Moderix
Autonomous AI agents for scalable Trust & Safety content moderation in OpenEnv environments, featuring high-performance routing.
Why it exists
Built for the Meta x Scaler x PyTorch hackathon. We set out to solve the massive scaling challenges of content moderation by creating autonomous trust and safety agents that run locally.
How it works
- Implements specialized moderation routing agents built on PyTorch.
- Packages local inference environments cleanly inside Docker containers.
- Orchestrates multi-agent handoffs for text and visual content evaluation.
- Serves low-latency agent models deployed on Hugging Face Spaces.
What happened
We wrote the entire codebase in an intense 5-day hackathon sprint. Near the deadline, we ran our test suite of 26 test cases: 23 failed, and only 3 passed. It was a chaotic, eye-opening experience. We debugged until the final hours, learned a massive amount about agent stability, and managed to get the system operational.
What I'd change
I'd move the agent routing decision matrix from rules-based weights to a lightweight, fine-tuned classification model to handle nuanced semantic contexts more dynamically.