Developed a Knowledge Graph-based Retrieval-Augmented Generation (RAG) system with verifiable citations and multi-hop reasoning for the shubhamsaboo/awesome-llm-apps repository. The work focused on integrating Neo4j and Python to enable robust document retrieval and source attribution, while leveraging Docker for deployment consistency. Addressed code review feedback by improving Docker configuration, enhancing error handling, and ensuring environment variables were managed securely. Streamlit was used for the application interface, and code quality was elevated through PEP8 compliance, import hygiene, and parameterized Cypher queries to prevent injection. The project emphasized deployment reliability and maintainable, secure full stack development practices throughout.