chopratejas
bd2d447c26
Add quality retention eval and fix linting for Python 3.12
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- Add quality_retention_eval.py for needle-in-haystack testing to verify
intelligent compression retains critical information (100% retention achieved)
- Add intelligent_context_integration_test.py for comprehensive pipeline testing
- Add test_progressive_summarizer.py with 36 tests for ProgressiveSummarizer
- Add HeadroomConfig parameter to HeadroomClient for direct config injection
- Update pipeline.py with IntelligentContextManager wiring and logging
- Fix all ruff linting issues and format for Python 3.12 compatibility
- Add comprehensive_eval.py benchmark for multi-scenario evaluation
- Add real_data_demo.py for production-scale volume testing
- Add reasoning agent test examples (groq, debug)
2026-01-19 21:52:18 -08:00
chopratejas
77248cd1a3
Enhance /stats endpoint and add comprehensive benchmarks
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- Add detailed breakdowns by provider and model to /stats
- Include compression, telemetry, and feedback loop statistics
- Add latency.average_ms metric
- Add real-world agent benchmark with MCP tool patterns
- Add worst-case and adversarial benchmarks for edge cases
- Bump version to 0.2.12
2026-01-17 22:49:04 -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
7a05808e0f
Add cache optimization module with scalable dynamic content detection
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Implements a comprehensive cache optimization layer for LLM providers:
- Provider-specific optimizers (Anthropic, OpenAI, Google) with distinct
caching strategies: explicit breakpoints, prefix stabilization, and
CachedContent API respectively
- Scalable dynamic content detector using three strategies:
1. Structural detection: "Label: value" patterns (language-agnostic)
2. Entropy-based detection: high-entropy strings (IDs, tokens, hashes)
3. Universal patterns: ISO 8601, UUIDs, JWTs, hex hashes
- NO hardcoded locale-specific patterns (no month names, etc.)
- Semantic caching layer with LRU eviction and TTL support
- Plugin registry for provider selection and custom optimizers
- 131 tests, real-world benchmarks showing 20-55% compression at <0.3ms
2026-01-07 14:07:49 -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
