➜ brew install ollama

➜ ollama serve

# (optionally) I run Ollama as a background service
➜ brew services start ollama

# This takes a while (defaults to the llama3.1:8b model)
➜ ollama pull llama3.1:latest 

# (optional) This takes a longer time
➜ ollama pull llama3.1:70b

# (optional) This takes so long that I skipped it and ordered a CAT6 cable...
# ollama pull llama3.1:405b

➜ ollama run llama3.1:latest
>>> how much is 2+2?
The answer to 2 + 2 is:
4!```

## Accessing Ollama Llama 3.1 with Python

The Ollama project has an [`ollama-python`](https://github.com/ollama/ollama-python) library, which I use to build applications. 

My demo has a bit of flare because there are a few options, like `--stream,` that improve the quality of life while waiting for Ollama to return results. 

```python
# hello-llama.py
import typer

from enum import Enum
from ollama import Client
from rich import print


class Host(str, Enum):
    local = "http://127.0.0.1:11434"
    the_office = "http://the-office:11434"


class ModelChoices(str, Enum):
    llama31 = "llama3.1:latest"
    llama31_70b = "llama3.1:70b"


def main(
    host: Host = Host.local,
    local: bool = False,
    model: ModelChoices = ModelChoices.llama31,
    stream: bool = False,
):
    if local:
        host = Host.local

    client = Client(host=host.value)

    response = client.chat(
        model=model.value,
        messages=[
            {
                "role": "user",
                "content": \
                    "Please riff on the 'Llama Llama Red Pajama' book but using AI terms like the 'Ollama' server and the 'Llama 3.1' model."
                    "Instead of using 'Llama Llama', please use 'Ollama Llama 3.1'.",
            }
        ],
        stream=stream,
    )

    if stream:
        for chunk in response:
            print(chunk["message"]["content"], end="", flush=True)
        print()

	else:
        print(f"[yellow]{response['message']['content']}[/yellow]")

if __name__ == "__main__":
    typer.run(main)

# Install a few "nice to have" libraries
➜ pip install ollama rich typer

# Run our demo
➜ python hello-llama.py --stream

Here's a riff on "Llama Llama Red Pajama" but with an AI twist:

**Ollama Llama 3.1, Ollama Llama 3.1**
Mama said to Ollama Llama 3.1,
"Dinner's done, time for some learning fun!"
But Ollama Llama 3.1 didn't wanna play
With the data sets and algorithms all day.

He wanted to go out and get some rest,
And dream of neural nets that were truly blessed.
But Mama said, "No way, young Ollama Llama 3.1,
You need to train on some more NLP."

Ollama Llama 3.1 got so mad and blue
He shouted at the cloud, "I don't wanna do this too!"
But then he remembered all the things he could see,
On the Ollama server, where his models would be.

So he plugged in his GPU and gave a happy sigh
And trained on some texts, till the morning light shone high.
He learned about embeddings and wordplay too,
And how to chat with humans, that's what he wanted to do.

**The end**

➜ launchctl setenv OLLAMA_HOST 0.0.0.0:11434
➜ launchctl setenv OLLAMA_ORIGINS http://*

# Restart the Ollama server to pick up on the ENV vars
➜ brew services restart ollama

# Install llm
➜ brew install llm

# Install llm-ollama
➜ llm install llm-ollama

# List all of models from Ollama
➜ llm ollama list-models

# 
➜ llm -m llama3.1:latest "how much is 2+2?"
The answer to 2 + 2 is:

4