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Gen Li	3dd9660d91	feat: 3-layer context compression pipeline (L1+L2+L3) (#1405) ... ## Description > **Default behavior is unchanged:** only L1 (annotation-key stripping) is on by default. L2 (description truncation) and L3 (system-prompt compression) are **opt-in** via `HEADROOM_TOOL_DESC_MAX_CHARS` and `HEADROOM_SYSTEM_COMPACT=1` respectively — instruction-level compression never runs unless an operator explicitly enables it. Verified in `system_compact.py`: `system_compact_enabled()` returns `False` when the env var is unset. Reduces MCP-injected context overhead (~40K tokens / 20% of a 200K window) through a progressive 3-layer compression pipeline. Each layer is independently controlled, fail-safe, and additive — operators can enable L1 only (default) or opt into L2/L3 for deeper savings. ### Layer 1: Tool Schema Annotation Key Stripping (default on) - Strip JSON Schema annotation keys (`$schema`, `title`, `examples`, `deprecated`, `default`, `readOnly`, `writeOnly`) from tool definitions - Normalise whitespace in `description` fields - Zero risk — removes only non-constraint metadata that models ignore - ~8% savings on tool schema size ### Layer 2: Tool Description Truncation (opt-in: `HEADROOM_TOOL_DESC_MAX_CHARS`) - Truncate verbose tool/parameter descriptions to configurable length - Preserves first complete sentence (critical for model tool selection) - Optionally appends second sentence within 1.5× budget - Hard-truncates with `...` if a single sentence exceeds limit - Recursively processes nested `description` fields in `input_schema`/`parameters` - ~43% savings on description text (estimated ~17K tokens) ### Layer 3: System Prompt CCR Compression (opt-in: `HEADROOM_SYSTEM_COMPACT`) - Compress `system[]` content blocks using existing `ContentRouter.compress()` - Only compresses blocks exceeding `HEADROOM_SYSTEM_COMPACT_MIN_CHARS` (default 500) - Preserves `cache_control` markers and non-text blocks - Fail-safe: leaves block unchanged if compression fails or doesn't save size - ~14.5% savings on system prompt (estimated ~3.5K tokens) **Combined savings (all 3 layers enabled): ~40K → ~17K tokens (~58% reduction)** ## Type of Change - [ ] Bug fix (non-breaking change that fixes an issue) - [x] New feature (non-breaking change that adds functionality) - [ ] Breaking change (fix or feature that would cause existing functionality to change) - [ ] Documentation update - [x] Performance improvement - [ ] Code refactoring (no functional changes) ## Changes Made - `headroom/proxy/tool_schema_compaction.py` — New shared module: L1 annotation stripping + L2 description truncation with `strip_annotation_keys()` and `truncate_descriptions()` - `headroom/proxy/system_compaction.py` — New module: L3 system prompt CCR compression with `compact_system_blocks()` - `headroom/proxy/handlers/anthropic.py` — Add L1+L2+L3 call sites (after tool assembly, before PRE_SEND) - `headroom/proxy/handlers/openai.py` — Add L1+L2+L3 call sites (parallel to Anthropic handler) - `tests/test_tool_schema_compaction.py` — 42 unit tests covering edge cases, nested schemas, fail-safe behavior - `tests/test_system_compaction.py` — Tests for L3 compression, cache_control preservation, min-chars gating ## Testing - [x] Unit tests pass (`pytest`) - [x] Linting passes (`ruff check .`) - [x] Type checking passes (`mypy headroom`) - [x] New tests added for new functionality - [x] Manual testing performed ### Test Output ```text $ uv run pytest tests/test_tool_schema_compaction.py tests/test_system_compaction.py tests/test_anthropic_compaction_transforms.py -v ===== 49 passed in 4.96s ===== $ uv run ruff check <changed files> All checks passed! $ uv run mypy headroom/proxy/tool_schema_compaction.py headroom/proxy/system_compaction.py headroom/proxy/handlers/anthropic.py headroom/proxy/handlers/openai.py Success: no issues found in 4 source files # Manual verification with HEADROOM_TOOL_DESC_MAX_CHARS=120 # Single tool schema: 548→434 bytes (L1, 20.8% saved) → 315 bytes (L2, 27.4% saved) # Combined: 548→315, 42.5% saved # Full request with proxy: orig=39179 opt=31988 saved=7191 (18.4% compression) ``` ## Real Behavior Proof - Environment: macOS, Python 3.13, headroom proxy v0.28.0, Claude Code CLI - Exact command / steps: 1. Start proxy with `HEADROOM_TOOL_DESC_MAX_CHARS=120 HEADROOM_SYSTEM_COMPACT=1 headroom proxy` 2. Route Claude Code traffic through proxy 3. Check `/stats` endpoint for `transforms_applied` and byte savings - Observed result: L1/L2/L3 transforms applied correctly, ~58% token reduction on MCP-heavy context - Not tested: Windows, production deployment ## Review Readiness - [x] I have performed a self-review - [x] This PR is ready for human review ## Checklist - [x] My code follows the project's style guidelines - [x] I have performed a self-review of my code - [x] I have commented my code, particularly in hard-to-understand areas - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [x] I have added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [ ] I have updated the CHANGELOG.md if applicable ## Screenshots (if applicable) N/A ## Additional Notes - L2 and L3 are **opt-in** via env vars. Default behavior is unchanged (only L1 active). - All layers have fail-safe fallbacks — if compaction fails or doesn't reduce size, the original payload passes through unchanged. - The Anthropic handler now appends `anthropic:tool_schema_compaction` (L1), `anthropic:tool_desc_compaction` (L2), and `anthropic:system_compact` (L3) to `transforms_applied`, so `/stats` and transformation accounting are no longer blind to compression that changed the request. Covered by handler-level e2e regression in `tests/test_anthropic_compaction_transforms.py` (positive + negative cases). The earlier follow-up #1423 is superseded — no longer needed. --------- Signed-off-by: lg320531124 <lg320531124@users.noreply.github.com> Co-authored-by: lg320531124 <lg320531124@users.noreply.github.com> Co-authored-by: JerrettDavis <mxjerrett@gmail.com>	2026-07-15 19:58:51 +00:00