Build a Chatbot with Memory
Learn how to build a chatbot that acts as a wellness coach using LangChain and Streamlit
Talking to LLM models is a great way to get started with AI. In this tutorial, you'll build a chatbot that acts as a wellness coach that runs locally on your machine. The chatbot will be able to remember information about the user and provide personalized advice based on their preferences and goals.
The chatbot will store conversation history and memories in a SQLite database, allowing it to recall past interactions and provide more relevant responses over time. We'll use Streamlit to create a user-friendly interface and allow you to interact with the chatbot easily. The backbone (LLM integration) will be done using LangChain and LangGraph.
Tutorial Goals
- Build a local chatbot that acts as wellness coach
- Manage conversation history and store it into a database
- Save and retrieve memories about the client from database
- Create UI for the chatbot using Streamlit
Project Setup
Members onlyJoin 900+ members
Become a member for full access
“Best educational investment in my ML/AI journey.”
Ana Clara MedeirosAI Developer
Renews yearly at the price you joined at. Cancel anytime.
30-day money-back guarantee. One email, full refund. Yearly includes live cohort access.
What you get
6 modules and 42 hands-on lessons with runnable code, failure diagnosis, and measured comparisons
2 capstone repositories you build, test, evaluate, and keep as portfolio proof
Videos, source code, complete projects and architecture diagrams
Recordings of live sessions
Discord community access
Not ready? Try these free lessons first
Instant access after paymentSecure checkout via Stripe
