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[GitHub Trending] chopratejas/headroom

7.9 relevance
Score Breakdown
technical depth
8
novelty
8
actionability
8
community
7
strategic
7
personal
9

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Token compression tool for LLM inputs, highly actionable and directly relevant to AI/ML cost optimization and agent systems.

AI/ML github.com
Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 60-95% fewer tokens, same answers. Library, proxy, MCP server. - chopratejas/headroom
Summary

Headroom is an open-source context compression layer for AI agents that reduces token consumption by 60–95% before prompts reach the LLM. It operates as a Python/TypeScript library, a zero-code proxy, an agent wrapper for Claude/Cursor/Codex, or an MCP server, using six algorithms (including AST-based CodeCompressor and a HuggingFace model) to compress tool outputs, logs, RAG chunks, and conversation history while caching originals for reversible retrieval via CCR. Benchmarks show 92% savings on SRE debugging and code search workloads with no accuracy loss on GSM8K or SQuAD v2.

Author

chopratejas