AI-Cognitive-Leap/agnes-the-ai-analyst
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7 commits

Author SHA1 Message Date
Petr
80c5b902e0 Add scheduled data sync and catalog refresh with systemd timers 
- New sync_schedule and profile_after_sync fields in TableConfig
  (formats: "every 15m", "every 1h", "daily 05:00")
- New src/scheduler.py with schedule evaluation logic (is_table_due)
- New --scheduled mode in data_sync.py: only syncs tables that are due,
  respects profile_after_sync flag, auto-restarts webapp after profiling
- Systemd timer+service for data-refresh (every 15 min)
- Systemd timer+service for catalog-refresh (every 15 min)
- deploy.sh enables new timers automatically
- Complete table config reference in data_description.md.example
- 58 new scheduler tests
 2026-03-15 02:16:31 +01:00
Petr
c5c24cb45b Implement OpenMetadata catalog integration (Phase 1) 
Add OpenMetadata REST API connector and enricher to merge table/column metadata
from OpenMetadata catalog at sync and query time.

Changes:
- connectors/openmetadata/client.py: HTTP client for OM API
- connectors/openmetadata/enricher.py: Data enrichment with TTL cache
- tests/test_openmetadata_*: Unit tests for client and enricher
- src/config.py: Add catalog_fqn field to TableConfig
- src/data_sync.py: Use enricher in _generate_schema_yaml (catalog > BQ API > data_description.md)
- webapp/app.py: Initialize enricher, enrich catalog data with tags/tier/owners/url
- config/instance.yaml.example: Document openmetadata section

Features:
- FQN auto-derivation: bigquery.{table.id}
- TTL cache (default 1h) to avoid repeated API calls
- Graceful degradation: disabled if token missing, silent on HTTP errors
- Column description priority: catalog > BQ API > (none)
- Table description priority: catalog > data_description.md
 2026-03-12 14:07:13 +01:00
Petr
8bb46a9e0a Add per-partition streaming sync and hybrid query architecture 
Partitioned sync: iterates day-by-day instead of loading full dataset.
Each partition: query BQ -> stream to disk -> free RAM. Peak ~50 MB.
New helpers: _sync_single_partition, _cleanup_old_partitions, _generate_partition_dates.

Config: added partition_column_type (DATE/TIMESTAMP/DATETIME), query_mode (local/remote/hybrid).
DuckDB manager: hybrid architecture support (local Parquet + remote BQ tables).
Data sync: skips remote tables, filters by query_mode.

Tests: 113 passing (adapter, client, config, data_sync, duckdb_manager).
 2026-03-12 13:20:41 +01:00
Petr
758910463b Add BigQuery data source adapter 
BigQuery connector that syncs BQ tables to local Parquet files via PyArrow
(no CSV intermediate step). Supports full refresh, timestamp-based
incremental (via incremental_column), and partition-based sync strategies.

- connectors/bigquery/client.py: BQ API wrapper with ADC auth, parameterized
  queries, metadata cache, cross-project support (job project != data project)
- connectors/bigquery/adapter.py: DataSource implementation with merge/dedup
- src/config.py: Add incremental_column field to TableConfig
- 72 unit tests (mocked, no GCP SDK required)
 2026-03-11 13:56:12 +01:00
Petr
b99ec576ca Add self-service data onboarding system 
Table Registry as central source of truth (JSON) with atomic writes,
optimistic locking, audit logging, and data_description.md generation.
Existing readers (config.py, profiler.py) need zero changes.

Phase 1 - Discovery API:
  - discover_tables() on DataSource ABC + Keboola implementation
  - admin_required decorator with server-side recomputation
  - GET /api/admin/discover-tables endpoint

Phase 2 - Table Registry:
  - src/table_registry.py with CRUD, validation, migration from MD
  - Admin API: register/update/unregister with version locking
  - DELETE cascade cleans up per-user subscriptions

Phase 3 - Auto-Profiling:
  - profile_changed_tables() for incremental profiling
  - Non-fatal hook in sync_all() after successful sync

Phase 4 - Per-Table Subscriptions:
  - table_mode (all/explicit) with per-table toggles
  - GET/POST /api/table-subscriptions endpoints
  - Subscription status in catalog and dashboard views

Phase 5 - Smart Sync:
  - Python-generated rsync filter files (not shell YAML parsing)
  - sync_data.sh uses --filter="merge ..." for explicit mode

Phase 6 - Admin UI:
  - /admin/tables with discovery, registration modal, registry mgmt
  - Vanilla JS, matching existing design system
 2026-03-09 14:25:37 +01:00
Petr
266e8573d3 Extract Keboola into connectors/keboola module 
Move all Keboola-specific code out of src/ into connectors/keboola/:
- git mv src/keboola_client.py -> connectors/keboola/client.py
- Extract LocalKeboolaSource (855 lines) from data_sync.py -> connectors/keboola/adapter.py
- Rename to KeboolaDataSource with full env var validation
- Extend DataSource ABC with get_column_metadata() and get_source_name()
- Add dynamic connector registry via importlib in create_data_source()
- Refactor _generate_schema_yaml to use ABC methods (source_type, _schema_version: 2)
- Remove src/adapters/ (redundant facade layer)
- Remove Keboola validation from src/config.py (connector validates itself)
- Add 14 tests for factory, ABC defaults, env validation, dynamic lookup
 2026-03-09 12:22:16 +01:00
Petr
c56905d34f Initial commit: OSS data distribution platform 
Open-source AI data analyst platform extracted from internal repo.
Includes data sync engine, Keboola adapter, Flask web portal,
server deployment scripts, and configuration templates.
 2026-03-08 23:31:28 +01:00