AI Code Reviewer: Never Ship Bugs Again

Описание и применение

Запуск локальной модели Llama3.2 на MacBook устраняет расходы на токены, сохраняет данные приватными и обеспечивает мгновенные ответы для проверки кода и других задач.

Задача

Every token costs money, each API call adds up, and data is sent to cloud servers.

Результат

Local LLM deployment eliminates API costs, keeps data private, and offers instant responses for code review and other AI tasks.

Рабочий процесс

• Install Ollama via Homebrew
• Pull the llama3.2 model with ollama pull llama3.2
• Start the local server with ollama serve
• Send requests to http://localhost:11434/api/generate using the provided Python snippet

Доказательства

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

Источник

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

Источник

brew install ollama ollama pull llama3.2 ollama serve

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

Источник