Feature request: Semantic checkpoint module during inference

[elly99-AI]

I propose adding a semantic checkpoint module to the LLaMA inference pipeline.
This would allow the model to reflect on its output before emission, improving coherence and epistemic alignment.

Motivation:

LLaMA is widely used in production and research.
Introducing a semantic checkpoint — using Specter embeddings and FAISS — could help detect conceptual drift and reinforce output consistency.

Proposed Implementation:

• Embed the generated output
• Compare against a conceptual memory index
• Trigger revision or flagging if semantic misalignment is detected

Inspired by https://github.com/elly99-AI/MarCognity-AI.git, a framework for cognitive orchestration and semantic audit.