Predicting Agriculture App is a sophisticated, yet user-friendly tool designed to forecast crop yields by analyzing various agricultural factors. This app allows users to input detailed information about their farming conditions, including climate zone, soil type, weather patterns, and farm practices. By providing data such as location, crop type, irrigation methods, and fertilizer usage, the app generates accurate and tailored yield predictions. Built with Streamlit, the app features an intuitive interface that simplifies data entry and makes the prediction process accessible to both novice and experienced farmers. It leverages a powerful API to analyze the input data and provide insights into potential crop yields, helping users make informed decisions about their farming practices. Whether you are managing a small garden or a large farm, the Predicting Agriculture App offers valuable predictions that can optimize your yield and improve agricultural outcomes. By considering critical factors such as soil moisture, temperature, and weather conditions, the app supports effective planning and resource management, ultimately contributing to more successful and sustainable farming operations.

Gaia is an innovative web application designed to provide safety and support to women who find themselves alone in potentially risky situations. The app can chat using an AI to give the user the illusion of being in company, offering both emotional reassurance and a sense of security. In addition, Gaia can help users call emergency services instantly if they are in danger. The app also features a map that identifies the most dangerous areas based on real-time emergency call data, enabling users to avoid risky locations. This data-driven approach will also assist law enforcement in intelligently focusing their efforts on areas with higher safety concerns. We have worked just for London and we have got the data from their official website.

PoliBot is an advanced global crisis negotiation simulator built using Python and Streamlit. The core idea is to model complex international relations and decision-making during various global emergencies (like climate collapse, pandemics, or energy crises) using autonomous AI agents. Each agent represents a specific country (e.g., USA, China, India, EU, Pakistan), equipped with a unique profile detailing its strengths, weaknesses, and national interests. Leveraging the Groq API and the Llama3 language model, these agents analyze the ongoing scenario, consult their recent memory of interactions, and decide on diplomatic actions—such as proposing deals, building alliances, or raising concerns—to best serve their country's objectives. The simulation dynamically tracks key global metrics (Peace Index, Economic Growth, CO₂ Emissions, etc.) and visualizes the evolving diplomatic network and relationships between nations using NetworkX and Matplotlib. Users can configure the scenario, participating nations, simulation speed, and other parameters, observing how AI-driven diplomacy unfolds turn by turn. The project demonstrates the potential of LLMs in simulating complex multi-agent systems and geopolitical dynamics.