Multi-Agent AI Systems: Build Without CrewAI or AutoGen

A developer built a set of 45 open-source AI tools running entirely on local models via Ollama, avoiding paid API calls and sending no data to third-party servers. The stack uses llama3.2 and other small models served from localhost through a simple Python requests wrapper, with the code published on GitHub.

Every token costs money. Every API call adds up. And your data goes to their servers. brew install ollama ollama pull llama3.2 ollama serve Now you have a GPT-4 level model running on your MacBook. Free. Private. Fast. python 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 | 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 | I built 45 tools using this stack. All free. All local. All open source. github.com/amrendramishra/ai-tools https://github.com/amrendramishra/ai-tools VP at JPMorgan Chase. Building AI tools at amrendranmishra.dev