Udemy – AI Chatbots with Python, LangChain, LangSmith & Streamlit

Udemy – AI Chatbots with Python, LangChain, LangSmith & Streamlit

File Name:AI Chatbots with Python, LangChain, LangSmith & Streamlit
Content Source:https://www.udemy.com/course/ai-chatbots-with-python-langchain-langsmith-streamlit
Genre / Category:Other Tutorials
File Size :444.5 MB
Publisher:Prateek Sethi
Updated and Published:August 6, 2025
Product Details

In this hands-on masterclass, you’ll learn how to design, build real-world AI chatbots using Python, LangChain, Streamlit, and modern LLM platforms like OpenAI and Ollama. Whether you’re a developer, data scientist, or AI enthusiast—this course will teach you everything you need to create production-ready AI assistants from scratch.

You’ll go far beyond the basics. By the end, you’ll have built a full-stack chatbot with memory, LLM switching, persistent conversation history and LangSmith-powered observability and debugging.

What You’ll Build:

  • A memory-enabled chatbot with a modern Streamlit UI
  • Multi-provider LLM support (OpenAI & Ollama)
  • Persistent chat history using SQLite
  • Fully traceable workflows using LangSmith
  • A ready-to-deploy conversational assistant for your business or clients

    Key Technologies Covered:
    • Python – Core scripting for AI Chatbot
    • LangChain – Prompting, chains, memory, parsing
    • Streamlit – Frontend chat UI and user interaction
    • LangSmith – Debugging, tracing, observability
    • OpenAI & Ollama – Cloud and local LLM integration
    • SQLChatMessageHistory – Long-term memory via SQLite
    • Prompt engineering – System + human messages and history placeholders

      What You Will Learn:
      • How to design a modular and scalable LLM chatbot
      • How to build Streamlit chat UIs
      • How to use LangChain’s memory components and prompt templates
      • How to switch between OpenAI and Ollama models on the fly
      • How to structure LangChain chains using RunnableLambda and RunnableWithMessageHistory
      • How to trace, debug, and compare model outputs using LangSmith
      • How to store and retrieve chat history from a SQL database
      • How to deploy your chatbot locally or to the cloud

DOWNLOAD LINK: AI Chatbots with Python, LangChain, LangSmith & Streamlit

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