Morph makes it easy to create chat apps that utilise the LLM API and share them with your team. In this tutorial, you will create a chat app using Morph’s LLM components and OpenAI’s API.

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Prerequisites

Please install pageckages in advance by the following command. 
pip install openai
Obtain the OpenAI API key in advance from the OpenAI dashboard and save it in an .env file.
.env
OPENAI_API_KEY=your_api_key

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Output

chatbot

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Tutorial

Create a chat app using the <LLM /> component and the LLM API. Implement the chat app logic in the Python function and use the yield to stream the chat logs, allowing the <LLM /> component to automatically display the streaming results.
Implement the logic to answer user questions using the OpenAI SDK. The function specified in the postData attribute of the <LLM /> component takes prompt and thread_id as arguments.
  • prompt: The prompt entered by the user
  • thread_id: The ID of the chat thread. A new ID is issued when a new thread is opened.
import os
import morph
from morph import MorphGlobalContext
from openai import OpenAI

@morph.func
def llm_chat_app(context: MorphGlobalContext):
    client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
    prompt = context.vars["prompt"]
    # thread_id can be used to identify the chat thread
    thread_id = context.vars["thread_id"]

    # chat
    messages = [{"role": "user", "content": prompt}]
    response = client.chat.completions.create(
        model="gpt-4o",
        messages=messages,
        stream=True,
    )

    for chunk in response:
        yield chunk.choices[0].delta.content