Prashant Kumar - Frontend Engineer | Contra
Work by Prashant Kumar
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Prashant Kumar
Full-Stack + AI Automation Developer
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Prashant is ready for their next project!
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Akhil V
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Nugraha
Delhi, India
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Delhi, India
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3D Interactive Developer Portfolio | Prashant Kumar A premium, modern, and highly interactive developer portfolio website designed to showcase engineering expertise in Artificial Intelligence, Machine Learning, and Full-Stack Development. The site features a professional deep-space dark theme, responsive glassmorphic cards, scroll-triggered animations, and multiple engaging interactive elements. Theme: Deep Space Obsidian backgrounds with glowing cyan/indigo border gradients. Dual Link Buttons: Each project card features two distinct buttons for Visit Site (hosted deploy) and View Code (GitHub repository), designed for quick updates. Magnetic Cursor: A custom dual-ring magnetic cursor that expands and changes colors when hovering over clickable items.
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GigaCorp Customer Support Assistant A small RAG (Retrieval-Augmented Generation) demo using FastAPI, Chroma, and a local FAQ. What this project is This project contains a simple customer support assistant that: Loads a FAQ text file (gigacorp_faq.txt) into a Chroma vector store (via ingest.py (http://ingest.py)). Exposes a FastAPI web service (app.py (http://app.py)) with a web UI in static/ and a chat API (/api/chat). Uses a configurable LLM provider (Groq or OpenAI) when an API key is available; otherwise it returns a safe fallback response. The repository is available on : https://github.com/Prashant-tgr/Customer_Support_RAG.git
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It is a scheduling agent service for small businesses and booking systems it uses the agentic AI approach for scheduling and booking processes along with interacting with user and resolving their queries.
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Autonomous Learning Path This project implements an adaptive learning path engine (Skillgraph) with a FastAPI backend and a lightweight frontend. It demonstrates core techniques used in modern AI-enabled learning systems: multi-agent orchestration, retrieval-augmented generation (RAG), and directed acyclic graph (DAG) path planning.
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