changes

Joyal_CV.pdf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f426356195d6258f38880d8f151dd3c1b3ee3c12561d5bccfcd47f209d55da45
+size 133267

Nikita_Bansal.pdf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6aa258b56889c3cc673f8fc99a3a50b7b1c94bc66b88f94d1af2d8fd5cea8e84
+size 139526

Vineet_Goyal_Resume (4).pdf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d4a00d860cc55d529c20e0f5423e285fd7e509b2b124a54296b52b1f7eee44bb
+size 110750

agg.py

@@ -31,10 +31,26 @@ STUDENTS_TO_FETCH = [
         "github_user": "akshit7093",
         "codeforces_user": "akshit7093",
         "resume_path": "resume.pdf"  # REQUIRED FIELD
+    },
+    {
+        "enrollment_no": "35314811922",
+        "leetcode_user": "Nikita_06211",
+        "github_user": "Nikita06211",
+        "codeforces_user": "Nikita06211",
+        "resume_path": "Nikita_Bansal.pdf"
+    },
+    {
+        "enrollment_no": "05414811922",
+        "leetcode_user": "Vineet_Goyal10",
+        "github_user": "Vineetg2003",
+        "codeforces_user": "Nikita06211",
+        "resume_path": "Vineet_Goyal_Resume (4).pdf"
     }
+
     # Add more student dictionaries here
 ]
 
+
 OUTPUT_FILE = 'final_cleaned_student_data.json'
 
 # --- Advanced Cleaning and Filtering Functions ---
@@ -263,16 +279,41 @@ def main():
     ipu_scraper = StudentScraper(encryption_key="Qm9sRG9OYVphcmEK")
     all_student_data = {}
 
-    logger.info(f"Starting data aggregation for {len(STUDENTS_TO_FETCH)} student(s)...")
+    # Load existing data if output file exists
+    if os.path.exists(OUTPUT_FILE):
+        try:
+            with open(OUTPUT_FILE, 'r', encoding='utf-8') as f:
+                all_student_data = json.load(f)
+            logger.info(f"Loaded existing data for {len(all_student_data)} student(s) from '{OUTPUT_FILE}'.")
+        except Exception as e:
+            logger.warning(f"Could not load existing data: {e}. Starting fresh.")
+            all_student_data = {}
+    else:
+        logger.info(f"No existing output file found. Starting fresh.")
+
+    # Get set of already processed enrollment numbers
+    existing_enrollments = set(all_student_data.keys())
+
+    # Filter STUDENTS_TO_FETCH to only include unprocessed enrollments
+    students_to_process = [
+        student for student in STUDENTS_TO_FETCH
+        if student.get("enrollment_no") not in existing_enrollments
+    ]
+
+    if not students_to_process:
+        logger.info("✅ No new students to process. All enrollments already exist.")
+        return
+
+    logger.info(f"Starting data aggregation for {len(students_to_process)} new student(s)...")
 
-    for student in STUDENTS_TO_FETCH:
+    for student in students_to_process:
         enrollment_no = student.get("enrollment_no")
         if not enrollment_no:
             logger.warning("Skipping entry due to missing enrollment number.")
             continue
 
         logger.info(f"\nProcessing data for Enrollment No: {enrollment_no}")
-        
+
         student_record = {
             "name": None,
             "enrollment_no": enrollment_no,
@@ -282,7 +323,7 @@ def main():
                 "github": None,
                 "codeforces": None,
             },
-            "resume": None,  # NEW FIELD
+            "resume": None,
             "errors": {}
         }
 
@@ -312,7 +353,7 @@ def main():
             except Exception as e:
                 student_record["errors"]["leetcode"] = str(e)
                 logger.error(f"    > LeetCode processing FAILED: {e}")
-        
+
         if student.get("github_user"):
             try:
                 logger.info(f"  - Processing GitHub data for '{student['github_user']}'...")
@@ -338,31 +379,30 @@ def main():
             except Exception as e:
                 student_record["errors"]["codeforces"] = str(e)
                 logger.error(f"    > Codeforces processing FAILED: {e}")
-        
+
         # Process resume data
         if student.get("resume_path"):
             try:
                 logger.info(f"  - Processing resume from '{student['resume_path']}'...")
-                
-                # Check if file exists
+
                 if not os.path.exists(student["resume_path"]):
                     raise FileNotFoundError(f"Resume file not found at {student['resume_path']}")
-                
+
                 raw_resume_data = parse_resume(student["resume_path"])
                 student_record["resume"] = clean_resume_data(raw_resume_data)
                 logger.info("    > Resume data processed successfully.")
             except Exception as e:
                 student_record["errors"]["resume"] = str(e)
                 logger.error(f"    > Resume processing FAILED: {e}")
-        
+
         all_student_data[enrollment_no] = student_record
-        time.sleep(1)  # Respectful delay between requests
+        time.sleep(1)  # Respectful delay
 
-    # Save the final cleaned & aggregated data
+    # Save merged data (existing + new)
     try:
         with open(OUTPUT_FILE, 'w', encoding='utf-8') as f:
             json.dump(all_student_data, f, indent=4, ensure_ascii=False)
-        logger.info(f"\n✅ Final cleaning complete. Data saved to '{OUTPUT_FILE}'.")
+        logger.info(f"\n✅ Final data saved to '{OUTPUT_FILE}' ({len(all_student_data)} total students).")
     except Exception as e:
         logger.error(f"\n❌ Error saving final JSON file: {e}")
 

anshul santoshi final resume.pdf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:64e4cfb67315d599e1162b19d90a757ab681ed2aca31e9f7b2be14a230bdaa8c
+size 454596

app_copy.py

@@ -43,11 +43,39 @@ def test_frontend():
     return render_template('final.html') # Make sure index.html exists in templates/
 
 # --- Example route for students (adjust as needed) ---
+import json
+import os
+
 @app.route('/api/students', methods=['GET'])
 def get_students_list():
-    # Dummy implementation or integrate with your student data
-    # This is just an example, replace with actual logic
-    return jsonify([{"enrollment_no": "35214811922", "name": "Akshit Sharma"}])
+    enrollment_no = request.args.get('enrollment_no')  # Optional query param
+
+    # Path to your JSON file
+    json_path = 'final_cleaned_student_data.json'
+    
+    if not os.path.exists(json_path):
+        logger.error("Student data file not found.")
+        return jsonify({'error': 'Student data file not found.'}), 404
+
+    try:
+        with open(json_path, 'r', encoding='utf-8') as f:
+            all_students = json.load(f)
+
+        if enrollment_no:
+            # Return specific student if enrollment_no is provided
+            student = all_students.get(enrollment_no)
+            if not student:
+                logger.warning(f"Student with enrollment {enrollment_no} not found.")
+                return jsonify({'error': 'Student not found.'}), 404
+            return jsonify(student)
+        else:
+            # Return all students (values only, not keys)
+            print(all_students.values())
+            return jsonify(list(all_students.values()))
+
+    except Exception as e:
+        logger.error(f"Error reading student data: {e}", exc_info=True)
+        return jsonify({'error': 'Failed to load student data.'}), 500
 
 # --- Job Analysis Route (Corrected) ---
 @app.route('/api/job-analysis', methods=['POST'])
@@ -193,7 +221,7 @@ def get_student_report(enrollment_no: str):
              return jsonify(report_data), 404 # Or appropriate error code
         return jsonify(report_data)
     except Exception as e:
-        logger.error(f"Error generating report for {enrollment_no}: {e}", exc_info=True)
+        logger.error(f"Error generating report for {enrollment_no}: {e}",exc_info=True)
         return jsonify({'error': 'Failed to generate report.'}), 500
 
 

dashboard_analyzer.py

@@ -172,13 +172,29 @@ def _analyze_github(github_data: dict) -> dict:
     elif activity_level in ["Very Active", "Active"] or stats.get('public_repos', 0) > 10: rating = "Good Profile"
     return {"rating": rating, "activity_level": activity_level, "top_languages": top_languages, "stats": stats}
 
