mirror of
https://github.com/headroomlabs-ai/headroom.git
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## Description Adds `headroom.testing`, a fluent, contractual test harness for building Headroom scenarios and suites that can be simulated locally, orchestrated, deployed through the proxy, and handed off to `headroom-bench` / `agent-evals` with bench-native manifests. Closes # ## Type of Change - [x] 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) - [x] Documentation update - [ ] Performance improvement - [ ] Code refactoring (no functional changes) ## Changes Made - Add `headroom.testing.Headroom` fluent scenario builder with provider/platform/configuration facets such as `WithBedrock`, `OnAppleSilicon`, `Configure`, `WithCompression`, `WithCCR`, `WithCache`, `WithPrefixFreeze`, `WithReadMaturation`, and `WithMemory`. - Add contractual coverage over the current `HeadroomConfig` and `ProxyConfig` dataclass surfaces, including full JSON-ready proxy deployment payloads. - Add no-key local simulations, scenario/suite orchestration, guarantee evaluation, deployment plans, and a local proxy lifecycle context manager. - Add `headroom-bench` handoff artifacts, including `agent_evals.models.RunManifest`-compatible JSON without taking a runtime dependency on `agent-evals`. - Add demonstration tests for providers, feature facets, manifests, suites, guarantees, deployment payloads, and the no-key simulation path. - Fix unversioned OTEL meter lookup typing so `mypy headroom` remains green on current `main`. ## 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 python -m ruff check . All checks passed! python -m mypy headroom headroom\proxy\server.py:1680: note: By default the bodies of untyped functions are not checked, consider using --check-untyped-defs [annotation-unchecked] headroom\proxy\server.py:1691: note: By default the bodies of untyped functions are not checked, consider using --check-untyped-defs [annotation-unchecked] Success: no issues found in 512 source files python -m pytest tests/test_cli/test_subprocess_utf8_encoding.py tests/test_testing_harness.py -q 24 passed, 1 warning in 4.68s ``` ## Real Behavior Proof - Environment: Windows, Python 3.13.13, branch `feat/headroom-test-harness` rebased on `headroomlabs-ai/main`. - Exact command / steps: built a `Headroom.WithOpenAI().WithCompression(mode="cache", kompress=False).Build()` scenario and entered `scenario.deploy_local(port=19192, timeout_s=20)`. - Observed result: proxy launched, `/readyz` succeeded, handle returned `http://127.0.0.1:19192`, `OPENAI_BASE_URL=http://127.0.0.1:19192/v1`, and context-manager teardown completed. - Exact command / steps: emitted `scenario.agent_evals_manifest(...).to_dict()` and validated it with the current cloned `headroom-bench` `agent_evals.models.RunManifest` pydantic model. - Observed result: validation succeeded with arms `a0_direct`, `a1_passthrough`, and `b_headroom` for provider `openai`. - Not tested: upstream-provider API calls requiring real OpenAI/Anthropic/Bedrock keys; phase-1 validation intentionally stays no-key/local. ## 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 - [x] I did **not** edit `CHANGELOG.md` — it is generated by release-please from my Conventional Commit PR title (a CI guard enforces this) ## Screenshots (if applicable) N/A. ## Additional Notes The pytest warning shown above is the existing OpenAI pricing-data staleness warning from cost estimation. The harness does not call upstream providers during local simulation.
