ryan
8f02318542
YNAB has no event feed, so keep a local copy in ynab_* tables synced via server_knowledge delta requests: full download on first run, deltas every YNAB_SYNC_INTERVAL seconds and on demand before each tool call, full resync daily. Each sync diffs against the mirror and appends real edits (transactions, assignments, renames) to ynab_changes, the edit history YNAB doesn't keep. Agent YNAB tools now answer from the mirror: budget summary (spending computed from transactions, since YNAB's month activity nets in credit card payment categories), account balances, transaction search with splits expanded, spending reports by category/payee/account/month, category budget, and recent changes. Adds an admin-only read-only ynab_sql tool guarded by a sqlglot allowlist (scope-resolved tables, no dangerous functions), a READ ONLY transaction, a timeout, and a row cap. Replaces utils/ynab_service.py and drops the unused ynab SDK. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
1.9 KiB
1.9 KiB
Tasks & Feature Requests
Feature Requests
YNAB Integration (Admin-Only)
- Description: Integration with YNAB (You Need A Budget) API to enable financial data queries and insights
- Requirements:
- Admin-guarded endpoint (requires
lldap_admingroup) - YNAB API token configuration in environment variables
- Sync budget data, transactions, and categories
- Store YNAB data for RAG queries
- Admin-guarded endpoint (requires
- Endpoints:
POST /api/admin/ynab/sync- Trigger YNAB data syncGET /api/admin/ynab/status- Check sync status and last updateGET /api/admin/ynab/budgets- List available budgets
- Implementation Notes:
- Use YNAB API v1 (https://api.youneedabudget.com/v1)
- Consider rate limiting (200 requests per hour)
- Store transaction data in PostgreSQL with appropriate indexing
- Index transaction descriptions and categories in ChromaDB for RAG queries
Money Insights
- Description: AI-powered financial insights and analysis based on YNAB data
- Features:
- Spending pattern analysis
- Budget vs. actual comparisons
- Category-based spending trends
- Anomaly detection (unusual transactions)
- Natural language queries like "How much did I spend on groceries last month?"
- Month-over-month and year-over-year comparisons
- Implementation Notes:
- Leverage existing LangChain agent architecture
- Add custom tools for financial calculations
- Use LLM to generate insights and summaries
- Create visualizations or data exports for frontend display
Backlog
- YNAB API client module
- YNAB data models (Budget, Transaction, Category, Account)
- Database schema for financial data
- YNAB sync background job/scheduler
- Financial insights LangChain tools
- Admin UI for YNAB configuration
- Frontend components for money insights display
Technical Debt
To be added
Bugs
To be added