chopratejas
7a34030b0d
Fix mypy type errors in LiteLLM and OpenAI providers
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- Add type: ignore[assignment] comments for optional litellm imports
- Add None checks before accessing optional module functions
- Handle nullable max_input_tokens and max_output_tokens values
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 16:42:11 -08:00
chopratejas
905c229251
Add AST-based code compression and custom model configuration
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CodeAwareCompressor:
- Tree-sitter based AST parsing for Python, JS, TS, Go, Rust, Java, C, C++
- Preserves imports, signatures, type annotations, error handlers
- Guarantees syntactically valid output
- Uses tree-sitter-language-pack for broad language support
ContentRouter:
- Intelligent compression orchestrator
- Auto-routes content to optimal compressor based on type detection
- Source hint support for high-confidence routing
Custom Model Configuration:
- HEADROOM_MODEL_LIMITS env var and ~/.headroom/models.json support
- Pattern-based inference for unknown models (opus/sonnet/haiku tiers)
- Support for Claude 4.5, Claude 4, o3, o3-mini
- Graceful fallback - never crashes on unknown models
2026-01-14 13:46:55 -08:00
chopratejas
e4a41faa33
Fix all ruff lint and format errors for CI
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- Fix E402: Move module-level imports to top of file
- Fix F401: Add noqa for availability check imports
- Fix F402: Rename loop variables shadowing imports
- Fix E722: Replace bare except with except Exception
- Fix B904: Add exception chaining (from e)
- Fix F811: Remove duplicate imports
- Fix B027: Add noqa for empty close() method
- Fix E741: Rename ambiguous variable l -> label
- Fix I001: Import sorting issues
- Apply ruff format to all 106 files
All 902 tests pass.
2026-01-10 15:33:44 -08:00
chopratejas
175746cc26
Prepare for OSS release v0.2.0
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This commit prepares Headroom for public open source release with
comprehensive documentation, licensing, and community infrastructure.
License & Legal:
- Add Apache 2.0 LICENSE file
- Add NOTICE file with third-party attributions
- Add SECURITY.md for vulnerability reporting
Community:
- Add CONTRIBUTING.md with contribution guidelines
- Add CODE_OF_CONDUCT.md (Contributor Covenant)
- Add GitHub issue templates (bug report, feature request)
- Add pull request template
Documentation:
- Update README.md with compelling value proposition
- Add docs/getting-started.md
- Add docs/proxy.md for proxy server documentation
- Add docs/transforms.md for transform reference
- Add docs/api.md for API reference
- Add examples/README.md
Package Infrastructure:
- Add headroom/py.typed for PEP 561 compliance
- Add headroom/cli.py for CLI entry point
- Add .github/workflows/ci.yml for CI pipeline
- Add .github/workflows/publish.yml for PyPI publishing
- Update pyproject.toml with proper metadata
New Features:
- Add multi-provider support (Google, Cohere, LiteLLM, OpenAI-compatible)
- Add universal tokenizer registry with multiple backends
- Add model registry with pricing and context limits
- Add production proxy server with caching and rate limiting
Code Quality:
- Fix 83 lint issues via ruff auto-fix
- Fix version consistency (benchmarks 0.1.0 → 0.2.0)
- Add skip decorators for optional dependency tests
2026-01-07 11:36:44 -08:00
chopratejas
9c7d4512d6
Initial commit: Headroom SDK - LLM context optimization toolkit
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A comprehensive SDK for optimizing LLM context windows, reducing token
usage while preserving critical information for AI agents.
Core Features:
- SmartCrusher: Statistical compression of tool outputs (70-85% reduction)
- CacheAligner: Prefix optimization for prompt cache hits
- RollingWindow: Intelligent context window management
- BM25/Hybrid relevance scoring for smart item selection
Integrations:
- OpenAI and Anthropic provider support
- LangChain integration (ChatModel, Callbacks, Runnable)
- MCP (Model Context Protocol) integration for tool compression
Test Coverage:
- 372 tests passing across all modules
- 35 performance benchmarks
- Real-world agent evaluations with 88% token savings
Key Components:
- headroom/transforms/: Core compression transforms
- headroom/providers/: OpenAI and Anthropic support
- headroom/integrations/: LangChain and MCP integrations
- headroom/relevance/: BM25 and hybrid scoring
- headroom/pricing/: Model pricing registry
- benchmarks/: Performance benchmark suite
- examples/: Usage examples and demos
2026-01-06 23:16:58 -08:00
