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CS student at Islington College, Kathmandu. I build ML models and the products around them β€” PyTorch, RAG pipelines, agent tool-calling, and full-stack deployment.

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about me

CS student in Kathmandu. I got into programming out of curiosity and ended up falling for machine learning β€” first the fundamentals (PyTorch, training models from scratch), then LLMs and RAG, and now the part I enjoy most: building AI products around models, not just notebooks.

  • πŸ”­ Currently building an AI research agent β€” a custom agent loop (no frameworks) that combines document RAG with live web search.
  • 🌱 Learning deep learning + LLM engineering in parallel. I learn by building β€” every project exists because I wanted to understand one specific thing.
  • πŸ“« Reach me at Praansu12@gmail.com β€” always happy to chat.

featured projects

πŸ€– AI Research Agent

An agent loop built from scratch β€” no framework. Decides on its own whether to search your documents (ChromaDB RAG), search the web, or both. Streams tool calls live.

πŸ“„ PDF Chat RAG

Upload a PDF, ask questions about it. Full RAG pipeline β€” PyMuPDF extraction, sentence-transformers embeddings, ChromaDB retrieval, Groq Llama 3. Streaming SSE + document deletion.

πŸš— Vehicle Classifier

PyTorch + ResNet18 transfer learning β€” classifies bus/car/motorcycle/truck at 90% accuracy (400 images, 100/class). Confusion matrix visualization. FastAPI inference API with Docker.

🌿 EcoVerda

Full-stack e-commerce for eco products β€” Next.js 16, TypeScript, Tailwind, Prisma, Stripe. Blur-up image placeholders, debounced search with URL sync, cart persistence.


more projects

Project What it is
πŸ…ΏοΈ ParkX IoT smart parking β€” ESP32 firmware, FastAPI backend, live dashboard
❀️ Health Guard ML Heart disease prediction with XGBoost + SHAP explanations
🏷️ Vehicle Labeling Tool PyQt5 GUI I built to label my own training data
πŸ”¬ Small Agent Reliability Research: evaluating 3B-9B models as autonomous agents across 14 tasks

tech stack

Languages β€” Python, TypeScript, JavaScript, HTML/CSS, SQL, Java, C++

ML/AI β€” PyTorch, scikit-learn, Pandas, NumPy, XGBoost, OpenCV, sentence-transformers

LLM / RAG β€” Groq (Llama 3), ChromaDB, embeddings, agent tool-calling, RAG pipelines

Backend & Tools β€” FastAPI, Next.js, Prisma, Streamlit, Flask, Git, Docker, SQLite

IoT β€” ESP32, Arduino


streak



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