Content Repurposer: One Article Becomes Seven Posts

Описание и применение

Локальная модель Llama 3.2 позволяет генерировать контент без затрат на облачные API и без передачи данных сторонним серверам.

Задача

Using cloud AI for content generation is costly, adds up per token, and sends data to external servers.

Результат

The local setup allows content generation and AI tool development without cloud costs or data exposure.

Рабочий процесс

• Install Ollama via Homebrew: brew install ollama
• Pull the Llama 3.2 model: ollama pull llama3.2
• Start the local server: ollama serve
• Send a POST request to http://localhost:11434/api/generate with the model and prompt
• Receive the response JSON and extract the response field

Доказательства

Every token costs money. Every API call adds up. And your data goes to their servers.

Источник

brew install ollama ollama pull llama3.2 ollama serve

Источник

Now you have a GPT‑4 level model running on your MacBook. Free. Private. Fast.

Источник

import requests def ask_local_ai(question): r = requests.post("http://localhost:11434/api/generate", json={"model":"llama3.2","prompt":question,"stream":False}) return r.json()["response"] # Works immediately, no API key needed answer = ask_local_ai("Explain Docker in one paragraph") print(answer)

Источник