Msglm

msglm

Installation

Install the latest version from pypi

$ pip install msglm

Usage

To use an LLM we need to structure our messages in a particular format.

Here’s an example of a text chat from the OpenAI docs.

from openai import OpenAI
client = OpenAI()

completion = client.chat.completions.create(
  model="gpt-4o",
  messages=[
    {"role": "user", "content": "What's the Wild Atlantic Way?"}
  ]
)

Generating the correct format for a particular API can get tedious. The goal of *msglm* is to make it easier.

The examples below will show you how to use *msglm* for text and image chats with OpenAI and Anthropic.

Text Chats

For a text chat simply pass a list of strings and the api format (e.g. “openai”) to **mk_msgs** and it will generate the correct format.

mk_msgs(["Hello, world!", "some assistant response"], api="openai")

[
    {"role": "user", "content": "Hello, world!"},
    {"role": "assistant", "content": "Some assistant response"}
]

anthropic

from msglm import mk_msgs_anthropic as mk_msgs
from anthropic import Anthropic
client = Anthropic()

r = client.messages.create(
    model="claude-3-haiku-20240307",
    max_tokens=1024,
    messages=[mk_msgs(["Hello, world!", "some LLM response"])]
)
print(r.content[0].text)

openai

from msglm import mk_msgs_openai as mk_msgs
from openai import OpenAI

client = OpenAI()
r = client.chat.completions.create(
  model="gpt-4o-mini",
  messages=[mk_msgs(["Hello, world!", "some LLM response"])]
)
print(r.choices[0].message.content)

Image Chats

For an image chat simply pass the raw image bytes in a list with your question to *mk_msgs* and it will generate the correct format.

mk_msg([img, "What's in this image?"], api="anthropic")

[
    {
        "role": "user", 
        "content": [
            {"type": "image", "source": {