Unlocking LLaMA 3 with Ollama: A Beginner's Guide

Unlocking LLaMA 3 with Ollama: A Beginner's Guide

Hey there! I'm Tommy, and I'm excited to guide you through the fascinating world of AI and generative models. This tutorial is perfect for anyone interested in tech, especially those looking to build cool projects for hackathons. We'll be using Ollama to make it easy for everyone, regardless of their computer's capabilities. Let's dive into the magic of LLaMA 3, an incredible generative model, and see how it can transform your ideas into reality!

🎯 Objectives

By the end of this tutorial, you'll be able to:

• Set up and use the LLaMA 3 model via Ollama.
• Implement basic chat functionality using the LLaMA 3 model.
• Stream responses for real-time feedback.
• Maintain ongoing dialogue with context.
• Complete text prompts effectively.
• Generate SQL queries from text inputs.
• Create custom clients to interact with the Ollama server.

📋 Prerequisites

Before we get started, make sure you have the following:

• Basic knowledge of Python
• A code editor like Visual Studio Code (VSCode)
• A computer with internet access

🚀 Instructions on How to Install LLaMA3

In this section, we'll walk you through the process of setting up LLaMA 3 using Ollama. LLaMA 3 is a powerful generative model that can be used for various natural language processing tasks. We'll be using Ollama to interact with LLaMA 3 and run our Python scripts.

Installation and Setup

First, you'll need to set up Ollama and install the required libraries. We'll be using the Ollama app to interact with LLaMA 3.

1. Download and Install Ollama: Go to Ollama's official website and download the desktop app. Follow the installation instructions for your operating system.

2. Start the Ollama App: Once installed, open the Ollama app. The app will run a local server that the Python library will connect to behind the scenes.

3. Download LLama3 Locally: Open your local terminal and run the following code below to download llama3 8 billion paramater 4bit locally, which we will use in our program.

   ollama pull llama3
   

4. Install Ollama Python Library: Still in your local terminal, run the following code to install the Ollama library for Python.

   pip3 install ollama
   

🛠️ Practical Applications

Create a Python file named llama3_demo.py or whatever you prefer just make sure it has a .py extension. Copy and paste the following code snippets into your file to explore the practical applications of LLaMA 3 with Ollama.

Conversation Initiation

LLama3 can be used to initiate a conversation with the llama3 model, you can use the chat function:

import ollama

prompt = 'Create a product description for a new smartphone:'
response = ollama.chat(model='llama3', messages=[{
    'role': 'user',
    'content': prompt,
},
])
print(response['message']['content'])

Streaming Responses

For applications requiring real-time feedback, you can enable streaming responses. This allows you to receive parts of the response as they are generated:

import ollama

ollama_response = ollama.chat(
    model='llama3',
    stream=True,
    messages=[
        {
            'role': 'user',
            'content': 'Explain the Big Bang theory',
        },
    ]
)

for chunk in ollama_response:
    print(chunk['message']['content'], end='', flush=True)

Ongoing Dialogue with Context

Maintaining context in a conversation allows for more natural interactions. Here's how you can manage ongoing dialogue:

import ollama

chat_messages = []

def create_message(content, role):
    return {'role': role, 'content': content}

def chat():
    response = ollama.chat(model='llama3', stream=True, messages=chat_messages)
    assistant_message = ''
    for chunk in response:
        assistant_message += chunk['message']['content']
        print(chunk['message']['content'], end='', flush=True)
    chat_messages.append(create_message(assistant_message, 'assistant'))

def ask(message):
    chat_messages.append(create_message(message, 'user'))
    print(f'\n\n--{message}--\n\n')
    chat()

ask('What is the capital of France?')
ask('How far is it from Paris to Berlin?')

Text Completion

You can use Ollama with Llama3 for text completion tasks, such as code generation or completing sentences by using the generate function:

import ollama

response = ollama.generate(
    model='llama3',
    prompt='Once upon a time, in a faraway land,'
)
print(response['response'])

Custom Clients

You can also create custom client to interact with the Ollama server. Here's an example of a custom client:

from ollama import Client

client = Client(host='http://your-ollama-server')
response = client.chat(model='llama3', messages=[
    {
        'role': 'user',
        'content': 'What is machine learning?',
    }
])
print(response['message']['content'])

Generating SQL from Text

Ollama can be used to generate SQL queries from natural language inputs. Here's how to set up a local instance and use it:

from ollama import Client

client = Client(host='http://localhost:11434')

prompt = 'Get the top 10 most expensive products.'
response = client.chat(model='llama3', messages=[
    {
        'role': 'system',
        'content': """Here is the database schema that the SQL query will run on:
    CREATE TABLE products (
      product_id INTEGER PRIMARY KEY,
      name VARCHAR(50),
      price DECIMAL(10,2),
      quantity INTEGER
    );
    """,
    },
    {
        'role': 'user',
        'content': prompt,
    }
])
print(response['message']['content'])

🖥️ Running Your Python File

To run your Python file, open your terminal, navigate to the directory where your llama3_demo.py file is located, and run:

python3 llama3_demo.py

🎓 Conclusion

In this tutorial, we explored the basics of LLaMA 3, how to set it up, and practical applications using Ollama. You learned how to implement chat functionality, streaming responses, maintain dialogue context, complete text, generate SQL, and create custom clients. With these skills, you're ready to build exciting AI projects.

For more details, check out the Ollama Blog on Python & JavaScript Libraries.

Happy coding, and enjoy your AI journey!