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.
POST /api/admin/configure now writes a default ai: block into the
instance.yaml overlay when the request leaves it untouched and either
ANTHROPIC_API_KEY or LLM_API_KEY is set in the environment. The block
references the env var via ${VAR} syntax — secrets never land in YAML.
connectors.llm.factory grows create_extractor_from_env_or_config which
falls back to ANTHROPIC_API_KEY / LLM_API_KEY when ai_config is empty
and raises a clear ValueError when neither is available. Both
services/corporate_memory and services/verification_detector switch to
the new helper, replacing the old 'silently skip when ai: missing'
path that was the silent-failure root cause.
Tests:
- tests/test_setup_ai_block.py — overlay seeding contract.
- tests/test_llm_provider_env_fallback.py — fallback + fail-fast.
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.
