divyanshu saini 𓀛

Designed and implemented a full-stack educational assessment platform using a decoupled Django REST Framework (DRF) backend and a Next.js App Router frontend, featuring structured LLM-driven document ingestion, real-time student telemetry tracking, and a signal-driven gamification system.

• Architected a decoupled full-stack platform with a high-concurrency Django REST Framework (DRF) API and a Next.js 14 App Router frontend, implementing token-based authentication and secure session-state management.
• Engineered an asynchronous LLM ingestion pipeline using PyPDF2 and Google's Gemini Pro SDK to chunk raw curriculum PDFs into 8KB payloads, utilizing custom retry/backoff wrappers to enforce deterministic JSON output schemas for MCQ and short-answer questions
• Orchestrated Stateful AI Agents via LangGraph: Built self-correcting multi-agent state graphs using LangGraph for exam summarization and syllabus parsing; integrated a validation-correction loop that feeds quality feedback back into prompt generators to fix missing sections or schema violations.
• Decoupled Heavy Compute via Celery: Offloaded slow Gemini API inference (2s–30s latency) to an asynchronous Celery task worker pool, configuring soft/hard task time limits, custom retry queues, and worker concurrency controls.
• Implemented Redis Distributed Locking & Caching: Engineered a custom locking layer in Redis to guarantee task mutual exclusion (avoiding duplicate roadmap/summary generation), while using Redis for fast-read cache invalidation on dynamic resources.
• Established Observability with Flower: Configured Flower monitoring dashboards to track worker workloads, queue latencies, active task states, and retry behaviors to audit performance bottlenecks under production loads.
• Real-Time Telemetry Pipeline: Built a 5-stage telemetry-processing system (Ingest, Batch Inference, Aggregation, Reporting, and Transaction-Isolated Database Write) that evaluates user attempt vectors to identify performance weaknesses, map concept graphs, and generate syllabus roadmaps.
• Developed a concurrency-safe gamification engine using Django ORM signals (post save hooks), mapping user XP, dynamic streak multipliers, and global leaderboard rankings via optimized relational databases.
• Orchestrated local environment virtualization using Docker Compose to link Next.js (Node.js), Django (Gunicorn/Python), PostgreSQL 15, and Redis 7, ensuring feature parity across development and production environments.

Engineered an intelligent agent that automates end-to-end data analysis, from loading datasets to generating insights and visualizations.

• Automated data loading and preprocessing pipeline
• Generated intelligent insights using AI models
• Created dynamic visualization components

Developed a data visualization tool to analyze exported WhatsApp chats, providing insights on user activity, message trends, and emoji frequency.

• Parsed and processed chat export files
• Generated activity heatmaps and trend analysis
• Built emoji frequency and sentiment analysis features

Created a browser-based agent capable of combining natural language reasoning with external tools like search engines and APIs.

• Integrated natural language processing capabilities
• Connected external APIs and search engines
• Implemented multi-step reasoning workflows