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Ahamed Shahmi's avatar
Ahamed Shahmi
Kalmunai, Sri Lanka
Full-Stack AI Engineer | RAG Pipelines • LLM Apps • Chatbot
Full-Stack AI Engineer | RAG Pipelines • LLM Apps • Chatbot
Cover image for AI Agent for Automatic Book
AI Agent for Automatic Book Summary Generation An AI-powered agent that automatically generates summaries for PDF books using Large Language Models (LLMs). The system continuously monitors a Google Drive folder, detects newly uploaded PDFs in real time, and generates concise summaries without manual intervention. This project combines workflow automation using n8n with a FastAPI backend to demonstrate a production-style AI agent architecture.
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Cover image for Multi-Modal AI System for Produce
Multi-Modal AI System for Produce Freshness Detection Designed and deployed a real-time multi-modal AI System integration CNN-based image analysis with gas sensor, NIR, and metadata features using early fusion. Achieved 93.42% accuracy with 113 ms interference latency on a portable edge device, outperforming image-only and sensor-only baselines across Accuracy, Precision, Recall, and F1-score.
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Cover image for Intelligent resume analysis powered by Gemini
Intelligent resume analysis powered by Gemini 2.5, all-MiniLM-L6-v2, FastAPI, and React + Vite. Multi-dimensional ATS scoring, keyword matching, semantic similarity, skill gap detection, and actionable recommendations — all via a clean REST API.
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Cover image for Built an agentic RAG chatbot
Built an agentic RAG chatbot enabling natural language conversations over 25 landmark AI/ML research papers from ArXiv, with source-attributed answers and page-level citations. Designed a 5-category intent classification system using zero-temperature Gemini to route messages - eliminating unnecessary vector. Implemented hybrid retrieval combining FAISS vector search (60%) and BM25 keyword search (40%) using LangChain EnsembleRetriever, improving recall for both semantic queries and exact terminology. Architected a two-layer memory system - short-term session memory and long-term cross-session memory, injected into the system prompt for personalised responses. Deployed FastAPI backend on AWS EC2 with Ngrok HTTPS tunnel and React frontend on Vercel. Technologies: Python, FastAPI, LangChain, HuggingFace Transformers, FAISS, BM25, Google Gemini, SQLite, React, AWS EC2, Vercel.
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