AFFAANhandClaude Opus 5
11a42e7afa
The moment a real MASKANX_OPERATOR_TOKENS got set in Settings >
Environments (this session, for the first time on this machine), 28 tests
in test_campaign_launch.py started failing with 401 instead of the status
each was actually testing.
Cause: adclaw/__init__.py calls load_envs_into_environ() at import time,
so envs.json — the exact file the Settings UI writes — becomes ambient
environment for every test process, not only the ones that opt in.
Most campaign tests deliberately exercise the unauthenticated path and
never send an operator header; once a real token map exists,
require_operator starts demanding one they don't send.
This was already named as a deferred minor in the Phase 2 ledger
("test_campaign_api client fixture does not delenv MASKANX_OPERATOR_TOKENS")
but scoped to one file. It affects nine. An autouse fixture in
tests/conftest.py clears it before every test; a test that wants a token
still gets one, since its own monkeypatch.setenv runs after and overrides
it. Confirmed narrowly scoped: adding only this one delenv brought the
suite from 28 failed back to 1212 passed with nothing left over — no need
to guess at a wider blast radius.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
95 lines
3.4 KiB
Python
95 lines
3.4 KiB
Python
# -*- coding: utf-8 -*-
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"""Shared fixtures for AOM tests."""
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import pytest
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@pytest.fixture(autouse=True)
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def _no_ambient_operator_tokens(monkeypatch):
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"""Never let a developer's real envs.json reach a test process.
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`adclaw/__init__.py` calls `load_envs_into_environ()` at import time, so
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whatever is saved in Settings > Environments on this machine becomes
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ambient environment for every test in the suite — not just the ones
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that opted in. Most campaign tests deliberately exercise the
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*unauthenticated* path (MASKANX_OPERATOR_TOKENS unset), so once a real
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operator token is configured for actual use, require_operator starts
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demanding a header those tests never send, and they fail with 401
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instead of the status the test is actually about. 28 tests broke this
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way the first time a real token was set.
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A test that wants a token still gets one: its own monkeypatch.setenv
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runs after this fixture in the same test and overrides it.
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"""
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monkeypatch.delenv("MASKANX_OPERATOR_TOKENS", raising=False)
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from adclaw.memory_agent.embeddings import FakeEmbeddingPipeline
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from adclaw.memory_agent.models import AOMConfig
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from adclaw.memory_agent.store import MemoryStore
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from adclaw.config.config import PersonaConfig, Config, AgentsConfig
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@pytest.fixture
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async def aom_store():
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"""In-memory SQLite store — zero I/O."""
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store = MemoryStore(":memory:", dimensions=32)
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await store.initialize()
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yield store
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await store.close()
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@pytest.fixture
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def fake_embedder():
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"""Deterministic embedding pipeline for tests."""
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return FakeEmbeddingPipeline(dimensions=32)
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@pytest.fixture
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def fake_llm_caller():
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"""Canned LLM: extraction → JSON, consolidation → insight text."""
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async def caller(prompt: str) -> str:
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if "extract" in prompt.lower():
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return '{"entities": ["test_entity"], "topics": ["test_topic"], "importance": 0.7}'
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if "consolidat" in prompt.lower() or "synthesiz" in prompt.lower() or "cluster" in prompt.lower():
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return "INSIGHT: Test insight about the data.\nIMPORTANCE: 0.8"
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if "memory" in prompt.lower() or "question" in prompt.lower():
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return "Based on the memories, the answer is test. [Memory #abc123]"
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return "Test response"
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return caller
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@pytest.fixture
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def aom_config():
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"""Default AOM configuration for tests."""
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return AOMConfig(
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enabled=True,
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embedding_backend="local",
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embedding_dimensions=32,
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importance_threshold=0.3,
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)
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@pytest.fixture
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def sample_personas():
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"""Three personas: coordinator + researcher + writer."""
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return [
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PersonaConfig(id="coordinator", name="Coordinator", is_coordinator=True, soul_md="## Role\nOrchestrate the team."),
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PersonaConfig(id="researcher", name="Mike", soul_md="## Role\nResearch and analyze."),
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PersonaConfig(id="content-writer", name="Mira", soul_md="## Role\nWrite content."),
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]
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@pytest.fixture
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def persona_manager(sample_personas, tmp_path):
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"""PersonaManager with 3 personas and temp working dir."""
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from adclaw.agents.persona_manager import PersonaManager
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mgr = PersonaManager(working_dir=str(tmp_path), personas=sample_personas)
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mgr.ensure_dirs()
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return mgr
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@pytest.fixture
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def config_with_personas(sample_personas):
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"""Config object with 3 personas."""
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return Config(agents=AgentsConfig(personas=sample_personas))
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