streamlit AI technology page Top Builders

Explore the top contributors showcasing the highest number of streamlit AI technology page app submissions within our community.

Streamlit: Effortless Front-Ends for Your Data Apps

Streamlit is a pioneering technology provider that specializes in turning data scripts into shareable web apps with minimal effort. Launched in 2018, Streamlit has gained popularity for its ease of use and efficiency, empowering data scientists and developers to create and deploy data-driven applications swiftly.

General
AuthorStreamlit
Repositoryhttps://github.com/streamlit/streamlit
TypeFramework for ML and data science apps

Key Features

  • Transforms Python scripts into interactive apps with simple annotations, dramatically reducing development time.
  • Facilitates real-time interactivity directly from Python code without requiring front-end expertise.
  • Supports hot-reloading, allowing instant app updates as the underlying code changes.
  • Provides built-in support for a wide array of widgets, enabling the addition of interactive features without additional coding.

Start building with Streamlit's products

Streamlit offers a range of features designed to simplify the process of app creation and deployment, enhancing productivity in data science and machine learning fields. Explore how you can leverage Streamlit to turn your data projects into interactive applications. Don’t forget to check out the innovative projects built with Streamlit at various tech meetups!

List of Streamlit's products

Streamlit Library

The Streamlit Library allows developers to quickly convert Python scripts into interactive web apps. This library is packed with easy-to-use functionalities that make it straightforward to add widgets, charts, maps, and media files, transforming complex data science projects into user-friendly applications.

Streamlit Sharing

Streamlit Sharing provides the hosting infrastructure to share Streamlit apps with the world. It simplifies deployment, enabling users to go from script to app in minutes on a secure and scalable platform.

Streamlit for Teams

Streamlit for Teams is designed for collaboration and enterprise usage, offering additional features like integration with existing databases, advanced security protocols, and customized control for managing user access and data privacy.

System Requirements

Streamlit is compatible with Linux, macOS, and Windows systems, requiring Python 3.6 or later. It typically runs with minimal hardware requirements, though performance scales with available resources. For optimal performance, a modern processor and sufficient RAM are recommended, with a stable internet connection for deploying apps using Streamlit Sharing. Modern browsers with JavaScript support are required to view and interact with the apps.

streamlit AI technology page Hackathon projects

Discover innovative solutions crafted with streamlit AI technology page, developed by our community members during our engaging hackathons.

Travel Buddy

Travel Buddy

"Travel Buddy" is an AI-powered travel assistant designed to help travelers plan their journeys efficiently. The app uses IBM Watson Assistant to suggest the best transportation options based on the traveler’s source and destination. Whether you're traveling by plane, bus, train, or other modes, the assistant provides personalized recommendations based on factors like cost, convenience, and travel time. Key Features: Multi-Mode Transport Suggestions: The app considers various modes of transportation, offering users the best options such as flights, buses, and trains based on their journey. Cost Estimates: It provides approximate prices for each mode of transport, helping users make informed decisions based on their budget. Step-by-Step Journey Breakdown: The assistant provides detailed instructions for each mode of transport, such as flight schedules, boarding times, route information, and any other relevant details. Real-Time Travel Updates (Optional): For added convenience, the app can provide real-time updates on flight delays, bus cancellations, and train schedule changes, ensuring that travelers are always informed. User-Friendly Chat Interface: Travelers can easily input their source and destination locations and interact with the assistant through an intuitive chat interface. The assistant provides recommendations directly in the chat, making it quick and simple. Responsive Design: The app is fully responsive, offering an optimal experience across desktops, tablets, and mobile devices. Eco-Friendly Recommendations: The assistant can also suggest the most eco-friendly travel options, helping travelers reduce their carbon footprint. Travel Buddy offers a seamless, interactive, and visually engaging experience for planning travel. Whether you’re looking for a budget-friendly route or the quickest travel option, the app provides all the information you need to make your journey as smooth as possible.

SmartSupport-IT

SmartSupport-IT

The "IT SmartSupport Virtual Assistant" is an AI-powered solution designed to streamline IT support and troubleshooting for users facing technical issues. The goal of this project is to create a conversational interface that provides efficient, step-by-step guidance for resolving a wide range of IT-related problems. Users will be able to describe their issues, and the virtual assistant will classify the problem into categories like user account management, hardware support, software support, network issues, and IT security. Once the issue is classified, the assistant will guide the user through troubleshooting steps tailored to their specific problem. The assistant aims to break down complex IT issues into simple, actionable instructions, making it easier for non-technical users to resolve their problems without requiring expert intervention. It will also provide suggestions for further actions if the issue cannot be resolved immediately, such as submitting a support ticket or contacting the IT team. This virtual assistant will be powered by IBM's advanced language models, which will enable it to process user input, understand context, and generate human-like responses. The assistant will also adapt its guidance based on the nature of the user's issue, ensuring that the instructions are clear and relevant. By providing real-time assistance and continuously improving through machine learning, this project aims to reduce IT support costs, minimize downtime for users, and enhance the overall user experience by making IT troubleshooting more accessible and efficient. It is especially beneficial for organizations looking to offer quick and effective IT support at scale, reducing the dependency on live agents for routine issues.