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

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

If you are using a cloud environment, set this as an environment variable in the “Data” tab.

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Output

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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 create_chunk function 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 morph_lib.stream import create_chunk
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 create_chunk(chunk.choices[0].delta.content)
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