Using AI/LLMs with Beancount - Anyone Experimenting?

Advanced technique: Using AI for smart categorization with context.

Instead of simple rule matching, I use AI to categorize based on:

Context-aware prompts:

Categorize this transaction considering:
- Merchant: "AMZN MKTP US*1A2B3C4D5"
- Amount: $47.23
- Previous Amazon purchases: Books, Kitchen supplies
- Date: Weekend
- My typical spending patterns

Return Beancount transaction.

AI considers:

  • Amount (books vs electronics)
  • Day of week (weekend = likely personal)
  • Historical patterns
  • Merchant variations

Results:

  • Better accuracy than simple regex (92% vs 85%)
  • Handles edge cases naturally
  • Learns from my patterns

Implementation:
Python script that:

  1. Reads uncategorized transactions
  2. Builds context from history
  3. Queries AI with context
  4. Outputs draft transactions
  5. I review and commit

Caution: Always review AI output before committing to ledger!