pip3 install chainlit embedchain --upgrade

import chainlit as cl
from embedchain import App
import uuid

@cl.on_chat_start
async def chat_startup():
  app = App.from_config(config={
    "app": {
      "config": {
        "name": "my-chatbot",
        "id": str(uuid.uuid4()),
        "collect_metrics": False
      }
    },
    "llm": {
      "config": {
        "model": "gpt-3.5-turbo-0125",
        "stream": True,
        "temperature": 0.0,
      }
    }
  })

  # Add documents to be used as knowledge base for the chatbot
  app.add("my_knowledge.pdf", data_type='pdf_file')

  cl.user_session.set("app", app)

@cl.on_message
async def on_new_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()

chainlit run <your script>.py

app = App.from_config(config={
  "llm": {
    "config": {
      "base_url": "https://gr-prd.aporia.com/<PROJECT_ID>",
      "model_kwargs": {
        "default_headers": { "X-APORIA-API-KEY": "<YOUR_APORIA_API_KEY>" }
      },
      # ...
    }
  },
  # ...
})

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