New src/rbac.py: Role enum, hierarchy, get_user_role(), has_role(),
is_admin(), is_km_admin(), has_dataset_access(), set_user_role().
webapp/auth.py: admin_required + km_admin_required now use DuckDB
roles instead of Linux groups (pwd.getpwnam + sudo/data-ops check).
app/auth/dependencies.py: imports Role from src/rbac.py (single source).
11 RBAC tests passing.
Update project structure, architecture diagram, key implementation
details, development commands, and extensibility docs.
Add extract service to docker-compose.yml for one-shot extraction.
migrate_registry_to_duckdb.py: imports tables from data_description.md
or table_registry.json into DuckDB table_registry with source columns.
migrate_parquets_to_extracts.py: copies parquets to /data/extracts/
and creates extract.duckdb with _meta + views.
- New extract_init.py: creates extract.duckdb with _meta + views for 6 entity types
- Update default paths to /data/extracts/jira/data/ and /data/extracts/jira/raw/
- After parquet writes, update _meta table in extract.duckdb
- Trigger SyncOrchestrator.rebuild_source("jira") after successful transform
- POST /auth/bootstrap — creates first admin, self-deactivates after
- da setup bootstrap — CLI command for agent-driven setup
- da setup verify — structured health check (JSON output for agents)
- cli/skills/deploy.md — complete deployment guide for AI agents
- 6 bootstrap tests including full agent deployment flow simulation
- 156 total tests passing
- Google OAuth with authlib + auto user creation + cookie-based JWT
- Password auth with argon2 hash + setup token flow
- Email magic link with SMTP/SendGrid support
- Cookie-based auth for web UI (after OAuth redirect)
- Dashboard template compatibility (user_info, activity, desktop status)
- 150 tests passing
- SyncSettingsRepository + DatasetPermissionRepository with RBAC
- Script deploy/run/undeploy API with import sandboxing
- User sync settings API with permission checks
- 4 CLI skills (connectors, security, notifications, corporate-memory)
- Kamal production + staging configs
- GitHub Actions CI + deploy workflows
- 91 total tests passing
- Fix sync_state.json parsing: derive last_updated from table last_sync
timestamps when root-level field is missing (flat format support)
- Parse ALL YAML blocks from data_description.md (was only first block)
- Show remote tables (daily_deal_traffic) in catalog with "Live" badge
- Show per-table sync timestamps and Local/Live query mode badges
- Add data freshness note to Business Metrics section
- Dashboard: fix "Not yet synced" bug, show local/live table breakdown
Same issue as config.py - profiler's TableInfo and parser required
primary_key and sync_strategy, breaking auto-profile after sync
when daily_deal_traffic (remote-only) is in config.
Remote-only tables (query_mode="remote") like daily_deal_traffic
don't need primary_key or sync_strategy. The parser used hard
lookups (table_data["primary_key"]) causing KeyError and breaking
all data sync since 2026-03-21.
Changes:
- TableConfig: default primary_key="" and sync_strategy="none"
- Parser: use .get() with defaults instead of [] lookups
- Validator: add "none" as valid sync_strategy
Add admin curation layer between AI extraction and knowledge distribution.
Admins (km_admin flag in instance.yaml) can approve, reject, mandate, and
revoke knowledge items. Mandatory items distribute to all targeted users
automatically.
Three governance modes (configurable per instance):
- mandatory_only: admin controls everything, no user voting
- admin_curated: admin controls, users vote as feedback signal
- hybrid: mandatory from admin + optional from user voting
Three approval workflows:
- review_queue: nothing published without admin approval
- auto_publish: items go live immediately, admin intervenes retroactively
- threshold: confidence-based auto-publish (Phase 5)
Includes:
- 9 admin action functions (approve/reject/mandate/revoke/edit/batch/...)
- 11 new admin API endpoints under /api/corporate-memory/admin/
- Immutable audit log (audit.jsonl)
- Audience targeting via groups
- Automatic migration of existing items to "approved" status
- km_admin_required auth decorator
- 69 tests covering all governance logic
- Backward compatible: no config = legacy wiki behavior
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.
Session testing revealed 3 issues with remote queries:
1. CLAUDE.md template recommended `cat <<HEREDOC | ssh ...` but
claude_settings.json had `cat` in deny list, causing 2-3 failed
attempts per query. Replaced with file-based approach: Write tool
creates JSON file, then `ssh ... < file` avoids the cat deny.
2. ssh/scp commands were not in the allow list, requiring manual
approval for every remote query. Added both to allow list.
3. DuckDB fetch_arrow_table() emitted DeprecationWarning on every
parquet export. Replaced with .arrow().read_all().
Also added instruction for proactive hybrid analysis when remote
tables are available (agent was only using local data until asked).
Agent was failing 3x on SSH commands due to backticks (BQ table names)
and single quotes (SQL string literals) getting mangled by nested shell
interpretation (local -> SSH -> bash -> Python).
New --stdin mode reads query spec as JSON from stdin via heredoc:
cat <<'QUERY' | ssh alias 'bash remote_query.sh --stdin'
{"register_bq": {"alias": "SELECT ... FROM \`table\` ..."}, "sql": "..."}
QUERY
Heredoc with <<'QUERY' (quoted) passes everything literally -- no
escaping needed for backticks, quotes, or parentheses.
Updated claude_md_template.txt to use --stdin as the primary method.
Analysts don't have WEBAPP_SECRET_KEY, so load_instance_config()
validation failed with noisy warnings. Now reads instance.yaml
directly with yaml.safe_load, skipping secret validation.
GCP OS Login doesn't honor /etc/group changes for SSH sessions,
so analyst can't read /opt/data-analyst/.env even after usermod.
Wrapper now reads .remote_query.env from scripts dir (dataread group),
falls back to .env for admin users. The env file contains only
non-secret BQ config (project ID, location, data dir).
Analyst user (foundry_e_psimecek) couldn't access /opt/data-analyst/.
Added to data-ops group on server.
New scripts/remote_query.sh wrapper handles env setup (PYTHONPATH,
CONFIG_DIR, .env) so agents use simple:
ssh alias 'bash ~/server/scripts/remote_query.sh --sql "..." --format table'
Updated claude_md_template.txt to use wrapper instead of raw commands.
find_project_root() and parse_data_description() now check CONFIG_DIR
env var first when looking for data_description.md. On server deployment,
data_description.md lives in instance/config/ (CONFIG_DIR), not in the
OSS repo's docs/ directory.
