Build a Weather App with Python Streamlit, LangChain, and OpenAI GPT | Step-by-Step Tutorial

Want to create your own weather app with a twist? In this tutorial, we’ll show you how to build a dynamic and interactive weather application using Python, Streamlit, LangChain, and the power of OpenAI’s GPT model.

Whether you’re a beginner or an experienced developer, we’ll guide you through every step of the process, making it easy for you to follow along and create your own personalized weather app.

What you’ll learn in this tutorial:1⃣ Setting up your development environment2⃣ Collecting real-time weather data3⃣ Creating a user-friendly interface with Streamlit4⃣ Leveraging LangChain to enhance your weather app5⃣ Integrating OpenAI’s GPT model for natural language interactions

By the end of this video, you’ll have a fully functional weather app that not only provides accurate weather information but also allows users to have conversations with the AI, thanks to GPT!

Download the code and resources:https://github.com/Princekrampah/AIWeatherAgent

Time Stamps:00:00 – Introduction and Demo02:40 – Creating Virtual Environment04:55 – Installing Libraries(LangChain, Streamlit, OpenAI, python-decouple)05:35 – DataForSeo With LangChain07:00 – Setting Up Environment Variables09:00 – Streamlit Chat UI17:20 – Creating AI Functionality20:50 – Prompt Engineering22:15 – LangChain Expression Language (LCEL)23:08 – Generating AI Response

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#Python #Streamlit #LangChain #OpenAI #GPT #WeatherApp #Tutorial #AI #Development #WebApp #WeatherForecast #Programming #Tech #codewithprince

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Helpful Links:

Streamlit Documentation: https://streamlit.io/LangChain Documentation: https://python.langchain.com/docs/integrations/tools/dataforseoOpenAI API Key: https://platform.openai.com/account/api-keysDataForSEO API Key: https://app.dataforseo.com/api-dashboard

Have questions or need assistance? Leave a comment below, and we’ll be happy to help!

Thanks for watching, and let’s get started on building your own Weather App with a twist!

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