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## Description Headroom's lossy compression drops rows/lines using statistical heuristics but **never checks that meaning survived** — a dropped `OOM killed worker 3` line can silently flip a model's answer with no signal that compression caused it. The repo already ships a quality-metric toolkit (`headroom/evals/metrics.py`) and a `weekly-suite` eval job, but neither gates the compression path on a PR. This adds a **per-PR fidelity regression gate**: compress vendored golden tool-outputs through SmartCrusher's lossy path and assert the evidence that answers each case's question survives. It is the first of a planned trio (this is the "offline gate" half of the fidelity work); query-aware retention and a hard token-budget API are documented follow-ups. Closes # ## 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 - [ ] Performance improvement - [ ] Code refactoring (no functional changes) ## Changes Made - **Blocking gate** (`tests/test_compression_fidelity_regression.py`): compresses each golden case via `smart_crush_tool_output(..., with_compaction=False)` and scores with `compute_information_recall`. Two assertions: - **Per-case critical recall == 1.0** — every `answer_evidence` string (placed in error/anomaly rows, the documented SmartCrusher retention guarantee) must survive. - **Aggregate recall ≥ committed baseline** (`baseline.json`, tol 0.02) — catches softer regressions. - **Vendored fixtures** (`tests/fixtures/fidelity_golden/`): deterministic `_generate.py` emits `cases.json` (4 cases: OOM crash, payment exception, latency anomaly, CI failure) + `baseline.json`. - **Non-blocking weekly report** (`.github/workflows/eval.yml`): one step in the existing `weekly-suite` job (schedule/manual only) reuses the existing `evaluate_information_retention` runner for a recall report on the production routing path. - **Pure reuse**: scoring (`evals/metrics.py`), compressor (`smart_crush_tool_output`), and the weekly runner (`evaluate_information_retention`) all already existed. ### Design notes - **Zero new CI setup.** The blocking gate runs in the existing `[dev]` test shard — no new workflow, no new deps, **no model, no network, no secrets** (verified under `HF_HUB_OFFLINE=1`). It deliberately uses small hand-made structured fixtures rather than the repo's HuggingFace dataset loaders, which would require a network download + ModernBERT and don't belong in a fast PR gate. - **Scope:** structured JSON tool-output (the dominant, deterministic, model-free case). Real-dataset (HotpotQA/BFCL) recall — which needs `[all]` + a local model — is a **documented follow-up PR**, and the `weekly-suite` job (which genuinely runs every Monday) is its natural home. ## 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 $ HF_HUB_OFFLINE=1 python -m pytest tests/test_compression_fidelity_regression.py -v tests/test_compression_fidelity_regression.py::test_critical_evidence_survives_compression[logs_oom] PASSED tests/test_compression_fidelity_regression.py::test_critical_evidence_survives_compression[payment_exception] PASSED tests/test_compression_fidelity_regression.py::test_critical_evidence_survives_compression[latency_anomaly] PASSED tests/test_compression_fidelity_regression.py::test_critical_evidence_survives_compression[ci_test_failures] PASSED tests/test_compression_fidelity_regression.py::test_aggregate_recall_not_regressed PASSED ============================== 5 passed in 0.18s =============================== ``` ## Real Behavior Proof - **Environment:** local checkout of `feat/fidelity-regression-gate`, `pip install -e ".[dev]"`, `HF_HUB_OFFLINE=1 TRANSFORMERS_OFFLINE=1` (proves no model/network). - **Exact command / steps:** `HF_HUB_OFFLINE=1 python -m pytest tests/test_compression_fidelity_regression.py -q` → `5 passed in 0.14s`. - **Negative control (proves the gate has teeth):** compressing `logs_oom` and probing for a benign row that compression legitimately drops returns `recall = 0.00, lost = ['heartbeat ping 25']` — i.e. the gate fires when critical evidence is dropped, so it is not trivially green. - **Weekly (non-blocking) step verified locally:** ```text Information retention: 50/50 cases >=0.9 recall, avg compression 65.7% ``` - **Not tested:** real-dataset (HotpotQA/BFCL) recall and prose/ModernBERT compression — intentionally deferred to a follow-up PR targeting the weekly job. ## 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 - [x] 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 ## Additional Notes - CHANGELOG/version intentionally untouched: repo uses **release-please**. - **Follow-up PR (planned):** wire the real HotpotQA/BFCL loaders (`headroom/evals/datasets.py`) into the `weekly-suite` job for genuine benchmark-scale recall coverage (model-allowed, non-blocking). Further follow-ups from the same design: a live per-request fidelity guardrail, query-aware lossy retention, and a hard `target_tokens` budget API. Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
152 lines
6.2 KiB
YAML
152 lines
6.2 KiB
YAML
name: Evaluation Suite
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on:
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schedule:
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- cron: '0 6 * * 1' # Weekly on Monday 6am UTC
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workflow_dispatch: # Manual trigger
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pull_request:
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paths:
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- 'headroom/transforms/**'
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- 'headroom/evals/**'
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- 'headroom/compress.py'
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jobs:
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# Fast smoke test on PRs touching compression code (~$0.05, ~2 min)
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smoke-test:
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if: github.event_name == 'pull_request'
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runs-on: ubuntu-latest
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timeout-minutes: 30
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steps:
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- uses: actions/checkout@v6
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- uses: actions/setup-python@v6
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with:
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python-version: "3.11"
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- name: Cache pip
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uses: actions/cache@v5
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with:
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path: ~/.cache/pip
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key: ${{ runner.os }}-pip-eval-${{ hashFiles('pyproject.toml') }}
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restore-keys: ${{ runner.os }}-pip-eval-
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# `pip install -e .` invokes maturin (declared in pyproject.toml's
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# build-system) which calls cargo to compile the Rust extension.
