DEV Community· Amrendra N Mishra·· 4 小時前AI 評分39
會逐漸瞭解你的個人 AI 助理
Personal AI Assistant That Learns About You
AI 導讀
文章示範如何透過 Ollama 在 MacBook 本機運行 llama3.2，建立免費、私密且快速的個人 AI 助理，並稱其達到 GPT-4 級別。文中列出 llama3.2、codellama、mistral、phi3 和 gemma2 等可用模型，作者表示已用這套技術建立 45 個免費、本機及開源工具。
正文
The Problem With Cloud AI
Every token costs money. Every API call adds up. And your data goes to their servers.
The Local Alternative
brew install ollama
ollama pull llama3.2
ollama serve
Now you have a GPT-4 level model running on your MacBook. Free. Private. Fast.
Real Code Example
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)
Available Models
| Model | Size | Best For |
|---|---|---|
| llama3.2 | 2GB | General use |
| codellama | 4GB | Code tasks |
| mistral | 4.4GB | Fast reasoning |
| phi3 | 2.2GB | Lightweight tasks |
| gemma2 | 5.4GB | Complex reasoning |
What You Can Build
- RAG systems for your documents
- Voice assistants that work offline
- Code reviewers on every git commit
- Content generators at zero cost
- Personal AI that remembers you
My Setup
I built 45 tools using this stack. All free. All local. All open source.
github.com/amrendramishra/ai-tools
VP at JPMorgan Chase. Building AI tools at amrendranmishra.dev
來源：DEV Community · dev.to