E2E test on a real BQ deploy showed every verification-extraction call
fails with HTTP 400 invalid_request_error: "output_config.format.schema:
For 'object' type, 'additionalProperties' must be explicitly set to false".
The Anthropic structured-output API now requires the field on every object
node in the json_schema. Fix: connectors/llm/anthropic_provider.py wraps
the caller-supplied schema through a recursive _strict_json_schema()
walker that adds the field where missing (preserving any explicit
override), then passes the strict variant to the API. Six unit tests in
TestStrictJsonSchema pin the recursion across nested objects, array items,
and the no-mutation invariant.
Adds /admin/scheduler-runs — a read-only admin page that surfaces the
last 200 audit-log entries from scheduler-driven actions. New
AuditRepository.query_actions(actions, limit) helper, new admin nav
entry. Failed scheduler ticks (HTTP 401, network errors) don't reach
the audit_log; the page calls that out with a hint to set
SCHEDULER_API_TOKEN if no rows show up.
The PR's #176 fail-fast change made collect_all() raise ValueError when
neither an ai: block nor ANTHROPIC_API_KEY/LLM_API_KEY was available.
verification_detector's CLI was updated to handle it; corporate_memory's
CLI was missed and crashed with an unhandled traceback.
services/corporate_memory/collector.py:main() now wraps the collect_all
call in try/except ValueError, prints a one-line actionable message
to stderr, and returns rc=1.
Regression test:
test_llm_connector.py::TestCorporateMemoryCollector::test_main_returns_1_on_no_ai_config_instead_of_traceback.
The PR rewrote collect_all() to call the new
create_extractor_from_env_or_config() helper, but the existing tests
still mocked the old direct create_extractor() symbol and the old
silent-skip-on-missing-config behavior. Five tests in
TestCorporateMemoryCollector and one in TestCollectorExtractorIntegration
were red on the PR branch.
Changes:
- Tests now mock connectors.llm.create_extractor_from_env_or_config
(the symbol the collector imports lazily).
- Renamed test_collect_all_no_ai_config_skips ->
test_collect_all_no_ai_config_or_env_raises and
test_collector_handles_invalid_config -> test_collector_raises_on_invalid_config.
Both assert pytest.raises(ValueError) — the explicit fail-fast
semantics defect 5 of #176 was supposed to enforce.
- collect_all() no longer swallows the factory's ValueError into
stats["errors"]; it propagates so the scheduler / admin endpoint
surface the actionable misconfiguration message instead of
pretending the run was a no-op.
- /api/admin/run-corporate-memory translates the propagated ValueError
into a 500 with the factory's message, matching
/api/admin/run-verification-detector.
Replace hardwired Anthropic API calls with a pluggable provider system.
Each deployment configures its AI provider in instance.yaml — switching
between Anthropic, LiteLLM, OpenRouter, or any OpenAI-compatible proxy
is a config change, not a code change.
New connectors/llm/ module:
- StructuredExtractor Protocol with extract_json() interface
- AnthropicExtractor: direct Anthropic SDK with retry + backoff
- OpenAICompatExtractor: any OpenAI-compatible proxy with three-layer
structured output fallback (json_schema -> json_object -> prompt)
- Configurable structured_output policy (strict/json/auto)
- Custom exception hierarchy (auth/rate_limit/timeout/format/refusal)
- Zero secrets in logs: no API keys, prompts, or responses logged
Reviewed by: Google Gemini, Claude Sonnet, OpenAI GPT-5.4.
Security audit passed with all critical findings resolved.
