Chainlit is a Python‑first framework that streamlines the creation, authentication, and deployment of conversational AI applications. It provides declarative SDK decorators, ready‑made UI components, OAuth integrations, and plug‑and‑play connectors to major LLM providers, supporting deployment to web, FastAPI, React embeds, and collaboration bots. The open‑source library enables engineers to build and scale chat experiences without custom glue code.
Funding
Funding not disclosed
Founders
Product
Problem
Developers building conversational AI applications must stitch together multiple components—LLM APIs, authentication flows, UI layers, and deployment pipelines—often writing custom glue code for each integration, which slows time‑to‑market and introduces reliability risks.
Solution
Chainlit offers a Python‑first framework that abstracts the end‑to‑end workflow of creating, securing, and deploying AI‑driven chat experiences. The library provides ready‑made UI widgets and a CLI to launch apps instantly, while allowing developers to inject bespoke Python logic for prompts, tool use, or state management. Built‑in authentication supports simple credentials and enterprise‑grade OAuth providers (GitHub, Google, Azure AD, Okta, Amazon). Seamless integrations connect to leading LLM providers such as OpenAI, Mistral, LangGraph, LlamaIndex, and HuggingFace, eliminating manual API handling. Deployment options span standalone web apps, embedded copilots, FastAPI services, custom React front‑ends, and bots for Slack, Discord, or Teams, enabling teams to scale from prototypes to production without re‑architecting the stack. All components are open source and designed for extensibility, letting enterprises maintain control over data and infrastructure.
Target Audience
Primary users are software engineers and product teams building conversational AI products, as well as enterprises deploying internal copilots or customer‑facing chatbots across web, mobile, and collaboration platforms.
Features
- Python SDK with declarative @chainlit decorators for defining prompts, tool calls, and conversation flow
- Interactive UI library offering customizable chat windows, message bubbles, and real‑time streaming of LLM outputs
- OAuth 2.0 integration matrix (GitHub, Google, Azure AD, Okta, Amazon) plus simple token‑based auth for rapid user onboarding
- Plug‑and‑play connectors to OpenAI, Mistral, LangGraph, LlamaIndex, HuggingFace, and other LLM endpoints
- Multi‑target deployment engine supporting standalone web servers, FastAPI back‑ends, React embeds, and Slack/Discord/Teams bot adapters
- Theming and component extension system for branding, custom widgets, and third‑party UI plugins
- Open‑source core with pip installable package and Docker images for reproducible, cloud‑agnostic environments