> ## Documentation Index
> Fetch the complete documentation index at: https://docs.chainlit.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Embedchain

In this tutorial, we'll walk through the steps to create a Chainlit application integrated with [Embedchain](https://github.com/embedchain/embedchain).

<img src="https://mintcdn.com/chainlit-43/b2WeFP1vh0enOZXn/images/embedchain-example.gif?s=16fe76a33b3d2cf6f0ea5c6d418ebfa9" alt="Preview of what you'll be building" width="1180" height="720" data-path="images/embedchain-example.gif" />

## Step 1: Create a Chainlit Application

In `app.py`, import the necessary packages and define one function to handle a new chat session and another function to handle messages incoming from the UI.

### With Embedchain

```python app.py theme={null}
import chainlit as cl
from embedchain import Pipeline as App

import os

os.environ["OPENAI_API_KEY"] = "sk-xxx"

@cl.on_chat_start
async def on_chat_start():
    app = App.from_config(config={
        'app': {
            'config': {
                'name': 'chainlit-app'
            }
        },
        'llm': {
            'config': {
                'stream': True,
            }
        }
    })
    # import your data here
    app.add("https://www.forbes.com/profile/elon-musk/")
    app.collect_metrics = False
    cl.user_session.set("app", app)


@cl.on_message
async def on_message(message: cl.Message):
    app = cl.user_session.get("app")
    msg = cl.Message(content="")
    for chunk in await cl.make_async(app.chat)(message.content):
        await msg.stream_token(chunk)
    
    await msg.send()
```

## Step 2: Run the Application

To start your app, open a terminal and navigate to the directory containing `app.py`. Then run the following command:

```bash theme={null}
chainlit run app.py -w
```

## Next Steps

Congratulations! You've just created your first LLM app with Chainlit and Embedchain.

Happy coding! 🎉