPATCH with Multi-JD Comparison and AI Skill Gap Analysis")
 
-.gr-button {
-    background: linear-gradient(135deg, #00b4d8, #0077b6) !important;
-    color: #ffffff !important;
-    font-weight: bold;
-    letter-spacing: 0.8px;
-    border: none !important;
-    cursor: pointer;
-    text-transform: uppercase;
-    box-shadow: 0 4px 12px rgba(0, 183, 255, 0.3);
-}
+    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")
 
-.gr-button:hover {
-    background: linear-gradient(135deg, #0077b6, #00b4d8) !important;
-    box-shadow: 0 6px 20px rgba(0, 183, 255, 0.5);
-    transform: translateY(-2px);
-}
-</style>
-
-<!-- Floating Circle Elements -->
-<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")
-    gr.Markdown("Upload your **Resume PDF** and **Multiple Job Descriptions (PDFs)**. TALENTPATCH will compare and generate detailed reports with skill gap and recommendations.")
-
-    with gr.Row():
-        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")
-
-    submit_btn = gr.Button("🚀 Analyze Skill Gap")
-
-    match_slider = gr.Slider(minimum=0, maximum=100, step=1, label="Overall Skill Match (%)", interactive=False)
+    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)
     similarity_text = gr.Textbox(label="Status Message", interactive=False)
     report_output = gr.Textbox(label="AI-Generated Multi-JD Skill Gap Report", lines=20, interactive=False)
     download_pdf = gr.File(label="📥 Download Full Report as PDF")
     top_skills_output = gr.Textbox(label="Top Missing Skills Across JDs", interactive=False)
-    learning_resources = gr.Textbox(label="📚 AI Learning Resource Recommendations", 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],
+        inputs=[resume_file, jd_files, jd_link_input],
         outputs=[
-            match_slider, skill_match_text, missing_skills_text, similarity_text,
-            report_output, download_pdf, top_skills_output, learning_resources
+            match_progress,
+            skill_match_text,
+            missing_skills_text,
+            similarity_text,
+            report_output,
+            download_pdf,
+            top_skills_output,
+            learning_resources,
+            certification_output,
+            scraped_skills_output
         ]
     )