-def _extract_skills(student_data: dict) -> list:
-    """Extracts, combines, and cleans a list of key skills."""
+def _extract_skills(student_data: dict) -> dict: # MODIFIED to return a dict
+    """
+    Extracts, combines, cleans, and COUNTS key skills for chart display.
+    """
+    from collections import Counter
+
     resume_skills = student_data.get("resume", {}).get("key_skills", [])
-    leetcode_skills = [item.get("skill") for item in student_data.get("coding_profiles", {}).get("leetcode", {}).get("topSkillsSummary", [])]
+    leetcode_skills = [
+        item.get("skill") for item in student_data.get("coding_profiles", {}).get("leetcode", {}).get("topSkillsSummary", [])
+    ]
+    
+    # Normalize skills to title case for consistency
     normalized_resume = [s.strip().title() for s in resume_skills]
     normalized_leetcode = [s.strip().title() for s in leetcode_skills]
-    return list(dict.fromkeys(normalized_resume + normalized_leetcode))
+
+    # Combine and count occurrences (though here they are unique, this is a robust way to handle it)
+    all_skills = normalized_resume + normalized_leetcode
+    
+    # Using Counter will give a dict like {'Python': 2, 'Java': 1}, perfect for charts
+    # In this case, since we combine unique lists, counts will be 1 or 2, but it provides the right structure.
+    skill_counts = dict(Counter(all_skills))
+    
+    return skill_counts
 
 def _calculate_profile_completeness(student_data: dict) -> dict:
     """Scores the profile based on the presence of key data points."""

