Add LLM-Based or SLM Swarm-based Moderation Node for WarpNet

In order to enforce basic human rights and safety across the WarpNet distributed social network, we need to introduce a dedicated moderation node powered by a local LLM (Large Language Model). This node should be capable of automatically evaluating content and rejecting harmful material such as:

• Child sexual abuse material (CSAM)
• Violent or gore content
• Illegal drug or weapon sales
• Calls for terrorism or extremist violence etc.

Given the decentralized nature of WarpNet, content moderation must happen locally, without reliance on centralized infrastructure or cloud APIs. A locally-run LLM enables us to evaluate and flag content as "hidden".

Possible solutions:

• Integrate a local LLM (such as Mistral or LLaMA) into a dedicated node.
• Use llama.cpp or onnxruntime for inference, eliminating the need for Docker or external APIs.
• Define a simple moderation API (/moderate) to evaluate content before storage or broadcast.
• Optionally distribute moderation tags to peer nodes to assist in propagation control.

Good to have:

• Allow plug-in moderation models (e.g., community-trained LoRA adapters)
• Support image and video moderation via CLIP or ONNX-based classifiers
• Log moderation decisions with transparency (e.g., why a post was rejected)

Ways to integrate with the network:

• Pubsub
• Requesting list of tweets worker
• (Your solution)

Please help!