459 lines
17 KiB
Python
459 lines
17 KiB
Python
from __future__ import annotations
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import json
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from datetime import datetime, timezone
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from pathlib import Path
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import pytest
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from headroom.config import HeadroomConfig
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from headroom.proxy.models import ProxyConfig
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from headroom.testing import (
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AgentEvalsPricing,
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ArmName,
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Configurator,
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GuaranteeResult,
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Headroom,
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ProviderTarget,
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ScenarioOrchestrator,
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ScenarioTask,
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)
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AGENT_EVALS_RUN_MANIFEST_FIELDS = {
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"experiment_id",
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"created_at",
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"headroom_git_sha",
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"agent_evals_git_sha",
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"model_snapshot",
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"provider",
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"auth_mode",
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"benchmark",
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"benchmark_ref",
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"harness",
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"harness_version",
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"docker_digests",
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"arms",
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"k_runs",
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"temperature",
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"seeds",
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"alpha",
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"margins",
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"pricing",
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}
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def _configure_bedrock_apple(c: Configurator) -> None:
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c.kompress_enabled = False
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c.mode = "cache"
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c.default_mode = "optimize"
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def test_contract_covers_current_headroom_and_proxy_config_fields() -> None:
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scenario = Headroom.scenario("contract").build()
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assert scenario.contract.field_names("headroom") == set(HeadroomConfig.__dataclass_fields__)
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assert scenario.contract.field_names("proxy") == set(ProxyConfig.__dataclass_fields__)
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def test_fluent_builder_configures_real_proxy_and_sdk_configs() -> None:
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scenario = (
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Headroom.WithBedrock(region="us-east-1", profile="bench")
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.named("bedrock-apple")
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.OnAppleSilicon()
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.configure(_configure_bedrock_apple)
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.configure_proxy(savings_profile="coding", min_tokens_to_crush=10)
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.build()
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)
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assert scenario.provider is ProviderTarget.BEDROCK
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assert scenario.proxy_config.backend == "bedrock"
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assert scenario.proxy_config.bedrock_region == "us-east-1"
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assert scenario.proxy_config.bedrock_profile == "bench"
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assert scenario.proxy_config.disable_kompress is True
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assert scenario.proxy_config.mode == "cache"
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assert scenario.headroom_config.default_mode.value == "optimize"
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command = scenario.proxy_command(port=18800)
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assert command[:4] == ("headroom", "proxy", "--port", "18800")
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assert "--backend" in command
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assert "bedrock" in command
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assert "--disable-kompress" in command
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assert "--savings-profile" not in command
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env = scenario.env()
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assert env["HEADROOM_BACKEND"] == "bedrock"
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assert env["HEADROOM_DISABLE_KOMPRESS"] == "1"
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assert env["HEADROOM_BEDROCK_REGION"] == "us-east-1"
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assert env["AWS_PROFILE"] == "bench"
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def test_unknown_config_field_fails_fast() -> None:
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with pytest.raises(AttributeError, match="unknown Headroom harness config field"):
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Headroom.scenario().configure(not_a_real_knob=True)
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def test_bench_manifest_fragment_matches_headroom_bench_arm_shape() -> None:
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scenario = (
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Headroom.with_openai()
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.configure(mode="cache", kompress_enabled=False)
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.configure_proxy(savings_profile="coding")
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.build()
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)
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fragment = scenario.bench_manifest_fragment(provider="openai").to_dict()
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assert fragment["harness"] == "headroom.testing"
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assert [arm["name"] for arm in fragment["arms"]] == [
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ArmName.A0_DIRECT.value,
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ArmName.A1_PASSTHROUGH.value,
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ArmName.B_HEADROOM.value,
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]
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assert fragment["arms"][0]["proxy_mode"] is None
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assert fragment["arms"][1]["proxy_mode"] == "off"
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assert fragment["arms"][2]["proxy_mode"] == "cache"
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assert fragment["arms"][2]["proxy_flags"] == ["--disable-kompress"]
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assert fragment["env"]["HEADROOM_MODE"] == "cache"
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assert fragment["env"]["HEADROOM_SAVINGS_PROFILE"] == "coding"
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assert fragment["deployment_plan"]["config_env_var"] == "HEADROOM_PROXY_CONFIG_JSON"
