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chopratejas 90d3aea44c Publish headroom-ai v0.2.0 to PyPI with DevEx fixes 
- Renamed package from 'headroom' to 'headroom-ai' (PyPI name conflict)
- Fixed numpy/jinja2 imports to be lazy (core install no longer crashes)
- Fixed SQLite default path (now uses temp directory)
- Fixed f-string {tool} crash in proxy server
- Updated README with correct package name and examples
- Added quickstart and troubleshooting docs

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-10 14:51:08 -08:00
..
api.md Prepare for OSS release v0.2.0 2026-01-07 11:36:44 -08:00
ARCHITECTURE.md feat: Add CCR architecture, TOIN telemetry, and DevEx improvements 2026-01-10 10:12:13 -08:00
getting-started.md Prepare for OSS release v0.2.0 2026-01-07 11:36:44 -08:00
proxy.md Prepare for OSS release v0.2.0 2026-01-07 11:36:44 -08:00
quickstart.md Publish headroom-ai v0.2.0 to PyPI with DevEx fixes 2026-01-10 14:51:08 -08:00
README.md Prepare for OSS release v0.2.0 2026-01-07 11:36:44 -08:00
transforms.md Prepare for OSS release v0.2.0 2026-01-07 11:36:44 -08:00
troubleshooting.md Publish headroom-ai v0.2.0 to PyPI with DevEx fixes 2026-01-10 14:51:08 -08:00

README.md

Headroom Documentation

Welcome to the Headroom documentation.

Quick Links

Overview

Headroom is the Context Optimization Layer for LLM applications. It reduces your LLM costs by 50-90% through intelligent context compression.

Core Concepts

  1. Transforms: Stateless functions that modify message arrays to reduce tokens
  2. Providers: Adapters for different LLM providers (OpenAI, Anthropic, etc.)
  3. Pipeline: Chains multiple transforms together
  4. Proxy: HTTP server that applies transforms transparently

Getting Help