final_cleaned_student_data copy.json

@@ -0,0 +1,882 @@
+{
+    "35214811922": {
+        "name": "AKSHIT SHARMA",
+        "enrollment_no": "35214811922",
+        "academic_profile": {
+            "institute": "MAHARAJA AGRASEN INSTITUTE OF TECHNOLOGY",
+            "degree": "Bachelor of Technology",
+            "branch": "Artificial Intelligence and Data Science",
+            "overall_cgpa": 8.45,
+            "overall_percentage": 82.06,
+            "semester_performance": [
+                {
+                    "semester": 1,
+                    "sgpa": 7.72,
+                    "percentage": 73.7,
+                    "subjects": [
+                        {
+                            "subject": "ENVIRONMENTAL STUDIES LAB",
+                            "grade": "O",
+                            "marks": 92
+                        },
+                        {
+                            "subject": "ENGINEERING GRAPHICS-I",
+                            "grade": "O",
+                            "marks": 95
+                        },
+                        {
+                            "subject": "PROGRAMMING IN 'C' LAB",
+                            "grade": "O",
+                            "marks": 97
+                        },
+                        {
+                            "subject": "PHYSICS - I LAB",
+                            "grade": "A+",
+                            "marks": 80
+                        },
+                        {
+                            "subject": "MANUFACTURING PROCESS",
+                            "grade": "A",
+                            "marks": 70
+                        },
+                        {
+                            "subject": "COMMUNICATIONS SKILLS",
+                            "grade": "B+",
+                            "marks": 59
+                        },
+                        {
+                            "subject": "APPLIED MATHEMATICS - I",
+                            "grade": "B+",
+                            "marks": 57
+                        },
+                        {
+                            "subject": "ENVIRONMENTAL STUDIES",
+                            "grade": "A",
+                            "marks": 73
+                        },
+                        {
+                            "subject": "APPLIED PHYSICS - I",
+                            "grade": "C",
+                            "marks": 45
+                        },
+                        {
+                            "subject": "PROGRAMMING IN 'C'",
+                            "grade": "A",
+                            "marks": 69
+                        }
+                    ]
+                },
+                {
+                    "semester": 2,
+                    "sgpa": 6.8,
+                    "percentage": 71.08,
+                    "subjects": [
+                        {
+                            "subject": "WORKSHOP PRACTICE",
+                            "grade": "A+",
+                            "marks": 85
+                        },
+                        {
+                            "subject": "ELECTRICAL SCIENCE LAB",
+                            "grade": "A+",
+                            "marks": 78
+                        },
+                        {
+                            "subject": "ENGINEERING GRAPHICS - II",
+                            "grade": "A+",
+                            "marks": 87
+                        },
+                        {
+                            "subject": "APPLIED CHEMISTRY",
+                            "grade": "A+",
+                            "marks": 88
+                        },
+                        {
+                            "subject": "PHYSICS-II LAB",
+                            "grade": "O",
+                            "marks": 94
+                        },
+                        {
+                            "subject": "HUMAN VALUES AND ETHICS",
+                            "grade": "A+",
+                            "marks": 88
+                        },
+                        {
+                            "subject": "INDIAN CONSTITUTION",
+                            "grade": "A+",
+                            "marks": 80
+                        },
+                        {
+                            "subject": "ENGINEERING MECHANICS",
+                            "grade": "B",
+                            "marks": 52
+                        },
+                        {
+                            "subject": "APPLIED MATHEMATICS -II",
+                            "grade": "P",
+                            "marks": 43
+                        },
+                        {
+                            "subject": "ELECTRICAL SCIENCE",
+                            "grade": "B",
+                            "marks": 54
+                        },
+                        {
+                            "subject": "APPLIED PHYSICS - II",
+                            "grade": "B",
+                            "marks": 51
+                        },
+                        {
+                            "subject": "APPLIED CHEMISTRY",
+                            "grade": "B",
+                            "marks": 53
+                        }
+                    ]
+                },
+                {
+                    "semester": 3,
+                    "sgpa": 8.96,
+                    "percentage": 83.85,
+                    "subjects": [
+                        {
+                            "subject": "WEB PROGRAMMING LAB",
+                            "grade": "A+",
+                            "marks": 87
+                        },
+                        {
+                            "subject": "PRINCIPLES OF ARTIFICIAL INTELLIGENCE LAB",
+                            "grade": "O",
+                            "marks": 90
+                        },
+                        {
+                            "subject": "DIGITAL LOGIC DESIGN LAB",
+                            "grade": "O",
+                            "marks": 90
+                        },
+                        {
+                            "subject": "FOUNDATIONS OF DATA SCIENCE LAB",
+                            "grade": "O",
+                            "marks": 96
+                        },
+                        {
+                            "subject": "DATA STRUCTURES LAB",
+                            "grade": "O",
+                            "marks": 92
+                        },
+                        {
+                            "subject": "SELECTED READING",
+                            "grade": "O",
+                            "marks": 94
+                        },
+                        {
+                            "subject": "CRITICAL REASONING AND SYSTEMS THINKING",
+                            "grade": "A+",
+                            "marks": 81
+                        },
+                        {
+                            "subject": "UNIVERSAL HUMAN VALUES - II",
+                            "grade": "A+",
+                            "marks": 77
+                        },
+                        {
+                            "subject": "PROBABILITY, STATISTICS AND LINEAR ALGEBRA",
+                            "grade": "A+",
+                            "marks": 75
+                        },
+                        {
+                            "subject": "PRINCIPLES OF ARTIFICIAL INTELLIGENCE",
+                            "grade": "A",
+                            "marks": 66
+                        },
+                        {
+                            "subject": "DIGITAL LOGIC DESIGN",
+                            "grade": "A+",
+                            "marks": 86
+                        },
+                        {
+                            "subject": "FOUNDATIONS OF DATA SCIENCE",
+                            "grade": "A+",
+                            "marks": 87
+                        },
+                        {
+                            "subject": "DATA STRUCTURES",
+                            "grade": "A",
+                            "marks": 69
+                        }
+                    ]
+                },
+                {
+                    "semester": 4,
+                    "sgpa": 8.68,
+                    "percentage": 85.69,
+                    "subjects": [
+                        {
+                            "subject": "OBJECT ORIENTED PROGRAMMING",
+                            "grade": "A",
+                            "marks": 72
+                        },
+                        {
+                            "subject": "DATABASE MANAGEMENT SYSTEMS",
+                            "grade": "A+",
+                            "marks": 87
+                        },
+                        {
+                            "subject": "SOFTWARE ENGINEERING",
+                            "grade": "A",
+                            "marks": 74
+                        },
+                        {
+                            "subject": "COMPUTER NETWORKS AND INTERNET PROTOCOL",
+                            "grade": "A+",
+                            "marks": 75
+                        },
+                        {
+                            "subject": "FUNDAMENTALS OF MACHINE LEARNING",
+                            "grade": "A+",
+                            "marks": 78
+                        },
+                        {
+                            "subject": "COMPUTATIONAL METHODS",
+                            "grade": "B",
+                            "marks": 51
+                        },
+                        {
+                            "subject": "EFFECTIVE TECHNICAL WRITING",
+                            "grade": "O",
+                            "marks": 99
+                        },
+                        {
+                            "subject": "EMERGING TRENDS IN TECHNOLOGICAL INDUSTRIES",
+                            "grade": "O",
+                            "marks": 98
+                        },
+                        {
+                            "subject": "OBJECT ORIENTED PROGRAMMING LAB",
+                            "grade": "O",
+                            "marks": 95
+                        },
+                        {
+                            "subject": "DATABASE MANAGEMENT SYSTEMS LAB",
+                            "grade": "O",
+                            "marks": 94
+                        },
+                        {
+                            "subject": "COMPUTER NETWORKS AND INTERNET PROTOCOL LAB",
+                            "grade": "O",
+                            "marks": 98
+                        },
+                        {
+                            "subject": "FUNDAMENTALS OF MACHINE LERNING LAB",
+                            "grade": "O",
+                            "marks": 95
+                        },
+                        {
+                            "subject": "PRACTICUM (INTEGERATED PROJECT)",
+                            "grade": "O",
+                            "marks": 98
+                        }
+                    ]
+                },
+                {
+                    "semester": 5,
+                    "sgpa": 9.08,
+                    "percentage": 88.17,
+                    "subjects": [
+                        {
+                            "subject": "OPERATING SYSTEMS",
+                            "grade": "A+",
+                            "marks": 75
+                        },
+                        {
+                            "subject": "DESIGN AND ANALYSIS OF ALGORITHMS",
+                            "grade": "A",
+                            "marks": 66
+                        },
+                        {
+                            "subject": "DATA MINING",
+                            "grade": "A+",
+                            "marks": 82
+                        },
+                        {
+                            "subject": "COMPUTER ORGANIZATION AND ARCHITECTURE",
+                            "grade": "A+",
+                            "marks": 88
+                        },
+                        {
+                            "subject": "INTRODUCTION TO INTERNET OF THINGS",
+                            "grade": "A+",
+                            "marks": 81
+                        },
+                        {
+                            "subject": "PRINCIPLES OF ENTREPRENEURSHIP MINDSET",
+                            "grade": "A+",
+                            "marks": 80
+                        },
+                        {
+                            "subject": "OPERATING SYSTEMS LAB",
+                            "grade": "O",
+                            "marks": 99
+                        },
+                        {
+                            "subject": "DESIGN AND ANALYSIS OF ALGORITHMS LAB",
+                            "grade": "O",
+                            "marks": 96
+                        },
+                        {
+                            "subject": "DATA MINING LAB",
+                            "grade": "O",
+                            "marks": 93
+                        },
+                        {
+                            "subject": "INTRODUCTION TO INTERNET OF THINGS LAB",
+                            "grade": "O",
+                            "marks": 98
+                        },
+                        {
+                            "subject": "SUMMER TRAINING REPORT-1",
+                            "grade": "O",
+                            "marks": 100
+                        },
+                        {
+                            "subject": "SEMINAR ON CASE STUDY OF EMERGING AREAS OF TECHNOLOGY",
+                            "grade": "O",
+                            "marks": 100
+                        }
