Chainlit

Chainlit – Build AI Applications is a developer-focused framework and suite of tools designed to help teams ship ambitious and reliable AI applications. It provides end-to-end capabilities for building conversational AI apps, integrating with leading LLM providers, and deploying across multiple environments. The platform emphasizes developer productivity, customizable frontends, and robust integrations to streamline LLM application development from prototype to production.

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How to Use Chainlit

1. Install: pip install chainlit.
2. Run a local app: chainlit run app.py.
3. Deploy your app as a standalone web app, embedded copilot, FastAPI server, custom React, or Slack/Discord/Teams bot.

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Core Capabilities

• Build Conversational AI apps with your own Python logic
• Create beautiful, user-friendly frontends for web and mobile
• Deploy in multiple modes (standalone, embedded copilot, FastAPI, custom UI, or chat bots)
• Authentication options, including OAuth (Github, Google, Azure, Okta, Amazon, etc.)
• Frontend customization and custom chat components
• Rich integrations with popular frameworks and LLM providers

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Integrations & Providers

• OpenAI, Mistral, LangGraph, LlamaIndex, HuggingFace, and more

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How It Works

• Define your Python logic to handle conversations and business rules.
• Build a polished UI for end users.
• Deploy across supported environments with minimal configuration.

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Observability & Collaboration

• Tools to deploy, monitor, and iterate on LLM applications.
• Emphasizes scalability and reliability for enterprise use.

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Features

• Quickstart: easy installation and local testing with `pip install chainlit` and `chainlit run`.
• Multi-environment deployments: standalone web app, embedded copilot, FastAPI server, custom React apps, Slack/Discord/Teams bots.
• Authentication options: simple auth methods and OAuth (Github, Google, Azure, Okta, Amazon, etc.).
• Customizable frontend: tailor UI and create custom chat components.
• Integrations: compatibility with OpenAI, Mistral, LangGraph, LlamaIndex, HuggingFace and more.
• Developer-centric: designed for building and scaling AI applications with tooling for evaluation and improvement.

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About Chainlit Frameworks

• Chainlit Framework: Build Conversational AI apps, deploy across channels, and integrate with Python-based logic.
• Literal AI LLMOps: Tools for logging, evaluating, and improving LLM applications.
• Community & Resources: Documentation, examples, and support to help teams adopt Chainlit in production.

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Why Choose Chainlit

• End-to-end solution for AI app development from code to deployment.
• Flexible deployment options to fit various workflows and environments.
• Strong integration surface with major LLM providers and tooling ecosystems.
• Focus on developer experience, customization, and enterprise-readiness.