Welcome to Chainlit by Literal AI 👋

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Build production-ready Conversational AI applications in minutes, not weeks ⚡️

Chainlit is an open-source async Python framework which allows developers to build scalable Conversational AI or agentic applications.

✅ ChatGPT-like application
✅ Embedded Chatbot & Software Copilot
✅ Slack & Discord
✅ Custom frontend (build your own agentic experience)
✅ API Endpoint

Full documentation is available here. You can ask Chainlit related questions to Chainlit Help, an app built using Chainlit!

[!NOTE]
Contact us here for Enterprise Support. Check out Literal AI, our product to monitor and evaluate LLM applications! It works with any Python or TypeScript applications and seamlessly with Chainlit by adding a LITERAL_API_KEY in your project.

Installation

Open a terminal and run:

$ pip install chainlit
$ chainlit hello

If this opens the hello app in your browser, you're all set!

🚀 Quickstart

🐍 Pure Python

Create a new file demo.py with the following code:

import chainlit as cl


@cl.step(type="tool")
async def tool():
    # Fake tool
    await cl.sleep(2)
    return "Response from the tool!"


@cl.on_message  # this function will be called every time a user inputs a message in the UI
async def main(message: cl.Message):
    """
    This function is called every time a user inputs a message in the UI.
    It sends back an intermediate response from the tool, followed by the final answer.

    Args:
        message: The user's message.

    Returns:
        None.
    """

    final_answer = await cl.Message(content="").send()

    # Call the tool
    final_answer.content = await tool()

    await final_answer.update()

Now run it!

$ chainlit run demo.py -w

Quick Start

🎉 Key Features and Integrations

Full documentation is available here. Key features:

Chainlit is compatible with all Python programs and libraries. That being said, it comes with integrations for:

📚 More Examples - Cookbook

You can find various examples of Chainlit apps here that leverage tools and services such as OpenAI, Anthropiс, LangChain, LlamaIndex, ChromaDB, Pinecone and more.

Tell us what you would like to see added in Chainlit using the Github issues or on Discord.

💁 Contributing

As an open-source initiative in a rapidly evolving domain, we welcome contributions, be it through the addition of new features or the improvement of documentation.

For detailed information on how to contribute, see here.

📃 License

Chainlit is open-source and licensed under the Apache 2.0 license.

Release files for chainlit 1.1.400rc1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for chainlit 1.1.400rc1
File	Size	Uploaded
chainlit-1.1.400rc1.tar.gz	4.2 MB	Jul 15, 2024	Details

Built distribution (wheel)

Table of built distributions (wheels) for chainlit 1.1.400rc1
File	Interpreter	ABI	Platform	Reset
chainlit-1.1.400rc1-py3-none-any.whl 4.3 MB Jul 15, 2024	Python 3	none	any	Details

Total release size: 8.5 MB

Release files / chainlit-1.1.400rc1.tar.gz

Download URL	chainlit-1.1.400rc1.tar.gz
Size	4.2 MB
Tags	Source
SHA-256 checksum How to use checksums	`f73a9177cbd4142a2e0e370516a37af9c0e2ab2028973b48f680b6e2e103d4d4`
BLAKE2b-256 checksum How to use checksums	`0533fb6d1ee782b6a79b8b3fc4c43befe6abe65546384b86c86d2dc7c6699d9e`
Upload date	Jul 15, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/5.1.0 CPython/3.12.4`

Release files / chainlit-1.1.400rc1-py3-none-any.whl

Download URL	chainlit-1.1.400rc1-py3-none-any.whl
Size	4.3 MB
Tags	Python 3
SHA-256 checksum How to use checksums	`1f2fc0458befc164712945738acf53a1711cb14e5bf0818cef29d5dd04cb4eb3`
BLAKE2b-256 checksum How to use checksums	`bd4ed6e90b4a5176788a4034347bbd882f32bf0c3bca1b8e5b82a05176f80a8b`
Upload date	Jul 15, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/5.1.0 CPython/3.12.4`