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In this tutorial, we’ll walk through the steps to create a Chainlit application integrated with Embedchain. Preview of what you'll be building

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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.

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With Embedchain

app.py
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()

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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: 
chainlit run app.py -w

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Next Steps

Congratulations! You’ve just created your first LLM app with Chainlit and Embedchain. Happy coding! 🎉