Your agent pays twice for output it has already seen. OMNI returns a handle instead: 97.2% off a file read twice. Nothing deleted, nothing invented.
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Updated
Oct 9, 2026 - Rust
Your agent pays twice for output it has already seen. OMNI returns a handle instead: 97.2% off a file read twice. Nothing deleted, nothing invented.
This repository is the official implementation of Generative Context Distillation.
Bakes a system prompt into a LoRA adapter, so a chat model behaves as if prompted without the prompt in its context. It trains on the KL divergence to the prompted model, after Prompt Baking (arXiv 2409.13697). PyTorch, Transformers and PEFT, Qwen3.5 by default, and it fits an 8 GB GPU.
Pack a repo, docs site or folder into a trained KV cache your LLM reads instead of a giant prompt. Open source, self-hosted.
To associate your repository with the context-distillation topic, visit your repo's landing page and select "manage topics."