+                    ]
+                },
+                {
+                    "semester": 6,
+                    "sgpa": 9.38,
+                    "percentage": 88.55,
+                    "subjects": [
+                        {
+                            "subject": "DIGITAL IMAGE PROCESSING",
+                            "grade": "A",
+                            "marks": 73
+                        },
+                        {
+                            "subject": "BLOCKCHAIN TECHNOLOGY LAB",
+                            "grade": "O",
+                            "marks": 98
+                        },
+                        {
+                            "subject": "BLOCKCHAIN TECHNOLOGY",
+                            "grade": "A+",
+                            "marks": 76
+                        },
+                        {
+                            "subject": "FUNDAMENTALS OF DEEP LEARNING LAB",
+                            "grade": "O",
+                            "marks": 96
+                        },
+                        {
+                            "subject": "FUNDAMENTALS OF DEEP LEARNING",
+                            "grade": "A+",
+                            "marks": 84
+                        },
+                        {
+                            "subject": "BIG DATA ANALYTICS LAB",
+                            "grade": "O",
+                            "marks": 95
+                        },
+                        {
+                            "subject": "BIG DATA ANALYTICS",
+                            "grade": "O",
+                            "marks": 93
+                        },
+                        {
+                            "subject": "CRYPTOGRAPHY AND NETWORK SECURITY",
+                            "grade": "A+",
+                            "marks": 84
+                        },
+                        {
+                            "subject": "AI AND SUSTAINABLE COMPUTING",
+                            "grade": "O",
+                            "marks": 91
+                        },
+                        {
+                            "subject": "NSS/ NCC/ CULTURAL CLUBS/ TECHNICAL SOCIETY/ TECHNICAL CLUB",
+                            "grade": "O",
+                            "marks": 92
+                        },
+                        {
+                            "subject": "DIGITAL IMAGE PROCESSING LAB",
+                            "grade": "O",
+                            "marks": 92
+                        }
+                    ]
+                }
+            ]
+        },
+        "coding_profiles": {
+            "leetcode": {
+                "username": "akshitsharma7093",
+                "ranking": 2479447,
+                "totalSolved": 40,
+                "acceptanceRate": 64.08,
+                "problemsByDifficulty": {
+                    "Easy": "25/905",
+                    "Medium": "11/1927",
+                    "Hard": "4/874"
+                },
+                "primaryLanguage": {
+                    "languageName": "C++",
+                    "problemsSolved": 40
+                },
+                "topSkillsSummary": [
+                    {
+                        "skill": "Array",
+                        "solved": 22
+                    },
+                    {
+                        "skill": "String",
+                        "solved": 10
+                    },
+                    {
+                        "skill": "Hash Table",
+                        "solved": 8
+                    },
+                    {
+                        "skill": "Dynamic Programming",
+                        "solved": 7
+                    },
+                    {
+                        "skill": "Binary Search",
+                        "solved": 6
+                    },
+                    {
+                        "skill": "Math",
+                        "solved": 6
+                    },
+                    {
+                        "skill": "Recursion",
+                        "solved": 5
+                    },
+                    {
+                        "skill": "Two Pointers",
+                        "solved": 5
+                    },
+                    {
+                        "skill": "Tree",
+                        "solved": 4
+                    },
+                    {
+                        "skill": "Depth-First Search",
+                        "solved": 4
+                    },
+                    {
+                        "skill": "Stack",
+                        "solved": 4
+                    },
+                    {
+                        "skill": "Segment Tree",
+                        "solved": 3
+                    },
+                    {
+                        "skill": "Binary Tree",
+                        "solved": 3
+                    },
+                    {
+                        "skill": "Sliding Window",
+                        "solved": 3
+                    },
+                    {
+                        "skill": "Linked List",
+                        "solved": 3
+                    }
+                ],
+                "activity": {
+                    "currentStreak": 8,
+                    "totalActiveDays": 31
+                },
+                "recentSubmissions": [
+                    {
+                        "title": "Binary Tree Inorder Traversal",
+                        "timestamp": "2025-09-19"
+                    },
+                    {
+                        "title": "Binary Tree Preorder Traversal",
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+        "resume": {
+            "full_text": "Akshit Sharma \nFinal‑Year B.Tech (AI & Data Science) | Backend & AI/ML Engineer | Cloud‑Native Systems \nakshitsharma7096@gmail.com/ +91 8810248097/Github / Linkedin / LeetCode / CodeForces \nSKILLS\n \n●​\nProgramming Languages: Python, Java, C/C++, JavaScript, SQL, React, Node.js, TypeScript, Flask, FastAPI \n●​\nDatabases & Tools: Pandas, NumPy, Matplotlib, MongoDB, Postgre \n●​\nML/AI & Frameworks: TensorFlow, PyTorch, NLP, Computer Vision, Transformers, RAG, LangChain \n●​\nCloud & DevOps: AWS, Google Cloud Platform, OpenStack SDK, Docker, Kubernetes \n●​\nSystems & Fundamentals: Unix/Linux, TCP/IP Networking, Git, Data Structures & Algorithms, Computer Networks \nEXPERIENCE\n \nResearch Intern | Directorate of Research, Government of Arunachal Pradesh​\n​\n                    \n(August  2025 – Present) \n●​\nDeveloped a low-resource speech-to-speech translation pipeline using Wav2Vec 2.0 for ASR, MarianMT for NMT, and Tacotron 2 \nfor TTS, focusing on endangered languages with context-dependent meanings. \n●​\nOptimised system architecture to reduce translation latency to under 2 seconds, enabling real time deployment for field use. \nDeep Learning Intern | Akanila Technologies ​ ​\n                        https://github.com/akshit7093/Chatbot-for-websites \n(July 2024 – December 2024) \n●​\nDeveloped a universal chatbot platform by fine‑tuning Llama3.1 LLM using LoRA and integrating RAG with FAISS for \ndomain‑specific retrieval, boosting query accuracy to 90 % and improving response relevance by 25 %. \n●​\nDesigned a flexible Python backend with modular components in FastAPI increasing code reusability to 65% . \n●​\nImplemented automated deployments on AWS EC2, leveraging Docker for containerization and Kubernetes for container \norchestration. \nMachine Learning Intern | CodSoft                            ​\n        https://github.com/akshit7093/CODSOFT \n(August 2024 – September 2024) \n●​\nDeveloped a credit card fraud detection system using XGBoost, analyzing 1 million transaction records. \n●​\nEngineered 20+ features from behavioral and time-series data then trained an XGBoost model on SageMaker to drop false \npositives from 20% to 5% while keeping recall over 90%. \n●​\nBuilt an NLP model for SMS spam detection using Python and scikit-learn, achieving 95% accuracy on test data. \nPROJECT\n \nOpenStack Cloud Management System with Natural Language Interface          https://github.com/akshit7093/VM_manager_AgenticAi \n●​\nBuilt a cloud management system interfacing with OpenStack infrastructure APIs. \n●​\nEnabled users to issue natural language prompts (e.g., \"create a server\" or \"delete a volume\"), which an AI agent created using \nLangChain and Google's Gemini-2.5 pro model translated into precise OpenStack API calls. \n●​\nBuilt an interactive CLI and a web app for remote management, featuring resource analytics and container monitoring per VM. \n●​\nDesigned RESTful backend with Fastapi and containerized the application using Docker. \n●​\nTechnologies: Python, OpenStack SDK, Gemini, Fastapi, Docker, LangChain \nSignEase -Video calling platform for individuals with disabilities​                        https://github.com/akshit7093/Sign-language-translator.git \n●​\nCreated a video chat application using React and Node.js to enable video communication with ASL translation. \n●​\nImplemented American Sign Language (ASL) detection using MediaPipe for landmarks and an LSTM network in TensorFlow, \nreaching 89% accuracy on a small dataset of 20 videos. \n●​\nReduced latency from 500ms to 180ms using model quantization (TensorFlow Lite) and frame-rate optimization. \n●​\nTechnologies: Python, TensorFlow, WebRTC, React, Node.js, MediaPipe. \nEDUCATION \n \nMaharaja Agrasen Institute of Technology​\n​\n​\n​\n​\n​\n​\n(June 2022 - June 2026) \n●​\nB.Tech. in Computer Science with a specialization in Artificial Intelligence and Data Science \n●​\nCGPA:8.96/10 ​\n​\n​\n​\n​\n​\n​\n​\n  \n●​\nRelevant Coursework: Machine Learning, Data Mining, Image Processing, Data Structures and Algorithms, Computer Networks \nCERTIFICATIONS \n \n●​\nData Science (Pwskills) \n●​\nMachine Learning and Deep Learning Specialization (Coursera) \n●​\nAWS Solutions Architect Virtual Experience Program (Forage)  \n●​\nIntroduction to Generative AI (Google) \n●​\nDevelop GenAI Apps with Gemini and Streamlit (Google) \n●​\nPrompt Design in Vertex AI (Google) \nACHIEVEMENTS \n \n●​\nWinner – AceCloud X RTDS Hackathon ‘25",
+            "full_text_preview": "Akshit Sharma \nFinal‑Year B.Tech (AI & Data Science) | Backend & AI/ML Engineer | Cloud‑Native Systems \nakshitsharma7096@gmail.com/ +91 8810248097/Github / Linkedin / LeetCode / CodeForces \nSKILLS\n \n●​\nProgramming Languages: Python, Java, C/C++, JavaScript, SQL, React, Node.js, TypeScript, Flask, FastAPI \n●​\nDatabases & Tools: Pandas, NumPy, Matplotlib, MongoDB, Postgre \n●​\nML/AI & Frameworks: TensorFlow, PyTorch, NLP, Computer Vision, Transformers, RAG, LangChain \n●​\nCloud & DevOps: AWS, Google...",
+            "professional_links": [
+                "mailto:akshitsharma7096@gmail.com",
+                "https://github.com/akshit7093",
+                "https://www.linkedin.com/in/akshit-sharma-475a94271/",
+                "https://leetcode.com/u/akshitsharma7093/",
+                "https://codeforces.com/profile/akshit7093",
+                "https://github.com/akshit7093/Chatbot-for-websites",
+                "https://github.com/akshit7093/CODSOFT",
+                "https://github.com/akshit7093/VM_manager_AgenticAi",
+                "https://github.com/akshit7093/Sign-language-translator.git",
+                "https://www.cloudskillsboost.google/public_profiles/1b626606-8403-4450-9b1a-dbba876587d7/badges/9194948",
+                "https://www.cloudskillsboost.google/public_profiles/1b626606-8403-4450-9b1a-dbba876587d7/badges/9194066",
+                "https://www.cloudskillsboost.google/public_profiles/1b626606-8403-4450-9b1a-dbba876587d7/badges/9140322",
+                "https://drive.google.com/file/d/1OeO7jFd7le1gg_6I0oBGjmsBIfA50p73/view?usp=sharing"
+            ],
+            "skills_summary": "Akshit Sharma FinalYear B.Tech (AI  Data Science)  Backend  AIML Engineer  CloudNative Systems akshitsharma7096gmail.com 91 8810248097Github  Linkedin  LeetCode  CodeForces SKILLS  Programming Languages: Python, Java, CC, JavaScript, SQL, React, Node.js, TypeScript, Flask, FastAPI  Databases  Tools: Pandas, NumPy, Matplotlib, MongoDB, Postgre  MLAI  Frameworks: TensorFlow, PyTorch, NLP, Computer Vision, Transformers, RAG, LangChain  Cloud  DevOps: AWS, Google Cloud Platform, OpenStack SDK, Docker, Kubernetes  Systems  Fundamentals: UnixLinux, TCPIP Networking, Git, Data Structures  Algorithms, Computer Networks EXPERIENCE Research Intern  Directorate of Research, Government of Arunachal Pradesh  (August 2025  Present)  Developed a low-resource speech-to-speech translation pipeline using Wav2Vec 2.0 for ASR, MarianMT for NMT, and Tacotron 2 for TTS, focusing on endangered languages with context-dependent meanings.  Optimised system architecture to reduce translation latency to under 2 seconds, enabling real time deployment for field use. Deep Learning Intern  Akanila Technologies   https:github.comakshit7093Chatbot-for-websites (July 2024  December 2024)  Developed a universal chatbot platform by finetuning Llama3.1 LLM using LoRA and integrating RAG with FAISS for domainspecific retrieval, boosting query accuracy to 90  and improving response relevance by 25 .  Designed a flexible Python...",
+            "key_skills": [
+                "Python",
+                "Java",
+                "Javascript",
+                "React",
+                "Node",
+                "Sql",
+                "Mongodb",
+                "Aws",
+                "Docker",
+                "Kubernetes",
+                "Git",
+                "C++",
+                "Typescript",
+                "Flask",
+                "Tensorflow",
+                "Pytorch",
+                "Data structures",
+                "Algorithms",
+                "Backend"
+            ],
+            "total_hyperlinks": 13,
+            "professional_link_count": 13,
+            "missing_elements": []
+        },
+        "errors": {}
+    }
+}

