Wave Tracker simplifies mobile network analysis and optimization with a range of powerful features:

→ Easy Network Analysis: Helps users understand and improve mobile network performance.
→ Target Audience: Ideal for telecom professionals, engineers, and general users curious about network performance.
→ Input Data: Users can input MCC, MNC, Cell ID, LAC codes, or location data for area coverage analysis.
→ Data Fetching: Utilizes OpenCellID API to retrieve tower signal strength, location, and other key details.
→ Speed Predictions: Estimates internet speeds based on tower data and signal strength.
→ AI-Powered Insights: Offers suggestions for network optimization, such as tower selection and reducing interference.
→ Interactive Visualization: Displays network performance through dynamic charts for better clarity and actionable insights.
In conclusion, Wave Tracker provides a comprehensive and intuitive solution for users to analyze and optimize their mobile network performance. By combining real-time data with AI-driven insights, it empowers individuals and professionals alike to make informed decisions and improve connectivity. Whether you're troubleshooting network issues or enhancing coverage in rural areas, Wave Tracker is the go-to tool for smarter, more efficient network management.










AI for connectivity hackathon 

Wave Tracker is a handy tool for checking out your mobile network’s performance. It helps with troubleshooting, gives speed predictions, and shows network coverage all in real-time, using AI to give smart suggestions.

AI Ninjas

OpenAI is an AI research and deployment company

OpenAI

Empower your projects with customizable language models, prompt precision, and extensive tool integration through OpenGPTs by LangChain.

OpenGPTs

Large language models (LLMs) have transformed the way we approach machine learning and artificial intelligence. These models are incredibly powerful, but their true potential lies in their ability to work in harmony with other sources of data and computation. This library has been developed to assist developers in building applications that combine LLMs with other technologies, allowing them to create truly intelligent and innovative products.

Langchain

OpenELM, developed by Apple, is a family of Transformer-based language models optimized for devices with limited memory and computational resources, balancing high performance with efficiency.

OpenELM

Vercel is a platform designed for developers, providing speed, reliability, and scalability to create and deploy web applications. With built-in CI/CD, zero configuration, and deep integrations with popular Git providers such as GitHub, GitLab, and Bitbucket, Vercel streamlines the development process, making it easy for teams to collaborate and iterate on their projects.

Vercel

An open-source, locally running implementation of OpenAI's Code Interpreter.

open-interpreter

Reinforcement learning is a computational approach to machine learning where agents take actions in an environment to maximize some notion of cumulative reward.

Reinforcement Learning

Wave Tracker


ChatCinema is a multifaceted Streamlit application that combines a sophisticated movie information chatbot with advanced data processing and generation capabilities. The project integrates various cutting-edge technologies to create a versatile platform for movie enthusiasts, data scientists, and AI researchers.
At its core, ChatCinema features a highly interactive movie chatbot. This chatbot utilizes a CSV file ('Hydra-Movie-Scrape.csv') as its primary data source, containing a wealth of information about various movies. To enable efficient and relevant movie retrieval, the application employs the 'all-MiniLM-L6-v2' sentence transformer model to generate embeddings for movie summaries. These embeddings are then used in conjunction with cosine similarity calculations to find the most relevant movie based on user queries.
The chatbot's natural language processing capabilities are powered by the Groq API, specifically using the 'llama3-8b-8192' model. This integration allows for dynamic and context-aware responses to user inquiries. When a user inputs a movie-related query, the system retrieves the most similar movie from its database and uses this information as context for generating a response. The output includes comprehensive movie details such as title, year, summary, genres, IMDB ID, YouTube trailer link, rating, movie poster URL, director, writers, and cast information. Additionally, the chatbot generates relevant dialogues or additional information about the movie using the AI model.
A key feature of ChatCinema is its ability to maintain and manage chat history. The application stores conversation logs in Streamlit's session state, allowing for a continuous and contextual chat experience. Users have the option to download their chat history, which is provided as an encrypted CSV file for enhanced privacy and security.


Build Your AI Startup #2: Edge Runners

ChatCinema demonstrates a powerful combination of AI-driven chatbot technology, secure data handling, and dataset generation capabilities. Its versatile features make it suitable for both entertainment and educational purposes.

TechBlast

Unleash the potential of Streamlit for rapid deployment of data applications.

streamlit

Cutting-edge AI language model with unparalleled performance and innovative features.

Llama 3

Simplify AI integration with OpenAI's Assistants API, empowering developers to create AI assistants effortlessly.

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