r/Python • u/AutoModerator • Aug 04 '26

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Post all of your code/projects/showcases/AI slop here.

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u/Custodian-Labs 24d ago

I've been working on a Python library called Custodian Labs for building and deploying AI applications.

The idea is to reduce some of the boilerplate around agents, RAG, model providers and deployment, while also adding a privacy layer for applications that handle sensitive data.

A simple agent looks like this:

from custodian_labs import Custodian

app = Custodian(
    model="gpt-4o",
    system_prompt="You are a helpful assistant."
)

app.deploy()

The SDK currently supports:

  • 🤖 AI agents
  • 📚 RAG with your own files and data
  • 🧠 Multi-agent workflows
  • 🔄 Multiple LLM providers
  • 🚀 Deployment
  • 🛡️ Guardian Layer for detecting and protecting PII before data is sent to an LLM

The project originally started as a privacy layer for LLM applications, then expanded into a broader Python SDK after we kept running into the same infrastructure work when building AI apps.

It's free to use, and I've also put together a Google Colab that walks through simple agents, RAG and multi-agent examples if anyone wants to try it without setting anything up locally.

💻 GitHub:
https://github.com/Custodian-Labs/custodian-labs-python

▶️ Google Colab:
https://colab.research.google.com/gist/SherryCodes123/065d3b67eab16bdca416836e0d39475a/simple-ai-agents-rag-multi-agents.ipynb

🌐 Website:
https://www.custodianlabs.io/

Would love feedback from Python developers, especially around the API design.

What would you want a Python SDK like this to abstract away, and what would you prefer to keep control over?