rohanmaincv.pdf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c9368773767bb6a002c9bf6af8576b33ab1a59282409104bd5841a703b8d6335
+size 166820

static/final.css

@@ -8,6 +8,9 @@
     --text-color-muted: #8A8A8A; /* Dimmer text for labels/placeholders */
     --accent-color: #00E5FF; /* Vibrant cyan/teal for highlights */
     --accent-color-hover: #00B8CC;
+    --success-color: #4ade80; /* Green for positive elements */
+    --warning-color: #facc15; /* Amber for warnings */
+    --danger-color: #f87171; /* Red for errors */
     --font-family: 'Inter', sans-serif;
 }
 
@@ -39,6 +42,9 @@ h3 {
     font-size: 1.1rem;
     margin-bottom: 12px;
     color: var(--text-color);
+    /* Ensure title stays above the absolutely positioned canvas */
+    position: relative;
+    z-index: 2;
 }
 
 a {
@@ -204,30 +210,20 @@ input[type="text"]::placeholder {
     color: var(--text-color-muted);
 }
 
-
 /* --- Content Sections & Cards --- */
 .content-section.hidden {
     display: none;
 }
 
 .card {
-    background: rgba(26, 26, 26, 0.7); /* The semi-transparent panel color for the gloss effect */
-    backdrop-filter: blur(10px); /* The "frosted glass" effect */
+    background: rgba(26, 26, 26, 0.7);
+    backdrop-filter: blur(10px);
     border: 1px solid var(--border-color);
     border-radius: 16px;
     padding: 24px;
 }
 
-.chart-placeholder {
-    display: flex;
-    align-items: center;
-    justify-content: center;
-    height: 100%;
-    color: var(--text-color-muted);
-    font-size: 1.2rem;
-}
-
-/* --- Dashboard --- */
+/* --- Dashboard & Chart Fix --- */
 .dashboard-grid {
     display: grid;
     grid-template-columns: repeat(3, 1fr);
@@ -253,6 +249,26 @@ input[type="text"]::placeholder {
     color: var(--accent-color);
 }
 
+.chart-row {
+    grid-column: 1 / -1; /* Span full width of the grid */
+    display: grid;
+    grid-template-columns: repeat(2, 1fr);
+    gap: 24px;
+}
+
+/* CORRECTED CHART CONTAINER STYLES */
+.chart-container {
+    position: relative; /* This is the key: creates a positioning context for the canvas */
+    min-height: 350px; /* Give the container a minimum height */
+}
+
+.chart-container canvas {
+    position: absolute; /* Takes the canvas out of the layout flow */
+    top: 60px;          /* Leave space for the h3 title */
+    left: 24px;         /* Align with the card's left padding */
+    width: calc(100% - 48px) !important;  /* Fill container width, respecting padding */
+    height: calc(100% - 84px) !important; /* Fill container height, respecting title space and padding */
+}
 
 /* --- Report & Job Analysis Grids --- */
 .report-grid, .job-analysis-grid {
@@ -273,11 +289,158 @@ input[type="text"]::placeholder {
     font-size: 0.85rem;
 }
 
+/* --- Job Listings Page Specific Styles --- */
+.job-listings-container {
+    display: flex;
+    flex-direction: column;
+    gap: 20px;
+    margin-top: 20px;
+}
+
+.info-panel {
+    background: rgba(26, 26, 26, 0.7);
+    backdrop-filter: blur(10px);
+    border: 1px solid var(--border-color);
+    border-radius: 16px;
+    padding: 20px;
+    transition: var(--transition);
+}
+
+.info-panel h3 {
+    color: var(--accent-color);
+    margin-bottom: 10px;
+    font-size: 1.2rem;
+}
+
+.info-panel p {
+    margin-bottom: 8px;
+    color: var(--text-color);
+    line-height: 1.5;
+}
+
+.job-listings-tabs {
+    display: flex;
+    gap: 10px;
+    margin-bottom: 15px;
+}
+
+.tab-btn {
+    padding: 12px 24px;
+    border-radius: 12px 12px 0 0;
+    font-weight: 600;
+    color: var(--text-color-muted);
+    background: var(--input-bg);
+    border: 1px solid var(--border-color);
+    border-bottom: none;
+    cursor: pointer;
+    transition: var(--transition);
+    flex-grow: 1;
+    text-align: center;
+    font-size: 0.95rem;
+}
+
+.tab-btn:hover {
+    background: var(--panel-color);
+}
+
+.tab-btn.active {
+    color: var(--text-color);
+    background: var(--panel-color);
+    border-color: var(--accent-color);
+    border-bottom: 2px solid var(--accent-color);
+}
+
+.job-category-section {
+    display: flex;
+    flex-direction: column;
+    gap: 20px;
+    background: var(--panel-color);
+    border: 1px solid var(--border-color);
+    border-radius: 0 12px 12px 12px; /* Rounded top removed to connect with tabs */
+    padding: 20px;
+}
+
+.job-category-section h3 {
+    font-size: 1.2rem;
+    margin-bottom: 10px;
+    color: var(--accent-color);
+    padding-bottom: 8px;
+    border-bottom: 1px solid var(--border-color);
+}
+
+.job-listings-grid {
+    display: grid;
+    grid-template-columns: repeat(auto-fill, minmax(320px, 1fr));
+    gap: 20px;
+    margin-bottom: 20px;
+}
+
+.job-card {
+    background: rgba(44, 44, 44, 0.5); /* Slightly lighter than panel */
+    border: 1px solid var(--border-color);
+    border-radius: 12px;
+    padding: 20px;
+    transition: var(--transition);
+    display: flex;
+    flex-direction: column;
+    height: 100%; /* Ensure cards in a row are the same height */
+}
+
+.job-card:hover {
+    transform: translateY(-5px);
+    box-shadow: 0 10px 15px -3px rgba(0, 0, 0, 0.1), 0 4px 6px -2px rgba(0, 0, 0, 0.05);
+    border-color: var(--accent-color);
+}
+
+.job-card h4 {
+    margin: 0 0 10px 0;
+    color: var(--text-color);
+    font-size: 1.1rem;
+}
+
+.job-card .company {
+    font-weight: 600;
+    color: var(--accent-color);
+    margin: 0 0 5px 0;
+    font-size: 1rem;
+}
+
+.job-card .location,
+.job-card .type {
+    font-size: 0.9rem;
+    color: var(--text-color-muted);
+    margin: 3px 0;
+}
+
+.job-card .aligns-with {
+    color: var(--success-color);
+    font-size: 0.85rem;
+    font-style: italic;
+    margin: 8px 0;
+    font-weight: 500;
+}
+
+.job-card .mismatch {
+    color: var(--danger-color);
+    font-size: 0.85rem;
+    font-style: italic;
+    margin: 8px 0;
+    font-weight: 500;
+}
+
+.apply-btn {
+    margin-top: auto; /* Push button to the bottom */
+    align-self: flex-start; /* Align button to the left */
+    margin-top: 15px;
+    padding: 8px 16px; /* Slightly smaller padding for consistency */
+    font-size: 0.9rem;
+}
+
 /* --- Chat Interface --- */
 .chat-container {
     display: flex;
     flex-direction: column;
-    height: 70vh; /* Adjust height as needed */
+    height: 70vh;
     padding: 0;
 }
 
