From the course: Python for AI Projects: From Data Exploration to Impact

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Setting up your Coding Environment

Setting up your Coding Environment - Python Tutorial

From the course: Python for AI Projects: From Data Exploration to Impact

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Setting up your Coding Environment

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- [Instructor] Welcome to our final coding tutorial focused on generative and agentic AI. Clicking on the Resource link will take you straight into our Google Colab environment. In this tutorial, we'll learn how to run a Streamlit-based AI travel chatbot for our Explore California case study. You'll notice it includes many of the same features found in real-world AI applications. First, we'll build a linear RAG application using three approaches, starting with a simple Python app, then expanding it with LangChain and LangGraph AI frameworks. We can read this flow diagram from left to right. The search query retrieves the top Explore California locations, which are then added as context for the LLM to generate a response and follow-up question suggestions in the app interface. Finally, we'll use Streamlit's Session State to store the chat history, allowing future messages to include previous queries and responses as…

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