26c4e0934d
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.
93 lines
2.5 KiB
Text
93 lines
2.5 KiB
Text
# AI Data Analyst - Instance Configuration
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# ==========================================
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# This is the main configuration file for your instance.
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# Copy to instance.yaml and fill in your values.
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#
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# SECRET VALUES use ${ENV_VAR} syntax - actual values go in .env file.
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# Non-secret values are set directly here.
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# --- Instance branding ---
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instance:
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name: "AI Data Analyst"
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subtitle: "Your Organization"
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copyright: "Your Organization"
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# --- Server ---
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server:
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hostname: "" # DNS name (e.g., "data.acme.com")
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host: "" # IP address
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app_dir: "/opt/data-analyst" # Installation directory
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# --- Admin users ---
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# Manage the server, own data files, get unlimited resource limits.
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# SSH keys are used by server/setup.sh during provisioning.
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admins:
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- username: "admin"
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ssh_public_key: "ssh-ed25519 AAAA..."
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# --- Deployment ---
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deployment:
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method: "manual" # manual | github_actions
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repo_url: "" # e.g., "git@github.com:acme/ai-data-analyst.git"
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branch: "main"
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# --- Authentication ---
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auth:
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allowed_domain: "" # Google OAuth domain (e.g., "acme.com")
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google_client_id: "${GOOGLE_CLIENT_ID}"
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google_client_secret: "${GOOGLE_CLIENT_SECRET}"
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webapp_secret_key: "${WEBAPP_SECRET_KEY}"
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# --- Data source ---
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data_source:
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type: "keboola" # keboola | csv (bigquery planned)
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keboola:
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storage_token: "${KEBOOLA_STORAGE_TOKEN}"
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stack_url: "" # e.g., "https://connection.keboola.com"
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project_id: ""
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# --- Email (optional, for password auth) ---
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email:
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from_address: "noreply@example.com"
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from_name: "AI Data Analyst"
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sendgrid_api_key: "${SENDGRID_API_KEY}"
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# --- Desktop app (optional) ---
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desktop:
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jwt_issuer: "data-analyst"
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jwt_secret: "${DESKTOP_JWT_SECRET}"
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url_scheme: "data-analyst"
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# --- Telegram notifications (optional) ---
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telegram:
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bot_token: "${TELEGRAM_BOT_TOKEN}"
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bot_username: ""
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domain_suffix: ""
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# --- Jira integration (optional) ---
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jira:
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domain: ""
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email: ""
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api_token: "${JIRA_API_TOKEN}"
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webhook_secret: "${JIRA_WEBHOOK_SECRET}"
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sla_email: ""
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sla_api_token: "${JIRA_SLA_API_TOKEN}"
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cloud_id: ""
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# --- Corporate Memory AI (optional) ---
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ai:
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anthropic_api_key: "${ANTHROPIC_API_KEY}"
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# --- User display (for Corporate Memory avatars) ---
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users: {}
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# --- Username mapping (webapp email -> server username, only if different) ---
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username_mapping: {}
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# --- Optional datasets (sync settings UI) ---
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datasets: {}
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# --- Data catalog ---
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catalog:
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categories: {}
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order: []
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