Lilly Tech Systems
Learn Chainlit
Build production-ready chatbot UIs with Python. Create conversational AI applications with streaming, file uploads, multi-modal support, LangChain integration, and custom themes — all in pure Python.
Your Learning Path
Follow these lessons in order, or jump to any topic that interests you.
1. Introduction
What is Chainlit? Python chatbot framework, key features, and comparison with Gradio and Streamlit.
2. Setup
Install Chainlit, create your first chatbot, project structure, and configuration.
3. Chat Interface
@cl.on_message, step decorators, streaming responses, file uploads, and multi-modal messages.
4. LangChain Integration
Integrate LangChain chains, agents, and RAG pipelines with Chainlit's chat UI and step visualization.
5. Customization
Custom themes, branding, authentication, user sessions, and UI configuration.
6. Best Practices
Production deployment, Docker, error handling, testing, performance, and scaling patterns.
What You'll Learn
By the end of this course, you'll be able to:
Build Chatbots
Create full-featured chat interfaces with streaming, message history, and step-by-step reasoning.
LangChain + Chainlit
Visualize LangChain chains and agents with automatic step tracking and intermediate results.
Custom Branding
Theme your chatbot with custom logos, colors, fonts, and authentication for enterprise use.
Deploy to Production
Deploy Chainlit apps with Docker, handle authentication, and scale for multiple users.