Code from tutorials presented on the "Code AI with Rok" YouTube channel

Create a Chatbot app on your own data with GCP tools

Kedro Plugin to support running workflows on GCP Vertex AI Pipelines

Use Gemini Pro LLM via VertexAI to create an engaging quiz game incorporating TMDB API data

Connect LLM to Slackbot. Works via FastAPI

Collection of OSS models that are containerized into a serving container

Customized bot with langchain and gpt4

SQLGenius is an AI-powered SQL assistant that converts natural language to SQL queries using Vertex AI's Gemini Pro. Built with MCP and Streamlit, it provides an intuitive interface for BigQuery data exploration with real-time visualization and schema management.

A Flask app running GraphRAG for healthcare, made with Vertex AI and Neo4j, to be deployed in a container (Cloud Run or ECS).

A Streamlit-powered Jira assistant with MCP integration. Create, search, and manage Jira tickets through a clean tabbed interface using natural language commands or direct forms. Built with Python and MCP framework.

Discover how to learn anything faster with this AI-powered learning assistant built using Google's Gemini 2.0 Flash. Perfect for students, self-learners, and tech enthusiasts!

Generative AI Application (chatbot) using Cloud Run, Dialogflow and Vertex AI

Real time MLOPS architecture for tracking fraudulent transactions with MLFlow, GCP Vertex AI, Fast API and Airflow.

Self-Reflective RAG System: An intelligent document QA tool that evaluates its knowledge before answering or searching the web. Supports multiple LLMs, handles PDFs, and includes source attribution with a modern UI.

A Discord bot powered by Google Gemini Pro, capable of text generation, image analysis, audio transcription, and more.

Solution of Team RoboAgentic in Google Agentic AI Day

Term Project for University of Toronto's "SCS 3760 004 Cloud Technologies for Big Data, Machine Learning & Artificial Intelligence" course, Fall 2021.

Curated GCP AI & Cloud Solutions with practical examples, tools, and best practices for building and scaling AI applications and cloud architectures on Google Cloud Platform.