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assert fragment["contract_audit"]["passed"] is True
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json.dumps(fragment)
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def test_agent_evals_manifest_matches_run_manifest_contract() -> None:
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now = datetime(2026, 6, 15, 9, 30, tzinfo=timezone.utc)
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scenario = (
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Headroom.with_openai()
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.named("openai-cache")
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.WithCompression(mode="cache", kompress=False)
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.Build()
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)
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manifest = scenario.agent_evals_manifest(
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benchmark="mini_swebench",
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benchmark_ref="mini@abc123",
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provider="openai",
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now=now,
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model_snapshot="openai/gpt-4o",
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headroom_repo_path="/nonexistent-headroom",
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agent_evals_repo_path="/nonexistent-agent-evals",
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k_runs=3,
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pricing=AgentEvalsPricing(input_usd_per_1m=2.5, output_usd_per_1m=10.0),
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)
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payload = manifest.to_dict()
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assert set(payload) == AGENT_EVALS_RUN_MANIFEST_FIELDS
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assert payload["experiment_id"] == "mini_swebench-openai-cache-20260615T093000Z"
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assert payload["created_at"] == "2026-06-15T09:30:00+00:00"
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assert payload["headroom_git_sha"] == "unknown"
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assert payload["agent_evals_git_sha"] == "unknown"
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assert payload["provider"] == "openai"
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assert payload["benchmark"] == "mini_swebench"
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assert payload["benchmark_ref"] == "mini@abc123"
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assert payload["harness"] == "headroom.testing"
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assert payload["model_snapshot"] == "openai/gpt-4o"
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assert payload["seeds"] == [0, 1, 2]
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assert payload["margins"] == {"ccr": 0.0, "lossy": 2.0}
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assert payload["pricing"] == {"input_usd_per_1m": 2.5, "output_usd_per_1m": 10.0}
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assert [arm["name"] for arm in payload["arms"]] == [
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"a0_direct",
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"a1_passthrough",
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"b_headroom",
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]
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assert payload["arms"][2]["proxy_mode"] == "cache"
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assert payload["arms"][2]["proxy_flags"] == ["--disable-kompress"]
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json.dumps(payload)
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def test_sdk_simulation_runs_without_provider_api_keys() -> None:
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scenario = Headroom.with_openai().configure(default_mode="optimize").build()
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messages = [
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{"role": "system", "content": "You are concise."},
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{"role": "user", "content": "Summarize this small payload."},
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]
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result = scenario.simulate(messages, model="gpt-4o")
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assert result.tokens_before >= result.tokens_after
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assert result.tokens_saved >= 0
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assert result.messages
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def test_deployment_plan_carries_full_proxy_config_payload_through_env() -> None:
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scenario = (
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Headroom.WithBedrock(region="us-east-2", profile="bench")
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.Configure(mode="cache", kompress_enabled=False)
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.ConfigureProxy(memory_enabled=True, memory_top_k=3, offline=True)
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.Build()
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)
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plan = scenario.deployment_plan(port=18888)
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payload_from_env = json.loads(plan.env["HEADROOM_PROXY_CONFIG_JSON"])
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assert plan.command[:4] == ("headroom", "proxy", "--port", "18888")
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assert payload_from_env == plan.config_payload
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assert plan.env["HEADROOM_SKIP_UPSTREAM_CHECK"] == "1"
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assert plan.config_payload["backend"] == "bedrock"
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assert plan.config_payload["memory_enabled"] is True
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assert plan.config_payload["memory_top_k"] == 3
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assert plan.config_payload["offline"] is True
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assert set(plan.config_payload) == set(ProxyConfig.__dataclass_fields__)
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def test_contract_audit_reports_full_payload_coverage_and_proxy_only_notes() -> None:
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scenario = (
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Headroom.WithBedrock(region="us-east-1")
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.WithReadMaturation(enabled=True, quiesce_turns=2)
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.Build()
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)
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audit = scenario.audit_contract()
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assert audit.passed is True
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assert audit.missing_headroom_payload_fields == ()
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assert audit.missing_proxy_payload_fields == ()
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assert audit.extra_headroom_payload_fields == ()
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assert audit.extra_proxy_payload_fields == ()
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assert audit.headroom_fields_total == len(HeadroomConfig.__dataclass_fields__)
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assert audit.proxy_fields_total == len(ProxyConfig.__dataclass_fields__)
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assert "read_maturation is currently a proxy-only surface" in audit.notes
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json.dumps(audit.to_dict())
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def test_write_manifest_fragment_outputs_json_file(tmp_path: Path) -> None:
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path = tmp_path / "headroom-manifest-fragment.json"
