Update app.py

app.py

@@ -16,6 +16,24 @@ 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)
@@ -31,8 +49,31 @@ def extract_skills(text):
 def generate_learning_resources(missing_skills):
     suggestions = []
     for skill in missing_skills:
-        suggestions.append(f"For {skill}: Search for '{skill} tutorial' on YouTube, Coursera, or Udemy.")
-    return "\n".join(suggestions)
+        search_link = f"https://www.google.com/search?q={skill}+online+course"
+        youtube_link = f"https://www.youtube.com/results?search_query={skill}+tutorial"
+        suggestions.append(f"🔎 [{skill} Courses on Google]({search_link})\n▶️ [YouTube Tutorials]({youtube_link})\n")
+    return "\n\n".join(suggestions)
+
+def suggest_certifications(missing_skills):
+    cert_mapping = {
+        "Python": "Python for Everybody (Coursera)",
+        "Machine Learning": "Machine Learning by Andrew Ng (Coursera)",
+        "Cloud": "AWS Certified Solutions Architect",
+        "SQL": "Google Data Analytics Certificate",
+        "TensorFlow": "TensorFlow Developer Certificate",
+        "NLP": "Natural Language Processing Specialization (DeepLearning.AI)",
+        "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_skill_gap_report(user_skills, job_skills, missing_skills, match_percent):
     llm = ChatGroq(model="llama3-8b-8192", temperature=0.2)