Joshua Oluwatigbemileke Agboola

# RDA AI: Robotics Development Assistant RDA AI is an advanced, full-stack AI assistant tailored for robotics engineers and software developers. The platform streamlines hardware configuration, embedded programming, ROS (Robot Operating System) node generation, and physical simulation modeling. By pairing multi-modal generation with persistent state tracking, RDA AI acts as an end-to-end co-pilot for hardware engineering workflows. --- ## 🚀 Key Features * **Intelligent Code Generation:** Generates and debugs production-ready firmware code (Arduino C++, ESP-IDF, Python) for microcontrollers, sensors, and actuators. * **Schematic & Circuit Assistance:** Analyzes pinout layouts, visualizes component wirings, and troubleshoots electrical hardware logic. * **High-Fidelity Concept Visualizations:** Uses advanced text-to-image pipelines to generate visual design mockups, CAD concepts, and chassis structural layouts. --- ## 🛠️ Tech Stack & Architecture The system utilizes an asynchronous backend layer integrated with modern multi-modal foundation models and cloud database services: * **Frontend UI:** Built with **Streamlit**, providing a clean, responsive, dashboard-driven user interface for real-time streaming text interaction and image rendering. * **Orchestration & Compute:** Driven entirely by **Python**, handling data transformations, environment variables, and asynchronous API communication. * **AI Engine & Foundations:** * **Google Vertex AI:** Hosts and provides enterprise-grade orchestration for our cognitive pipelines. * **Gemini 2.5 Text (`gemini-2.5-text`):** Powers deep reasoning, logical sequence planning, context retrieval, and structured hardware code generation. * **Imagen 4 Model:** Handles high-fidelity spatial configurations, generating visual CAD blueprints, part prototypes, and structural robotic chassis mockups. * **Database & Persistence:** **Supabase** (PostgreSQL) manages secure user authentication, stores historical chat threads, keeps vector-mapped hardware device contexts, and handles generation logs. --- ## 📂 Project Structure ```text ├── .env.example # Sample environment configuration file ├── requirements.txt # Python dependencies ├── app.py # Main Streamlit application entrypoint ├── core/ # Core backend logic │ ├── __init__.py │ ├── ai_engine.py # Vertex AI, Gemini, and Imagen configurations │ └── database.py # Supabase client wrapper and CRUD operations ├── utils/ # Helper modules │ └── formatters.py # Code blocks, markdown, and layout parsers └── assets/ # App icons, static graphics, and styling sheets