Codemate: Your Coding Companion, Problem Statement: Programming is hard! Even experienced devs get stuck. Traditional resources lack personalized help and timely feedback. Solution: Codemate is an AI-powered chatbot that provides instant, tailored assistance to programmers of all levels. Interactive learning: Ask questions, get explanations, master concepts. Real-time feedback: Get your code checked, fix errors, and learn faster. Personalized guidance: Receive customized recommendations to boost your skills. Debugging help: Troubleshoot errors and get unstuck quickly. 24/7 availability: Codemate is always there to help you code with confidence!

Phase 1: Langflow Workflow Design Create Initial Langflow Workflow: Design the initial workflow diagram, define language selection triggers, and outline actions for initiating AI dialogue. Develop AI Interaction Scripts: Write scripts for the AI to explain basic coding concepts and create interactive visualizations to support these explanations. Integrate AI Feedback Mechanism: Design a feedback system for Llama 3 to analyze user code and develop templates for common errors and improvement suggestions. Phase 2: Llama 3 Integration Prepare Training Data: Compile and preprocess programming tutorials and code examples for training Llama 3. Train Llama 3 Model: Train the Llama 3 model on the prepared dataset and validate its performance, making necessary adjustments. Implement Llama Guard 2: Integrate Llama Guard 2 for code safety and test the system to prevent malicious code injection. Phase 3: Gamification Implementation Design Point System: Define rules for awarding points and implement a point tracking mechanism in the backend. Create Badges and Achievements: Design badges for various achievements and develop backend logic for awarding them. Optional: Leaderboard Implementation: Design a leaderboard interface and implement real-time leaderboard updates. Phase 4: User Interface Development with Streamlit Build User Interface with Streamlit: Design the overall layout using Streamlit and develop front-end components such as text input and buttons. Integrate Langflow and AI Components: Connect the Streamlit frontend with Langflow workflows to ensure smooth interaction between the UI and the AI agent. Implement Interactive Coding Challenges: Create a library of coding challenges for different levels and develop a submission and testing interface in Streamlit.

EchoCare is a smart, AI-driven disease prediction app designed to provide users with rapid, accessible health assessments based on their symptoms. By combining a trained machine learning model with large language models (LLMs) like Together.ai, EchoCare not only predicts the likelihood of various diseases but also offers human-like explanations and health advice. Users can input symptoms through a simple UI and receive real-time predictions, risk levels, and clear, conversational explanations. The app supports features like history tracking, health tips, and optional voice input via OpenAI’s Whisper. The backend is powered by Langflow and Astra DB, enabling seamless data management and future scalability. EchoCare empowers users to make informed health decisions early — reducing risk, improving awareness, and making preventative care more accessible for everyone.