billion-context: Context-Compression Plugin for Long-Lived Coding Sessions

The `billion-context` project is a context-compression tool designed to manage long-running single sessions that accumulate billions of tokens. By compressing conversational history into layered summaries, it aims to reduce token consumption and prevent context-window degradation on supported model APIs.

Core Capabilities

• Token Savings: Operates with smaller context windows (such as 100K) while targeting significantly fewer consumed tokens.
• Model-Driven Compression: The AI model decides when and what to compress using injected tools rather than hitting a hard truncation limit.
• Incremental & Reversible: Summaries are structured in small ranges, allowing on-demand decompression while maintaining prefix-cache efficiency.

Installation and Setup

Users can install the plugin via npm or run it as a launcher depending on their workflow:

• User-Level Prefix (Recommended): `npm install -g billion-context --prefix=~/.local` avoids permission errors on Linux and macOS.
• Native Plugin: Commands like `bili plugin install` integrate the proxy into supported clients such as Pi, OpenCode, and Claude Code.
• Launcher Mode: Wraps a client in a single command, spawning an independent proxy instance without modifying existing configuration files.

Verification and Monitoring

Once running, logs track cache health and compression events (`~/.local/state/billion-context/bili.log`). A healthy session targets a 95–97% prefix-cache hit rate. Users can also check cache statistics directly inside supported clients using commands like `/acp-cache` or inspect a web dashboard available locally.

Practical Implications & Verification

Adopting context compression can help developers maintain extended coding sessions without losing historical context or exceeding provider token limits. However, unreleased features on the development branch may be unstable, and users should rely on official release channels. Always verify installation steps, client compatibility, and configuration backups directly against the original GitHub repository before deployment.