Your first chat with an LLM 🗣️🤖

Working with an LLM

Many different chat providers

• OpenAI ChatGPT
• Anthropic Claude
• Google Gemini
• xAI Grok
• Meta Llama

etc…

Demo: OpenAI ChatGPT

from pprint import pprint

from dotenv import load_dotenv
from openai import OpenAI

load_dotenv()  # Loads OPENAI_API_KEY from the .env file

# Creates an OpenAI client, which can be used to access any OpenAI service
# (including Whisper and DALL-E, not just chat models). It's totally stateless.
client = OpenAI()

# The initial set of messages we'll start the conversation with: a system
# prompt and a user prompt.
messages = [
    {"role": "system", "content": "You are a terse assistant."},
    {"role": "user", "content": "What is the capital of the moon?"},
]

# Call out to the OpenAI API to generate a response. (This is a blocking call,
# but there are ways to do async, streaming, and async streaming as well.)
response = client.chat.completions.create(
    model="gpt-4.1",
    messages=messages,
)

# Print the response we just received.
print(response.choices[0].message.content)
# If you want to inspect the full response, you can do so by uncommenting the
# following line. The .dict() is helpful in getting more readable output.
# pprint(response.dict())

# The client.chat.completions.create() call is stateless. In order to carry on a
# multi-turn conversation, we need to keep track of the messages we've sent and
# received.
messages.append(response.choices[0].message)

# Ask a followup question.
messages.append({"role": "user", "content": "Are you sure?"})
response2 = client.chat.completions.create(
    model="gpt-4.1",
    messages=messages,
    stream=True,
)

for chunk in response2:
    print(chunk.choices[0].delta.content or "", end="", flush=True)
print()

GitHub Models

GitHub Models: https://github.com/marketplace/models

• Free tiers of all the latest models
• Playground to tinker with them

https://docs.github.com/en/github-models/use-github-models/prototyping-with-ai-models#rate-limits

Your turn: OpenAI / GitHub

05:00

Note

Make sure you have created a GitHub PAT (you do not need any specific context)

import os
from pprint import pprint

from dotenv import load_dotenv
from openai import OpenAI

load_dotenv()

# arguments passed switch to using GitHub models
client = OpenAI(
  api_key=os.environ["GITHUB_TOKEN"],
  base_url="https://models.inference.ai.azure.com"
)

messages = [
    {"role": "system", "content": "You are a terse assistant."},
    {"role": "user", "content": "What is the capital of the moon?"},
]

response = client.chat.completions.create(
    model="gpt-4.1",
    messages=messages,
)
print(response.choices[0].message.content)

messages.append(response.choices[0].message)

messages.append({"role": "user", "content": "Are you sure?"})
response2 = client.chat.completions.create(
    model="gpt-4.1",
    messages=messages,
    stream=True,
)

for chunk in response2:
    print(chunk.choices[0].delta.content or "", end="", flush=True)
print()

Educator Developer Blog

How to use any Python AI agent framework with free GitHub Models

Chatlas + Ellmer

Unify the prompt creation process and steps

Python

https://posit-dev.github.io/chatlas/

R

https://ellmer.tidyverse.org/

Demo: Chatlas + Ellmer (OpenAI)

Python Chatlas

from chatlas import ChatOpenAI
from dotenv import load_dotenv

load_dotenv()  # Loads OPENAI_API_KEY from the .env file

chat = ChatOpenAI(model="gpt-4.1", system_prompt="You are a terse assistant.")

chat.chat("What is the capital of the moon?")

chat.chat("Are you sure?")

Demo: Chatlas + Ellmer (Claude)

Python Chatlas

from chatlas import ChatAnthropic
from dotenv import load_dotenv

load_dotenv()

chat = ChatAnthropic(model="claude-3-7-sonnet-latest", system_prompt="You are a terse assistant.")

chat.chat("What is the capital of the moon?")

chat.chat("Are you sure?")

Your turn: Chatlas Ellmer GitHub

10:00

Python Chatlas

import os

from chatlas import ChatGithub
from dotenv import load_dotenv

load_dotenv()

chat = ChatGithub(
    model="gpt-4.1",
    system_prompt="You are a terse assistant.",
    api_key=os.getenv("GITHUB_PAT"),
)

chat.chat("What is the capital of the moon?")
chat.chat("Are you sure?")