From the course: Python for AI Projects: From Data Exploration to Impact
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Run an AI Chatbot from Explore California Dataset - Python Tutorial
From the course: Python for AI Projects: From Data Exploration to Impact
Run an AI Chatbot from Explore California Dataset
- [Instructor] Now, we can try asking a question. For example, where is the best beach in California? In this Hello World app, you'll see side-by-side LLM responses from a local tiny Llama model and a Mistral cloud model via open router. At the bottom of the app, there's an expander section showing the Python source code, the same as on GitHub. You'll notice there's quite a lot happening behind the scenes for such a simple-looking app. You'll notice the Streamlit app is well documented with clear comments and docstrings for each function. We won't dive into the Hello World code just yet, but we'll highlight the key parts of each AI chatbot version and how they differ. When you're done exploring the Streamlit app, head back to Colab and run the Shutdown Streamlit and Ngrok function to close the app and free up the Ngrok tunnel. Let's dive into our first pure Python implementation of the Explore California chatbot. For…
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Data exploration2m 18s
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Setting up your Coding Environment3m 35s
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Setting up LLMs4m 50s
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Deploy AI Web Apps using Streamlit4m 8s
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Run an AI Chatbot from Explore California Dataset3m 14s
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Improving GenAI performance3m 47s
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Bringing It All Together: Improving your Chatbot with ML9m 31s
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