Open-Sourced Deterministic Agent Context Compression Layer
MusicToThyEars · reddit · 2026-07-14
The author has open-sourced Context Warp Drive, a deterministic, zero-LLM context compression layer designed for long-running function-calling agents.
It aims to avoid the pitfalls of two common approaches:
- Truncating history directly: Loses valuable information
- Using another model to rewrite summaries: Risks losing exact identifiers and alters the prompt prefix
Key features of this solution include:
- Deterministic folding: Identical inputs produce a byte-for-byte consistent folded view
- Host retains original history: The model only sees a limited context
- Sealed prefixes remain byte-stable across different epochs, facilitating prompt cache reuse
- Folded evidence can be traced back via path / claim activity
- Supports message formats from Anthropic, OpenAI, and Gemini
The implementation is CPU-only, with zero I/O and no runtime dependencies. The repository also includes:
- Implementation code
- 900+ deterministic tests
- Benchmark scripts
- Evidence and caveats behind the published data
Project URL: github.com/dogtorjonah/context-warp-drive
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