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- name: Install Rust toolchain
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uses: dtolnay/rust-toolchain@1.96.0
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- name: Cache cargo registry + build
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uses: Swatinem/rust-cache@v2
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with:
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workspaces: ". -> target"
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- name: Install dependencies (builds Rust extension via maturin)
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run: |
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pip install -e ".[all]"
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python -c "from headroom._core import SmartCrusher; print('headroom._core OK:', SmartCrusher)"
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- name: Run CCR round-trip (zero cost)
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run: |
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python -c "
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from headroom.evals.runners.compression_only import CompressionOnlyRunner
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runner = CompressionOnlyRunner()
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cases = runner.generate_ccr_test_cases(n=50)
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result = runner.evaluate_ccr_lossless(cases)
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print(f'CCR Round-trip: {result.passed_cases}/{result.total_cases} passed')
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assert result.passed, f'CCR failures: {result.errors}'
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"
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- name: Run tool schema compaction integrity eval (zero cost)
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run: |
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python -c "
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from headroom.evals.runners.compression_only import CompressionOnlyRunner
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runner = CompressionOnlyRunner()
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result = runner.evaluate_tool_schema_compaction()
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print(f'Tool schema compaction: {result.passed_cases}/{result.total_cases} passed, {result.total_tokens_saved} annotation tokens stripped')
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assert result.passed, f'Schema compaction failures: {result.errors}'
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"
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# OPENAI_API_KEY is intentionally not set in the public OSS repo
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# (the secret list is empty). The CCR round-trip step above is the
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# mandatory gate; this step only runs when an operator has wired
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# OPENAI_API_KEY as a repo secret (e.g. on a downstream fork). When
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# missing, emit a loud GitHub `::warning::` annotation so the skip
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# is visible in the run summary — never a silent pass.
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- name: Run built-in tool output eval (skipped when OPENAI_API_KEY unset)
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env:
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OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
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run: |
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if [ -z "${OPENAI_API_KEY}" ]; then
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echo "::warning title=Smoke eval skipped::OPENAI_API_KEY is not configured for this repo; only the CCR round-trip gate ran. Wire the secret to enable the live OpenAI eval."
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exit 0
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fi
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python -m headroom.evals quick -n 8 --provider openai --model gpt-4o-mini
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# Full Tier 1 suite, weekly or manual (~$3-5, ~30-45 min)
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weekly-suite:
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if: github.event_name == 'schedule' || github.event_name == 'workflow_dispatch'
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runs-on: ubuntu-latest
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timeout-minutes: 90
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steps:
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- uses: actions/checkout@v6
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- uses: actions/setup-python@v6
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with:
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python-version: "3.11"
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- name: Cache pip
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uses: actions/cache@v5
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with:
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path: ~/.cache/pip
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key: ${{ runner.os }}-pip-eval-${{ hashFiles('pyproject.toml') }}
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restore-keys: ${{ runner.os }}-pip-eval-
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- name: Install Rust toolchain
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uses: dtolnay/rust-toolchain@1.96.0
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- name: Cache cargo registry + build
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uses: Swatinem/rust-cache@v2
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with:
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workspaces: ". -> target"
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- name: Install dependencies (builds Rust extension via maturin)
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run: |
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pip install -e ".[all]"
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python -c "from headroom._core import SmartCrusher; print('headroom._core OK')"
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- name: Run Tier 1 evaluation suite
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run: |
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if [ -z "${OPENAI_API_KEY}" ]; then
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echo "::warning title=Weekly eval skipped::OPENAI_API_KEY is not configured for this repo; skipping the live Tier 1 suite."
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mkdir -p eval_results
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printf '%s\n\n%s\n' \
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'# Weekly Evaluation Skipped' \
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'OPENAI_API_KEY is not configured for this repository, so the live Tier 1 evaluation suite was skipped.' \
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> eval_results/skipped.md
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exit 0
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fi
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python -m headroom.evals suite --tier 1 --ci -o eval_results/
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env:
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OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
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ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
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# Recall-based fidelity report on the production routing path. Zero cost
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# (synthetic structured cases -> Rust compressors; no model, no API, no
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# secrets). Non-blocking: surfaces recall trends weekly without gating.
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# The blocking per-PR fidelity gate lives in
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# tests/test_compression_fidelity_regression.py (runs in the [dev] shard).
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- name: Information-retention recall report (zero cost, non-blocking)
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run: |
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python -c "
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from headroom.evals.runners.compression_only import CompressionOnlyRunner
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runner = CompressionOnlyRunner()
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cases = runner.generate_info_retention_cases(n=50)
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result = runner.evaluate_information_retention(cases)
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print(f'Information retention: {result.passed_cases}/{result.total_cases} cases >=0.9 recall, avg compression {result.avg_compression_ratio:.1%}')
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if not result.passed:
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print(f'::warning title=Fidelity recall::{result.failed_cases} case(s) fell below 0.9 recall: {result.errors[:3]}')
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"
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- name: Upload results
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if: always()
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uses: actions/upload-artifact@v7
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with:
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name: eval-results-${{ github.run_number }}
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path: eval_results/
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