Pre-release

This release is a pre-release and may not be stable for production use.

Welcome to Chainlit 👋

Build a production ready Chat GPT like application in minutes ⚡️

Chainlit is an open-source async Python framework that makes it incredibly fast to build Chat GPT like applications with your own business logic and data.

Key features:

https://github.com/Chainlit/chainlit/assets/13104895/8882af90-fdfa-4b24-8200-1ee96c6c7490

Installation

Open a terminal and run:

$ pip install chainlit
$ chainlit hello

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

📖 Documentation

Please see here for full documentation on:

Getting started (installation, simple examples)
Examples
Reference (full API docs)

🚀 Quickstart

🐍 Pure Python

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

import chainlit as cl


@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 Tool 1, followed by the final answer.

    Args:
        message: The user's message.

    Returns:
        None.
    """

    # Send an intermediate response from Tool 1.
    await cl.Message(
        author="Tool 1",
        content=f"Response from tool1",
        parent_id=message.id,
    ).send()

    # Send the final answer.
    await cl.Message(content=f"This is the final answer").send()

Now run it!

$ chainlit run demo.py -w

Quick Start

🔗 Integrations

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

🎨 Custom Frontend

Chainlit allows you to create a custom frontend for your application, offering you the flexibility to design a unique user experience. By integrating your frontend with Chainlit's backend, you can harness the full power of Chainlit's features, including:

Abstractions for easier development
Monitoring and observability
Seamless integrations with various tools
Robust authentication mechanisms
Support for multi-user environments
Efficient data streaming capabilities

To build and connect your own frontend, check out our Custom Frontend Cookbook.

📚 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.

🛣 Roadmap

Selectable chat profiles (at the beginning of a chat)
One click chat sharing
New clients:
- Custom React app
- Slack
- Discord
- Website embbed

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

🏢 Enterprise support

For entreprise grade features and self hosting, please visit this page and fill the form.

💁 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.

Metadata

Release files for chainlit 0.7.604rc1

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Source distribution for chainlit 0.7.604rc1
File	Size	Uploaded	Provenance
chainlit-0.7.604rc1.tar.gz	2.1 MB	Nov 17, 2023	Without provenance	Details

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Table of built distributions (wheels) for chainlit 0.7.604rc1
File	Interpreter	ABI	Platform	Reset
chainlit-0.7.604rc1-py3-none-any.whl 2.2 MB Nov 17, 2023 Without provenance	Python 3	none	any	Details

Total release size: 4.3 MB

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Download URL	chainlit-0.7.604rc1.tar.gz
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SHA-256 checksum How to use checksums	`92fa1c77002bff726560b926b641b57cdcad1b7d9ced0a6e2c85e6dde053877b`
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Uploaded via	`twine/4.0.2 CPython/3.11.6`

Release files / chainlit-0.7.604rc1-py3-none-any.whl

Download URL	chainlit-0.7.604rc1-py3-none-any.whl
Size	2.2 MB
Tags	Python 3
SHA-256 checksum How to use checksums	`b6eae72bd3d8e331f9d05fdd486c4b047fcbcb7220326d3116b770035507ed01`
BLAKE2b-256 checksum How to use checksums	`10437c8ea1ef841d18a3bcb1166b4c8e210f160b778139e4c1e1046b51995aa3`
Upload date	Nov 17, 2023
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Uploaded via	`twine/4.0.2 CPython/3.11.6`

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