Commit graph

5 commits

Author SHA1 Message Date
Petr
95358448e6 Add modular LLM connector for Corporate Memory
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.
2026-03-23 12:08:33 +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
44bf43535b Add sample data generator with 9 e-commerce tables
Synthetic data generator for demo/testing without real data adapter:
- 9 tables: customers, products, campaigns, web_sessions, web_leads,
  orders, order_items, payments, support_tickets
- 4 size presets: xs (1MB), s (15MB), m (150MB), l (1.5GB)
- Realistic patterns: seasonality, Pareto customer distribution,
  segment-based behavior, referential integrity
- Deterministic output via --seed parameter

Also: docs/sample-data.md, updated auto-install.md with Step 6,
updated CLAUDE.md (email auth provider, dual-repo architecture)
2026-03-10 12:31:14 +01:00
Petr
26c4e0934d OSS cleanup: remove internal references, harden deployment, add config env interpolation
Phase 1 - Internal reference cleanup:
- Delete dev_docs/meetings/ (internal meeting notes/transcripts)
- Replace hardcoded usernames (padak/matejkys/dasa) with deploy/generic
- Replace "Internal AI Data Analyst" with "AI Data Analyst"
- Replace keboola/internal_ai_data_analyst URLs with your-org/ai-data-analyst
- Replace /tmp/keboola_load/ with /tmp/data_analyst_staging/ in dev_docs

Phase 2 - Deployment hardening:
- Tighten sudoers wildcards to explicit paths (visudo, sudoers cp)
- setup.sh creates all groups (data-ops, dataread, data-private) and deploy user
- webapp-setup.sh copies sudoers-webapp from repo instead of inline definition
- deploy.sh conditional copy for data_description.md (not in git for OSS)
- deploy.sh ownership changed to deploy:data-ops for /data/{scripts,docs,examples}

Phase 3 - Config and misc:
- Add ${ENV_VAR} interpolation to config/loader.py
- Expand config/instance.yaml.example with all sections (admins, deployment, auth, etc.)
- Create config/.env.template for secret values
- Add MIT LICENSE
- Fix .gitignore: add .venv/, docs/data_description.md
- Fix README.md: CSV status Planned, remove metrics/, update license text
- Translate Czech comments in requirements.txt to English
- Fix test_account_service.py: mock username mapping instead of relying on instance config

All 118 tests pass.
2026-03-09 07:59:57 +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