@@ -328,7 +491,6 @@ input[type="text"]::placeholder {
     white-space: pre-wrap;
 }
 
-
 /* --- Loading Spinner --- */
 .loading-overlay {
     position: fixed;
@@ -366,84 +528,139 @@ input[type="text"]::placeholder {
 .hidden {
     display: none !important;
 }
-/* Add these rules to your existing final.css */
 
-/* Ensure the chart containers have a defined size */
-.chart-container {
-    /* You can adjust these values as needed */
-    min-height: 300px; /* Set a minimum height */
-    /* Optional: Set a max-height if needed */
-    /* max-height: 400px; */
-    /* Ensure the canvas fills the container */
-    display: flex;
-    flex-direction: column; /* Stack chart title and canvas vertically */
-    justify-content: center; /* Center the chart vertically if needed */
-    align-items: center;   /* Center the chart horizontally */
-    position: relative; /* Needed for Chart.js responsiveness */
+/* --- Responsive Adjustments --- */
+@media (max-width: 1200px) {
+    .app-container {
+        grid-template-columns: 200px 1fr; /* Slimmer sidebar */
+    }
+    .main-content {
+        padding: 24px;
+    }
 }
 
-/* Ensure the canvas elements themselves have a defined size */
-.chart-container canvas {
-    width: 100% !important; /* Override any inline styles Chart.js might add */
-    height: 100% !important; /* Override any inline styles Chart.js might add */
-    max-width: 100%; /* Prevent overflow */
-    max-height: 100%; /* Prevent overflow */
+@media (max-width: 992px) {
+    .app-container {
+        grid-template-columns: 1fr; /* Stack sidebar and content */
+    }
+    .sidebar {
+        /* This example hides the sidebar, but you could make it a toggleable menu */
+        display: none;
+    }
+    .dashboard-grid, .chart-row, .report-grid, .job-analysis-grid, .job-listings-grid {
+        grid-template-columns: 1fr; /* Single column layout for cards */
+    }
+    .large-card {
+        grid-column: 1 / -1; /* Ensure it spans the single column */
+        grid-row: auto;
+    }
+    .metric-cards-grid {
+        grid-column: 1 / -1;
+        grid-template-columns: repeat(auto-fit, minmax(150px, 1fr));
+    }
+    .top-bar {
+        flex-direction: column;
+        align-items: stretch;
+    }
+    .job-listings-grid {
+        grid-template-columns: 1fr; /* Single column for job cards on smaller screens */
+    }
+    .job-category-section {
+        border-radius: 12px; /* Restore full border radius when tabs are above */
+    }
+    .job-listings-tabs {
+        flex-wrap: wrap; /* Allow tabs to wrap if needed */
+    }
+}
+/* --- Students Section --- */
+.students-container {
+    margin-top: 20px;
 }
 
-/* Optional: Style the placeholder text if no data is shown */
-.chart-placeholder {
-    display: flex;
-    align-items: center;
-    justify-content: center;
+.students-container .card {
+    padding: 0; /* Remove default card padding for full table width */
+    overflow: hidden; /* Contain shadows/borders */
+}
+
+.students-container h3 {
+    padding: 24px 24px 12px 24px; /* Match card padding */
+    margin: 0;
+    border-bottom: 1px solid var(--border-color);
+}
+
+.table-responsive {
+    overflow-x: auto;
     width: 100%;
-    height: 100%;
-    color: var(--gray); /* Use your defined CSS variable */
+}
+
+.students-table {
+    width: 100%;
+    border-collapse: collapse;
+    margin: 0;
+}
+
+.students-table thead {
+    background-color: var(--input-bg);
+}
+
+.students-table th,
+.students-table td {
+    padding: 16px 24px;
+    text-align: left;
+    border-bottom: 1px solid var(--border-color);
+}
+
+.students-table th {
+    font-weight: 600;
+    color: var(--text-color);
+    font-size: 0.9rem;
+    text-transform: uppercase;
+    letter-spacing: 0.5px;
+}
+
+.students-table tbody tr:last-child td {
+    border-bottom: none;
+}
+
+.students-table tbody tr:hover {
+    background-color: rgba(255, 255, 255, 0.05);
+}
+
+.students-table td {
+    color: var(--text-color);
+    font-size: 1rem;
+}
+
+.select-student-btn {
+    padding: 6px 12px;
+    font-size: 0.85rem;
+}
+
+/* --- Messages within Students Section --- */
+#students-loading-message,
+#students-error-message {
+    padding: 24px;
+    text-align: center;
     font-style: italic;
 }
 
-/* Adjust the grid layout if necessary */
-.dashboard-grid {
-    display: grid;
-    grid-template-columns: 1fr; /* Default to single column */
-    gap: 20px;
-    margin-top: 20px;
+#students-loading-message {
+    color: var(--text-color-muted);
 }
 
-.metric-cards-grid {
-    display: grid;
-    grid-template-columns: repeat(auto-fit, minmax(200px, 1fr)); /* Adjust minmax width as needed */
-    gap: 20px;
-    margin-bottom: 20px; /* Space below the metric row */
+#students-error-message {
+    color: var(--danger-color);
 }
 
-/* Responsive grid for dashboard sections */
-@media (min-width: 992px) {
-    .dashboard-grid {
-        grid-template-columns: 1fr 1fr; /* Two columns for most dashboard items */
-    }
-    .metric-cards-grid {
-        grid-column: span 2; /* Metrics span full width */
-    }
-    .large-card {
-        grid-column: span 2; /* Large card spans 2 columns */
-    }
-    .chart-row {
-        grid-column: span 2; /* Chart row spans 2 columns */
-        display: grid;
-        grid-template-columns: 1fr 1fr; /* Two charts side-by-side within the row */
-        gap: 20px;
-    }
-    .chart-container {
-        /* Remove min-height from individual containers if using chart-row */
-        min-height: auto;
-    }
+.hidden {
+    display: none !important;
 }
 
-/* Fallback for smaller screens */
-@media (max-width: 991px) {
-    .chart-row {
-        display: grid;
-        grid-template-columns: 1fr; /* Charts stack vertically on smaller screens */
-        gap: 20px;
-    }
-}
+/* Optional: Style the "Select" button if needed differently */
+/* .select-student-btn.btn-secondary {
+    background-color: #444;
+    border-color: #555;
+}
+.select-student-btn.btn-secondary:hover:not(:disabled) {
+    background-color: #555;
+} */

static/final.js

@@ -681,7 +681,8 @@ document.addEventListener('DOMContentLoaded', () => {
 
                 skillsChart = new Chart(skillsCtx, {
                     type: 'bar', // or 'doughnut', 'pie', etc.
-                     {
+                    // CORRECTED: Added the 'data' key for the chart data object
+                    data: {
                         labels: labels,
                         datasets: [{
                             label: 'Skill Count',
@@ -728,7 +729,8 @@ document.addEventListener('DOMContentLoaded', () => {
                 // For simplicity, let's use a bar chart here showing score out of 10
                 dsaChart = new Chart(dsaCtx, {
                     type: 'bar', // Could be 'radar', 'doughnut' for score
-                     {
+                    // CORRECTED: Added the 'data' key for the chart data object
+                    data: {
                         labels: ['DSA Score'],
                         datasets: [{
                             label: 'DSA Performance (0-10)',
@@ -801,7 +803,8 @@ document.addEventListener('DOMContentLoaded', () => {
         const messageP = document.createElement('p');
         // Apply markdown formatting if the flag is true (e.g., for AI responses)
         if (useMarkdown) {
-            messageP.innerHTML = text; // Use innerHTML to render the formatted HTML
+            // CORRECTED: Call the conversion function to turn markdown into HTML
+            messageP.innerHTML = convertMarkdownToHTML(text);
         } else {
             messageP.textContent = text; // Use textContent for plain text (e.g., user messages, loading)
         }

