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 environment
2⃣ Collecting real-time weather data
3⃣ Creating a user-friendly interface with Streamlit
4⃣ Leveraging LangChain to enhance your weather app
5⃣ 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 Demo
02:40 – Creating Virtual Environment
04:55 – Installing Libraries(LangChain, Streamlit, OpenAI, python-decouple)
05:35 – DataForSeo With LangChain
07:00 – Setting Up Environment Variables
09:00 – Streamlit Chat UI
17:20 – Creating AI Functionality
20:50 – Prompt Engineering
22:15 – 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/dataforseo
OpenAI API Key: https://platform.openai.com/account/api-keys
DataForSEO 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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