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chainlit.io

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Build AI applications

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Saas
Company
Chainlit
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About chainlit.io

Chainlit is a framework and platform designed to help developers and enterprises build, evaluate, and improve conversational AI applications. It provides tools for creating reliable AI systems, offering observability and analytics for LLM apps. Chainlit supports various deployment options, including standalone web apps, embedded copilots, FastAPI servers, and custom React or Slack/Discord/Teams bots. It also offers authentication and customization features, along with integrations with popular frameworks and LLM providers.

How to Use

To use Chainlit, install the library using pip install chainlit, then run your application using chainlit run app.py. You can then deploy your app as a web app or integrate it into other platforms.

Key Features

  • Building conversational AI applications
  • Evaluating AI systems
  • Observability and analytics for LLM apps
  • Deployment options (web app, copilot, FastAPI, bots)
  • Authentication (simple auth, OAuth)
  • Customization (frontend, chat components)
  • Integrations with frameworks and LLM providers

Use Cases

  • Creating a chat application with custom Python logic
  • Building a sales report generator using LLMs

FAQ

What integrations does Chainlit support? Claude Code API (code0.ai) Stable domestic direct-connect proxy for Claude API with CNY payment and low latency.

Key Features

Building conversational AI applications
Evaluating AI systems
Observability and analytics for LLM apps
Deployment options (web app, copilot, FastAPI, bots)
Authentication (simple auth, OAuth)
Customization (frontend, chat components)
Integrations with frameworks and LLM providers

Pros & Cons

Pros
  • Open-source with a large, active community (50k+ developers, 9k GitHub stars)
  • Easy to get started: pip install and run quickly
  • Supports a wide range of deployment targets and authentication methods
  • Integrates seamlessly with popular LLM providers and frameworks
Cons
  • Requires Python programming knowledge to use effectively

Best For

Creating a chat application with custom Python logicBuilding a sales report generator using LLMs

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