tesslate_chainlit 2.5.5
Build Conversational AI.
License: Apache-2.0
Requires Python: <4.0.0,>=3.10
Keywords: LLM, Agents, MCP, gen ai, chat ui, chatbot ui, openai, copilot, langchain, conversational ai

<h1 align="center">Welcome to Chainlit by Literal AI 👋</h1>

<p align="center">
<b>Build python production-ready conversational AI applications in minutes, not weeks ⚡️</b>

</p>
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<p align="center">
    <a href="https://chainlit.io"><b>Website</b></a>  •  
    <a href="https://docs.chainlit.io"><b>Documentation</b></a>  •  
    <a href="https://help.chainlit.io"><b>Chainlit Help</b></a>  •  
    <a href="https://github.com/Chainlit/cookbook"><b>Cookbook</b></a>
</p>

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    <a href="https://trendshift.io/repositories/6708" target="_blank"><img src="https://trendshift.io/api/badge/repositories/6708" alt="Chainlit%2Fchainlit | Trendshift" style="width: 250px; height: 45px;" width="250" height="45"/></a>
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https://github.com/user-attachments/assets/b3738aba-55c0-42fa-ac00-6efd1ee0d148

> [!NOTE]
> Chainlit is maintained by [Literal AI](https://literalai.com), an LLMOps platform to monitor and evaluate LLM applications! It works with any Python or TypeScript applications and [seamlessly](https://docs.chainlit.io/llmops/literalai) with Chainlit. For enterprise support, please fill this [form](https://docs.google.com/forms/d/e/1FAIpQLSdPVGqfuaWSC2DfunR6cY4C7kUHl0c2W7DnhzsF9bmMxrVpkg/viewform?usp=header).

## Installation

Open a terminal and run:

```sh
pip install chainlit
chainlit hello
```

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

### Development version

The latest in-development version can be installed straight from GitHub with:

```sh
pip install git+https://github.com/Chainlit/chainlit.git#subdirectory=backend/
```

(Requires Node and pnpm installed on the system.)

## 🚀 Quickstart

### 🐍 Pure Python

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

```python
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.
    """


    # Call the tool
    tool_res = await tool()

    await cl.Message(content=tool_res).send()
```

Now run it!

```sh
chainlit run demo.py -w
```

<img src="/images/quick-start.png" alt="Quick Start"></img>

## 📚 More Examples - Cookbook

You can find various examples of Chainlit apps [here](https://github.com/Chainlit/cookbook) 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](https://discord.gg/k73SQ3FyUh).

## 💁 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](/CONTRIBUTING.md).

## 📃 License

Chainlit is open-source and licensed under the [Apache 2.0](LICENSE) license.