chainlit-io

chainlit-io

Chainlit is a developer-focused framework for building, customizing, and deploying conversational AI applications and copilots, with Python-first tooling and integrations to major LLM providers.

chainlit-io is chatbots & assistants software teams evaluate for software & gaming. Use this page to review pricing, integration signals, and the best alternatives before you commit.

Pricing not listed
#140 in Chatbots & Assistants (140 tools)
Just launched
Data reviewed Sep 6, 2026

Profile facts come from the vendor source. AiMatch labels unknown pricing or API details instead of estimating them.

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Quick Overview

Best for: Software & Gaming

What it does

Chatbots & Assistants software for decision-makers comparing workflow fit and alternatives.

Best fit

Software & Gaming

Pricing snapshot

Pricing available on request

Next step

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chainlit-io

Chainlit is a Python-first framework and developer toolset for building conversational AI applications and copilots. The site frames Chainlit as a tool for developers and enterprises aiming to ship reliable AI applications, offering frontend customization, chat components, authentication, and integrations with popular LLM providers. Chainlit exposes commands to install and run apps locally and documents deployment options for standalone web apps, embedded copilots, FastAPI servers, and bots for Slack/Discord/Teams.

Chainlit helps build, evaluate, and improve conversational AI applications with observability and analytics.

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Key Features

Python-first chat apps

Create chat applications that run your Python logic (site copy: 'Chat application with your own python logic').

Easy install & local run

Instructions shown to install and run: '$ pip install chainlit' and '$ chainlit run app.py'.

Multiple deployment targets

Deploy as a standalone web app, embedded copilot, FastAPI server, custom React app, or as Slack/Discord/Teams bots.

Authentication

Supports simple auth methods and OAuth providers including GitHub, Google, Azure, Okta, Amazon (site copy lists these providers).

Customization & UI components

Customize the application frontend and create custom chat components.

Integrations with LLM & IR tools

Provides integrations with OpenAI, Mistral, LangGraph, LlamaIndex, HuggingFace and more.

Pricing

Current pricing details are not available from the vendor source.

Use Cases

Build conversational AI apps

Create chat-based applications and conversational interfaces for users, leveraging Python logic and custom UI components.

Embed copilots

Ship embedded copilots inside applications as cited by the site's deployment options.

Deploy bots to collaboration platforms

Create and deploy bots for Slack, Discord, and Microsoft Teams as supported deployment targets.

Developer prototyping and production

Install via pip and run locally for development, then deploy to production targets like FastAPI or standalone web apps.

Integrations

OpenAI

Integration with OpenAI as an LLM provider.

Mistral

Integration with Mistral as an LLM provider.

LangGraph

Integration with LangGraph listed on the site.

LlamaIndex

Integration with LlamaIndex for retrieval/indexing workflows.

HuggingFace

Integration with HuggingFace for models and tooling.

OAuth providers (GitHub, Google, Azure, Okta, Amazon)

Authentication integrations for enterprise identity providers (listed under Authentication).

Benefits

Speeds development of conversational AI apps with Python-first tooling and ready-made chat components.
Flexible deployment options (standalone web apps, FastAPI, embedded copilots, platform bots).
Pre-built integrations with major LLM providers and retrieval/indexing tools to connect models and data.
Built-in authentication support including OAuth providers for enterprise-ready access control.
Customizable frontend and component system to match product UX requirements.

Limitations

No verified limitations are available.

Frequently Asked Questions

No verified FAQs are available.

Getting Started

  1. 1 Step 1: Install the package locally (shown: '$ pip install chainlit').
  2. 2 Step 2: Run your app using the CLI (shown: '$ chainlit run app.py').
  3. 3 Step 3: Consult the project's Docs and GitHub (site prominently lists Docs and GitHub links) to configure deployments, authentication, and integrations.

Support

docs

Project documentation accessible from the site (page lists 'Docs' prominently).

github

Source code and project repository referenced via 'GitHub' links on the site.

community (Discord)

Community presence referenced by 'Discord Members' on the site.

API

Available: No

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