Chainlit
Build Conversational AI in minutes ⚡️
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What is Chainlit?
Chainlit is an open-source Python package designed to help developers build production-ready conversational AI applications in minutes rather than weeks. It provides a beautiful, user-friendly chat interface that works with any Python program or LLM framework, allowing developers to create chatbots, AI assistants, and conversational interfaces with just a few lines of code.
Key features include fast development with minimal Python code, built-in authentication supporting password login and OAuth providers (Google, GitHub, Azure, Okta, Amazon), data persistence for collecting and analyzing user chats, visualization of multi-step reasoning chains to understand how outputs are produced, and multi-platform deployment options. Chainlit integrates seamlessly with popular AI frameworks including LangChain, OpenAI, Mistral AI, Llama Index, Semantic Kernel, and Autogen.
Chainlit is ideal for Python developers, AI/ML engineers, data scientists, and enterprises that want to ship ambitious and reliable AI applications. It supports building chat applications with custom Python logic, embedding copilots on websites, creating FastAPI server integrations, and deploying as Slack/Discord/Teams bots. The framework has over 10.8k GitHub stars and is trusted by thousands of developers.
The platform supports streaming responses, document QA applications with source display, file uploads and downloads, custom UI elements like text and file buttons, and chain-of-thought visualization. Development includes auto-reloading with the -w flag for rapid iteration.
Chainlit pricing
Pricing model: Freemium
Chainlit is completely free and open-source under the Apache 2.0 license. There is no paid tier or commercial pricing - the entire framework including all features (authentication, data persistence, multi-platform deployment, integrations) is available at no cost. Developers can self-host Chainlit applications on their own infrastructure including Ploomber Cloud, AWS, Azure Container, Google Cloud Run, Google App Engine, Replit, Render, Fly.io, and HuggingFace Spaces.
Chainlit pros
- Open-source with Apache 2.0 license
- Build conversational AI in minutes not weeks
- Simple Python API with just a few lines of code
- Built-in authentication with password and OAuth support
- Supports Google, GitHub, Azure, Okta, Amazon OAuth
- Data persistence for chat collection and analysis
- Visualize multi-step reasoning and chain-of-thought
- Multi-platform deployment: Web App, Copilot, React, Slack, Discord, Teams
- Auto-reloading with -w flag for rapid development
- Streaming token responses for real-time updates
- Integrates with LangChain and LangGraph
- Compatible with OpenAI and Mistral AI
- Supports Llama Index and Semantic Kernel
- Integrates with Autogen agents
- File upload and download elements supported
- Custom React frontend integration available
- FastAPI mounting support for custom endpoints
- Requirements only Python 3.9 or higher
- 10.8k GitHub stars and active community
- Official data layer for data persistence
Chainlit cons
- Community-maintained as of May 2025 with no warranty
- Original Chainlit team stepped back from active development
- Chainlit SAS provides no warranties on future updates
- Applications are public by default requiring manual auth setup
- Requires Node and pnpm for development version installation
- Websockets required so deployment must support them
- Sticky sessions needed for auto-scaling load balancers
- CORS issues when embedding on different origins
- Browser window opens server-side without -h flag in production
- Default host is 127.0.0.1 requiring --host 0.0.0.0 for Docker
Frequently asked questions about Chainlit
What is Chainlit?
Chainlit is an open-source Python package to build production-ready conversational AI applications in minutes. It provides a beautiful chat interface and works with any Python program or library, including popular frameworks like LangChain, OpenAI, Mistral AI, and Llama Index.
How do I install Chainlit?
Install Chainlit via pip by running 'pip install chainlit' in your terminal. This makes the 'chainlit' command available. Verify installation by running 'chainlit hello' which opens the hello app in your browser.
How do I run a Chainlit app?
Create a Python file (e.g., app.py) with your chatbot logic using Chainlit decorators like @cl.on_message and @cl.on_chat_start. Then run 'chainlit run app.py -w' where the -w flag enables auto-reloading for development. The UI is accessible at http://localhost:8000.
What authentication options does Chainlit support?
Chainlit supports password authentication, OAuth (Google, GitHub, Azure, Okta, Amazon), and header-based authentication. To enable authentication, define a CHAINLIT_AUTH_SECRET environment variable and add authentication callbacks to your app.
How do I enable data persistence?
By default Chainlit apps don't persist chat data. To enable data persistence, use the official open-source data layer, a community data layer, or build your own. Configure this in the data-persistence settings.
What platforms can I deploy Chainlit to?
Chainlit supports multiple deployment platforms: Web App (native UI on port 8000), Copilot (embed on any website), Custom React App, Microsoft Teams, Slack, and Discord. Write your assistant logic once and use it everywhere.
Does Chainlit support LangChain?
Yes, Chainlit has official LangChain/LangGraph integration. Use cl.LangchainCallbackHandler to listen to chain intermediate steps and send them to the UI. The callback handler visualizes prompts, completions, and agent steps.
What is the @cl.step decorator used for?
The @cl.step decorator creates steps that represent intermediate reasoning steps in LLM-powered assistants. Unlike Messages, Steps have a type, input/output, and start/end. Steps can visualize chain-of-thought, with settings to display fully, hide, or show only tool calls.
Can I customize the Chainlit frontend?
Yes, you can customize the application frontend and create custom chat components. For advanced customization, Chainlit supports custom React frontends that integrate with the Chainlit backend, giving you flexibility to design unique user experiences.