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scenario = (
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Headroom.WithOpenAI(api_url="https://openai.internal")
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.WithCompression(mode="cache", kompress=False)
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.Build()
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)
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written = scenario.write_manifest_fragment(path, provider="openai")
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payload = json.loads(written.read_text(encoding="utf-8"))
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assert written == path
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assert payload["harness"] == "headroom.testing"
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assert payload["provider"] == "openai"
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assert (
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payload["deployment_plan"]["config_payload"]["openai_api_url"] == "https://openai.internal"
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)
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assert payload["contract_audit"]["passed"] is True
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def test_feature_facets_configure_authoritative_scenario_surfaces() -> None:
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scenario = (
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Headroom.WithAnthropic(api_url="https://anthropic.internal")
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.named("enterprise-feature-matrix")
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.WithCompression(
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mode="cache",
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kompress=False,
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lossless=True,
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compressors=["smart_crusher", "log", "diff"],
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min_tokens=25,
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max_items=9,
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savings_profile="coding",
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)
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.WithCCR(
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enabled=True,
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inject_tool=False,
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inject_marker=True,
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handle_responses=True,
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proactive_expansion=False,
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max_retrieval_rounds=1,
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)
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.WithCache(enabled=True, semantic=True, ttl_seconds=120, max_entries=33)
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.WithPrefixFreeze(enabled=False, session_ttl_seconds=42)
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.WithReadMaturation(enabled=True, quiesce_turns=2, max_hold_turns=8, min_size_bytes=512)
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.WithMemory(
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enabled=True,
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backend="local",
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mode="tool",
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top_k=4,
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min_similarity=0.5,
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inject_tools=False,
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inject_context=False,
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storage_mode="project",
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)
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.Build()
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)
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assert scenario.proxy_config.anthropic_api_url == "https://anthropic.internal"
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assert scenario.proxy_config.disable_kompress is True
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assert scenario.proxy_config.lossless is True
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assert scenario.proxy_config.compressors == {"smart_crusher", "log", "diff"}
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assert scenario.proxy_config.min_tokens_to_crush == 25
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assert scenario.proxy_config.max_items_after_crush == 9
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assert scenario.headroom_config.smart_crusher.lossless_only is True
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assert scenario.headroom_config.smart_crusher.min_tokens_to_crush == 25
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assert scenario.headroom_config.smart_crusher.max_items_after_crush == 9
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assert scenario.proxy_config.ccr_inject_tool is False
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assert scenario.proxy_config.ccr_inject_marker is True
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assert scenario.proxy_config.ccr_proactive_expansion is False
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assert scenario.proxy_config.ccr_max_retrieval_rounds == 1
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assert scenario.headroom_config.ccr.enabled is True
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assert scenario.headroom_config.ccr.inject_tool is False
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assert scenario.headroom_config.ccr.inject_retrieval_marker is True
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assert scenario.proxy_config.cache_ttl_seconds == 120
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assert scenario.proxy_config.cache_max_entries == 33
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assert scenario.headroom_config.cache_optimizer.enable_semantic_cache is True
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assert scenario.proxy_config.prefix_freeze_enabled is False
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assert scenario.headroom_config.prefix_freeze.enabled is False
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assert scenario.proxy_config.read_maturation is True
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assert scenario.metadata["read_maturation"]["quiesce_turns"] == 2
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assert scenario.proxy_config.memory_enabled is True
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assert scenario.proxy_config.memory_mode == "tool"
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assert scenario.proxy_config.memory_top_k == 4
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assert scenario.proxy_config.memory_min_similarity == 0.5
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assert scenario.proxy_config.memory_inject_tools is False
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assert scenario.proxy_config.memory_inject_context is False
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payload = scenario.deployment_plan(port=18889).config_payload
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assert payload["compressors"] == ["diff", "log", "smart_crusher"]
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assert payload["read_maturation"] is True
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assert payload["memory_mode"] == "tool"
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@pytest.mark.parametrize(
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("builder", "expected_provider", "expected_backend"),
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[
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(
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lambda: Headroom.WithAnthropic(api_url="https://anthropic.internal"),
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"anthropic",
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"anthropic",
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),