static/job_listings.css

@@ -0,0 +1,119 @@
+/* job_listings.css */
+
+.job-listings-container {
+    display: flex;
+    flex-direction: column;
+    gap: 20px;
+    margin-top: 20px;
+}
+
+.info-panel {
+    background: var(--bg-panel);
+    border-radius: var(--panel-radius);
+    padding: 15px 20px;
+    box-shadow: var(--panel-shadow);
+    border: 1px solid var(--border-panel);
+    transition: var(--transition);
+}
+
+.info-panel h3 {
+    color: var(--primary);
+    margin-bottom: 10px;
+}
+
+.info-panel p {
+    margin-bottom: 8px;
+    color: var(--text-secondary);
+}
+
+.job-listings-tabs {
+    display: flex;
+    gap: 10px;
+    margin-bottom: 15px;
+}
+
+.tab-btn {
+    padding: 10px 20px;
+    border-radius: 8px 8px 0 0;
+    font-weight: 600;
+    color: var(--gray);
+    background: var(--border-panel);
+    border: 1px solid var(--border-panel);
+    cursor: pointer;
+    transition: var(--transition);
+    flex-grow: 1;
+    text-align: center;
+}
+
+.tab-btn.active {
+    color: var(--primary);
+    background: var(--bg-panel);
+    border-bottom: 2px solid var(--primary);
+}
+
+.job-category-section {
+    display: flex;
+    flex-direction: column;
+    gap: 20px;
+}
+
+.job-listings-grid {
+    display: grid;
+    grid-template-columns: repeat(auto-fill, minmax(300px, 1fr));
+    gap: 20px;
+    margin-bottom: 20px;
+}
+
+.job-card {
+    background: var(--bg-panel);
+    border-radius: var(--panel-radius);
+    padding: 15px;
+    box-shadow: var(--panel-shadow);
+    border: 1px solid var(--border-panel);
+    transition: var(--transition);
+    display: flex;
+    flex-direction: column;
+}
+
+.job-card:hover {
+    transform: translateY(-2px);
+    box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
+}
+
+.job-card h4 {
+    margin: 0 0 10px 0;
+    color: var(--text-primary);
+}
+
+.job-card .company {
+    font-weight: 600;
+    color: var(--primary);
+    margin: 0;
+}
+
+.job-card .location,
+.job-card .type {
+    font-size: 0.9rem;
+    color: var(--gray);
+    margin: 5px 0;
+}
+
+.job-card .aligns-with {
+    color: var(--success);
+    font-size: 0.85rem;
+    font-style: italic;
+    margin: 5px 0;
+}
+
+.job-card .mismatch {
+    color: var(--danger);
+    font-size: 0.85rem;
+    font-style: italic;
+    margin: 5px 0;
+}
+
+.apply-btn {
+    margin-top: auto; /* Push button to the bottom */
+    align-self: flex-start; /* Align button to the left */
+    margin-top: 10px;
+}

static/job_listings.js

@@ -0,0 +1,241 @@
+// job_listings.js
+
+document.addEventListener('DOMContentLoaded', () => {
+    // --- DOM Elements ---
+    const jobListingsSection = document.getElementById('job-listings');
+    const tabButtons = document.querySelectorAll('.tab-btn');
+    const jobCategorySections = document.querySelectorAll('.job-category-section');
+    const studentSelector = document.getElementById('student-selector');
+
+    // --- Sample Job Listings Data (Simulated) ---
+    const sampleJobs = [
+        // --- On-Campus Jobs ---
+        {
+            id: 1,
+            title: "Software Engineer Intern",
+            company: "TechCorp",
+            location: "New Delhi, India",
+            type: "On-Campus",
+            description: "Internship for software development.",
+            requiredSkills: ["Python", "React", "DSA", "JavaScript"]
+        },
+        {
+            id: 2,
+            title: "Data Analyst",
+            company: "DataInsights Inc.",
+            location: "Gurgaon, India",
+            type: "On-Campus",
+            description: "Role involving data analysis and visualization.",
+            requiredSkills: ["Python", "SQL", "Tableau", "Statistics"]
+        },
+        {
+            id: 3,
+            title: "Frontend Developer",
+            company: "WebSolutions",
+            location: "Mumbai, India",
+            type: "On-Campus",
+            description: "Build user interfaces using modern frameworks.",
+            requiredSkills: ["JavaScript", "React", "CSS", "HTML", "Vue.js"]
+        },
+        {
+            id: 4,
+            title: "QA Engineer",
+            company: "QualityFirst Ltd.",
+            location: "Pune, India",
+            type: "On-Campus",
+            description: "Ensure software quality through testing.",
+            requiredSkills: ["Manual Testing", "Automation Testing", "Selenium", "JIRA"]
+        },
+        {
+            id: 5,
+            title: "DevOps Associate",
+            company: "CloudBridge",
+            location: "Hyderabad, India",
+            type: "On-Campus",
+            description: "Support CI/CD pipelines and cloud infrastructure.",
+            requiredSkills: ["Linux", "Docker", "CI/CD", "AWS Basics"]
+        },
+
+        // --- Off-Campus Jobs ---
+        {
+            id: 6,
+            title: "Backend Developer",
+            company: "CloudStartups",
+            location: "Bangalore, India",
+            type: "Off-Campus",
+            description: "Develop and maintain server-side applications.",
+            requiredSkills: ["Node.js", "AWS", "SQL", "REST APIs", "MongoDB"]
+        },
+        {
+            id: 7,
+            title: "Machine Learning Engineer",
+            company: "AIFrontiers",
+            location: "Chennai, India",
+            type: "Off-Campus",
+            description: "Design and deploy ML models for real-world problems.",
+            requiredSkills: ["Python", "ML", "TensorFlow", "PyTorch", "Scikit-learn"]
+        },
+        {
+            id: 8,
+            title: "Full Stack Developer",
+            company: "AppVenture",
+            location: "Remote",
+            type: "Off-Campus",
+            description: "Work on both frontend and backend of web applications.",
+            requiredSkills: ["JavaScript", "React", "Node.js", "Express", "PostgreSQL", "Docker"]
+        },
+        {
+            id: 9,
+            title: "Cybersecurity Specialist",
+            company: "SecureNet",
+            location: "Kolkata, India",
+            type: "Off-Campus",
+            description: "Protect systems and networks from cyber threats.",
+            requiredSkills: ["Network Security", "Ethical Hacking", "SIEM Tools", "Incident Response"]
+        },
+        {
+            id: 10,
+            title: "Mobile App Developer",
+            company: "MobileMasters",
+            location: "Jaipur, India",
+            type: "Off-Campus",
+            description: "Develop cross-platform mobile applications.",
+            requiredSkills: ["Flutter", "Dart", "Firebase", "iOS", "Android"]
+        }
+        // Add more sample jobs here if needed
+    ];
+
+    // --- Sample Student Profile Data (Simulated) ---
+    // This should ideally come from the main application state or be fetched based on the selected student
+    // Example profile matching some jobs, missing others
+    const sampleStudentProfile = {
+        keySkills: ["Python", "JavaScript", "React", "Node.js", "SQL", "DSA", "Git", "HTML", "CSS"] // Example skills from resume
+    };
+
+    // --- Tab Switching Logic ---
+    tabButtons.forEach(button => {
+        button.addEventListener('click', () => {
+            const targetCategory = button.getAttribute('data-category');
+
+            // Update active tab button
+            tabButtons.forEach(btn => btn.classList.remove('active'));
+            button.classList.add('active');
+
+            // Show corresponding category section, hide others
+            jobCategorySections.forEach(section => {
+                if (section.getAttribute('data-category') === targetCategory) {
+                    section.classList.remove('hidden');
+                } else {
+                    section.classList.add('hidden');
+                }
+            });
+
+            // Load jobs for the active tab
+            loadJobsForCategory(targetCategory);
+        });
+    });
+
+    // --- Function to Load Jobs for a Category ---
+    function loadJobsForCategory(category) {
+        console.log(`Loading jobs for category: ${category}`);
+        // Clear existing listings
+        const recommendedContainer = document.getElementById(`${category}-recommended-listings`);
+        const nonRecommendedContainer = document.getElementById(`${category}-non-recommended-listings`);
+        if (recommendedContainer) recommendedContainer.innerHTML = '';
+        if (nonRecommendedContainer) nonRecommendedContainer.innerHTML = '';
+
+        // Filter jobs by category
+        const categoryJobs = sampleJobs.filter(job => job.type.toLowerCase().includes(category));
+
+        // Categorize jobs based on recommendation logic
+        const recommendedJobs = [];
+        const nonRecommendedJobs = [];
+
+        categoryJobs.forEach(job => {
+            if (isJobRecommended(job, sampleStudentProfile)) {
+                recommendedJobs.push(job);
+            } else {
+                nonRecommendedJobs.push(job);
+            }
+        });
+
+        // Populate the UI
+        if (recommendedContainer) {
+            recommendedJobs.forEach(job => {
+                recommendedContainer.appendChild(createJobCard(job, true));
+            });
+        }
+        if (nonRecommendedContainer) {
+            nonRecommendedJobs.forEach(job => {
+                nonRecommendedContainer.appendChild(createJobCard(job, false));
+            });
+        }
+    }
+
+    // --- Function to Determine if Job is Recommended ---
+    function isJobRecommended(job, studentProfile) {
+        // Simple logic: if at least 2 of the required skills are in the student's key skills, recommend it.
+        const requiredSkillsLower = job.requiredSkills.map(skill => skill.toLowerCase());
+        const studentSkillsLower = studentProfile.keySkills.map(skill => skill.toLowerCase());
+        const matchingSkills = requiredSkillsLower.filter(skill => studentSkillsLower.includes(skill));
+        return matchingSkills.length >= 2; // Adjust threshold as needed
+    }
+
+    // --- Function to Create a Job Card Element ---
+    function createJobCard(job, isRecommended) {
+        const card = document.createElement('div');
+        card.className = `job-card ${isRecommended ? 'recommended' : 'non-recommended'}`;
+
+        card.innerHTML = `
+            <h4>${job.title}</h4>
+            <p class="company">${job.company}</p>
+            <p class="location">${job.location}</p>
+            <p class="type">${job.type}</p>
+            <p class="${isRecommended ? 'aligns-with' : 'mismatch'}">
+                ${isRecommended
+                    ? `Aligns with: ${job.requiredSkills.join(', ')}`
+                    : `Requires: ${job.requiredSkills.join(', ')}`}
+            </p>
+            <button class="btn ${isRecommended ? 'btn-primary' : 'btn-secondary'} apply-btn">
+                ${isRecommended ? 'Apply Now' : 'Apply Anyway'}
+            </button>
+        `;
+
+        // Add event listener to the button
+        const applyButton = card.querySelector('.apply-btn');
+        applyButton.addEventListener('click', (e) => {
+            e.preventDefault(); // Prevent default button behavior if it's inside a form
+            handleApplyClick(job, isRecommended);
+        });
+
+        return card;
+    }
+
+    // --- Function to Handle Apply Button Click ---
+    function handleApplyClick(job, isRecommended) {
+        // Example: Log the action, show an alert, or open the job link in a new tab
+        console.log(`Apply button clicked for job: ${job.title} (Category: ${job.type}, Recommended: ${isRecommended})`);
+        alert(`You clicked 'Apply ${isRecommended ? 'Now' : 'Anyway'}' for ${job.title} at ${job.company}. This would typically redirect you to the application portal.`);
+        // window.open(job.applicationLink, '_blank'); // If you have an application link
+    }
+
+    // --- Initial Load ---
+    // Load jobs for the initially active tab (On-Campus)
+    if (jobListingsSection && jobListingsSection.classList.contains('active')) {
+        loadJobsForCategory('on-campus');
+    } else if (jobListingsSection) {
+         // If the section exists but isn't active, load for on-campus by default for initial display
+         loadJobsForCategory('on-campus');
+    }
+
+    // Optional: Listen for changes in the student selector if the recommendation logic depends on the selected student
+    // studentSelector.addEventListener('change', () => {
+    //     const selectedEnrollment = studentSelector.value;
+    //     if (selectedEnrollment) {
+    //         // Fetch or update the student profile based on the selection
+    //         // Then reload the job listings using the new profile
+    //         // loadJobsForCategory(currentActiveCategory); // You'd need to track the current active category
+    //     }
+    // });
+
+});

