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chopratejas bf779b54e6 Fix all mypy type errors and flaky embedding test 
- Fix 34 mypy errors across 17 files with type annotations and casts
- Add type: ignore comments for legitimate dynamic patterns
- Handle None operands with (value or 0) pattern
- Cast return values to proper types (int, float, str, bool)
- Add EstimatingTokenCounter imports where needed
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- Fix flaky test_paraphrase_match with more distinct semantic examples
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2026-01-10 18:27:33 -08:00
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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