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(lambda: Headroom.WithOpenAI(api_url="https://openai.internal"), "openai", "anthropic"),
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(lambda: Headroom.WithGemini(api_url="https://gemini.internal"), "gemini", "anthropic"),
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(
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lambda: Headroom.WithCloudCode(api_url="https://cloudcode.internal"),
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"cloudcode",
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"anthropic",
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),
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(
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lambda: Headroom.WithVertex(api_url="https://vertex.internal"),
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"vertex",
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"litellm-vertex",
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),
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(lambda: Headroom.WithBedrock(region="us-east-1"), "bedrock", "bedrock"),
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(lambda: Headroom.WithAnyLLM(provider="mistral"), "anyllm", "anyllm"),
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(lambda: Headroom.WithLiteLLM(provider="openrouter"), "litellm", "litellm-openrouter"),
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],
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)
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def test_provider_builders_cover_current_proxy_targets(
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builder: object,
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expected_provider: str,
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expected_backend: str,
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) -> None:
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scenario = builder().WithCompression(mode="cache").Build() # type: ignore[operator]
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plan = scenario.deployment_plan(port=18901)
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assert scenario.provider.value == expected_provider
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assert plan.config_payload["backend"] == expected_backend
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assert plan.command[:4] == ("headroom", "proxy", "--port", "18901")
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assert json.loads(plan.env["HEADROOM_PROXY_CONFIG_JSON"]) == plan.config_payload
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def test_scenario_orchestrator_runs_multiple_scenarios_and_reports_guarantees() -> None:
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passthrough = (
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Headroom.with_openai()
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.named("passthrough")
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.Configure(optimize=False, default_mode="audit")
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.Build()
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)
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optimized = (
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Headroom.with_openai()
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.named("optimized")
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.Configure(mode="cache", default_mode="optimize")
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.Build()
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)
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task = ScenarioTask(
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task_id="tiny-chat",
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messages=[
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{"role": "system", "content": "You are concise."},
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{"role": "user", "content": "Summarize this small payload."},
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],
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model="gpt-4o",
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)
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report = ScenarioOrchestrator([passthrough, optimized]).run([task])
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assert report.passed is True
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assert len(report.cases) == 2
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assert report.total_tokens_before >= report.total_tokens_after
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payload = report.to_dict()
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assert payload["total_cases"] == 2
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assert payload["cases"][0]["guarantees"]
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def test_orchestrator_surfaces_custom_guarantee_failures() -> None:
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scenario = Headroom.with_openai().named("guarded").Build()
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task = ScenarioTask(
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task_id="expected-failure",
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messages=[{"role": "user", "content": "hello"}],
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)
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def always_fail(*_args: object) -> GuaranteeResult:
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return GuaranteeResult(name="always_fail", passed=False, detail="demonstration failure")
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report = ScenarioOrchestrator([scenario], guarantees=[always_fail]).run([task])
|
|
|
|
assert report.passed is False
|
|
assert report.cases[0].passed is False
|
|
assert report.to_dict()["cases"][0]["guarantees"] == [
|
|
{"name": "always_fail", "passed": False, "detail": "demonstration failure"}
|
|
]
|
|
|
|
|
|
def test_headroom_suite_orchestrates_matrix_and_assigns_deployment_ports(tmp_path: Path) -> None:
|
|
suite = (
|
|
Headroom.Suite("phase-1-matrix")
|
|
.Add(Headroom.WithOpenAI().named("openai-cache").WithCompression(mode="cache"))
|
|
.Add(
|
|
Headroom.WithBedrock(region="us-east-1")
|
|
.named("bedrock-token")
|
|
.WithCompression(mode="token")
|
|
)
|
|
)
|
|
task = ScenarioTask(
|
|
task_id="suite-smoke",
|
|
messages=[{"role": "user", "content": "hello"}],
|
|
)
|
|
|
|
report = suite.Orchestrate([task])
|
|
plans = suite.DeploymentPlans(port_start=19000)
|
|
bundle = suite.ManifestBundle(provider="openai", port_start=19000).to_dict()
|
|
path = suite.WriteManifestBundle(tmp_path / "suite.json", provider="openai", port_start=19000)
|
|
agent_paths = suite.WriteAgentEvalsManifests(
|
|
tmp_path / "agent-evals",
|
|
benchmark="mini_swebench",
|
|
benchmark_ref="mini@abc123",
|
|
provider="openai",
|
|
now=datetime(2026, 6, 15, 9, 30, tzinfo=timezone.utc),
|
|
)
|
|
written = json.loads(path.read_text(encoding="utf-8"))
|
|
|
|
assert report.passed is True
|
|
assert len(report.cases) == 2
|
|
assert set(plans) == {"openai-cache", "bedrock-token"}
|
|
assert plans["openai-cache"].command[:4] == ("headroom", "proxy", "--port", "19000")
|
|
assert plans["bedrock-token"].command[:4] == ("headroom", "proxy", "--port", "19001")
|
|
assert bundle["name"] == "phase-1-matrix"
|
|
assert [scenario["suite_port"] for scenario in bundle["scenarios"]] == [19000, 19001]
|
|
assert written == bundle
|
|
assert {path.name for path in agent_paths} == {
|
|
"openai-cache.agent-evals.json",
|
|
"bedrock-token.agent-evals.json",
|
|
}
|
|
first_agent_payload = json.loads(agent_paths[0].read_text(encoding="utf-8"))
|
|
assert set(first_agent_payload) == AGENT_EVALS_RUN_MANIFEST_FIELDS
|
|
assert first_agent_payload["provider"] == "openai"
|
|
|
|
|
|
def test_headroom_suite_rejects_duplicate_scenario_names() -> None:
|
|
suite = Headroom.Suite("duplicates").Add(Headroom.WithOpenAI().named("same"))
|
|
|
|
with pytest.raises(ValueError, match="duplicate scenario name"):
|
|
suite.Add(Headroom.WithBedrock(region="us-east-1").named("same"))
|
|
|
|
|
|
def test_empty_suite_fails_loudly() -> None:
|
|
with pytest.raises(ValueError, match="requires at least one scenario"):
|
|
Headroom.Suite("empty").DeploymentPlans()
|