templates/final.html

@@ -5,6 +5,7 @@
     <meta name="viewport" content="width=device-width, initial-scale=1.0">
     <title>AI Student Analyzer</title>
     <link rel="stylesheet" href="../static/final.css">
+    <link rel="stylesheet" href="../static/job_listings.css"> <!-- New CSS file for job listings -->
     <link rel="preconnect" href="https://fonts.googleapis.com">
     <link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
     <link href="https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700&display=swap" rel="stylesheet">
@@ -25,6 +26,7 @@
                     <li><a href="#students" class="nav-link">Students</a></li>
                     <li><a href="#reports" class="nav-link">Reports</a></li>
                     <li><a href="#job-analysis" class="nav-link">Job Analysis</a></li>
+                    <li><a href="#job-listings" class="nav-link">Job Listings</a></li> <!-- New Link -->
                     <li><a href="#chat" class="nav-link">Chat</a></li>
                 </ul>
             </nav>
@@ -174,6 +176,55 @@
                 </div>
             </section>
 
+            <!-- New Job Listings Page -->
+            <section id="job-listings" class="content-section hidden">
+                <h2>Job Listings</h2>
+                <div class="job-listings-container">
+                    <!-- Info Panel -->
+                    <div class="info-panel card">
+                        <h3>About Job Recommendations</h3>
+                        <p>
+                            <strong>Recommended Jobs:</strong> These jobs are highly aligned with your current profile, skills, and experience. Applying to these positions is likely to result in a higher success rate.
+                        </p>
+                        <p>
+                            <strong>Non-Recommended Jobs:</strong> These jobs may have requirements that differ significantly from your current profile. While you are free to apply, you might need to acquire additional skills or experience to be a strong candidate.
+                        </p>
+                    </div>
+
+                    <!-- Tabs for On-Campus / Off-Campus -->
+                    <div class="job-listings-tabs">
+                        <button class="tab-btn active" data-category="on-campus">On-Campus</button>
+                        <button class="tab-btn" data-category="off-campus">Off-Campus</button>
+                    </div>
+
+                    <!-- On-Campus Listings -->
+                    <div class="job-category-section" data-category="on-campus">
+                        <h3>Recommended</h3>
+                        <div class="job-listings-grid" id="on-campus-recommended-listings">
+                            <!-- Recommended jobs will be populated here by JS -->
+                        </div>
+
+                        <h3>Non-Recommended</h3>
+                        <div class="job-listings-grid" id="on-campus-non-recommended-listings">
+                            <!-- Non-recommended jobs will be populated here by JS -->
+                        </div>
+                    </div>
+
+                    <!-- Off-Campus Listings (Initially Hidden) -->
+                    <div class="job-category-section hidden" data-category="off-campus">
+                        <h3>Recommended</h3>
+                        <div class="job-listings-grid" id="off-campus-recommended-listings">
+                            <!-- Recommended jobs will be populated here by JS -->
+                        </div>
+
+                        <h3>Non-Recommended</h3>
+                        <div class="job-listings-grid" id="off-campus-non-recommended-listings">
+                            <!-- Non-recommended jobs will be populated here by JS -->
+                        </div>
+                    </div>
+                </div>
+            </section>
+
             <!-- Chatbot Interface -->
             <section id="chat" class="content-section hidden">
                 <h2>Student Q&A</h2>
@@ -189,5 +240,6 @@
     </div>
 
     <script src="../static/final.js"></script>
+    <script src="../static/job_listings.js"></script> <!-- New JS file for job listings -->
 </body>
 </html>