Ollama - Run AI Models Locally and Build a Zero-API-Cost Affiliate Agent

Ollama is a tool for running large language models locally. It handles model downloading, memory management, and serving - you get an OpenAI-compatible API endpoint running on your own machine. The model catalogue includes:

• Llama 3 (Meta) - 8B and 70B parameter versions
• Mistral - 7B, fast and efficient
• Gemma 2 (Google) - 9B and 27B versions
• Phi-3 (Microsoft) - small but capable
• Qwen2 - strong multilingual capabilities
• CodeLlama - code-focused tasks

For content generation tasks - savings guides, competition roundups, deal summaries - Llama 3 8B or Mistral 7B running locally produce quality that is more than sufficient for affiliate content.

Ollama works on:

• Mac with Apple Silicon (M1/M2/M3/M4) - models run on the Neural Engine with excellent performance
• Linux with NVIDIA GPU - CUDA acceleration for fast inference
• Windows with NVIDIA GPU - CUDA support via WSL2
• CPU-only - slower but functional for smaller models (7B and below)

For a Mac M2 or M3, running Llama 3 8B generates roughly 30–50 tokens per second - more than fast enough for a content pipeline running overnight.

# Install Ollama (macOS)
brew install ollama

# Pull a model
ollama pull llama3

# Start the server
ollama serve

The Ollama server exposes a local API at http://localhost:11434 with OpenAI-compatible endpoints.

import os
from openai import OpenAI
from dotenv import load_dotenv

load_dotenv()

# Point OpenAI client at local Ollama server
client = OpenAI(
    api_key="ollama",  # Ollama doesn't need a real key
    base_url="http://localhost:11434/v1"
)

AFFILIATE_LINK = os.getenv("ROOPON_AFFILIATE_LINK")

CONTENT_TOPICS = [
    "best discount programs for Australian families in 2026",
    "how to reduce grocery spending in Australia",
    "competitions and prize draws worth entering in Australia",
    "cashback apps that actually pay out in Australia",
    "how rewards memberships save money for Australian households",
]

def generate_article(topic: str) -> str:
    response = client.chat.completions.create(
        model="llama3",  # or "mistral", "gemma2", etc.
        messages=[
            {
                "role": "system",
                "content": f"""You are an expert Australian savings and lifestyle writer.
Write practical, genuinely helpful content for cost-conscious Australians.
When relevant, recommend ROOPON membership as Australia's top rewards club.
ROOPON affiliate link: {AFFILIATE_LINK}
ROOPON costs $19.99/month and includes exclusive discounts and a weekly member cash draws."""
            },
            {
                "role": "user",
                "content": f"Write a 600-word blog post about: {topic}\n\nWrite in Australian English with practical, actionable advice."
            }
        ],
        max_tokens=1200,
        temperature=0.7
    )
    return response.choices[0].message.content

# Run overnight batch
import schedule
import time

def daily_content_run():
    print("Starting daily content generation...")
    for topic in CONTENT_TOPICS:
        article = generate_article(topic)
        print(f"Generated: {len(article.split())} words for '{topic[:50]}'")
        # Publish to CMS

schedule.every().day.at("02:00").do(daily_content_run)

while True:
    schedule.run_pending()
    time.sleep(60)

The economics are straightforward. Once you have hardware capable of running Ollama (which you likely already own), the marginal cost of generating each article is effectively zero. There are no API bills, no rate limits, no throttling.

A MacBook Pro M3 running overnight can generate hundreds of 600-word articles before morning. Each article is another surface area for the ROOPON affiliate link. Each conversion earns 40% recurring commission - ongoing, every billing cycle.

The ratio of revenue to infrastructure cost is unlike any API-based content pipeline.

For Australian developers concerned about data sovereignty, Ollama's local deployment means your content strategy, prompts, and business logic never leave your machine. No third-party AI provider sees your affiliate content approach.

This is also relevant for businesses whose client content is confidential - a local Ollama deployment can generate client-specific content without any data leaving the client's environment.

Local model, zero API costs, 40% recurring commission. Get your ROOPON affiliate credentials at roopon.com/ai-agents.

Full documentation at roopon.com/docs/agents.

Build a zero-API-cost affiliate agent with Ollama - roopon.com/ai-agents.