๐ช๐ต๐ ๐ฅ๐ฒ๐ด๐ฒ๐ ๐๐ฎ๐ถ๐น๐ฒ๐ฑ ๐ฎ๐ป๐ฑ ๐๐๐ ๐ ๐ฆ๐ฎ๐๐ฒ๐ฑ ๐ ๐ฒ
I spent three days writing regex to parse emails. I wrote 400 lines of code. It worked for two formats. A third format broke everything.
Regex is brittle. Custom NLP models need too much data.
I switched to OpenAI function calling. I gave the model a JSON schema. The model returns structured data instead of plain text.
It handles:
- Different date formats
- Missing fields
- Address variations
Accuracy hit 92 percent.
I had one problem. Relative dates like "next Tuesday" were wrong. I added the current date to the prompt. This fixed the issue.
Trade-offs:
- Cost: Small fee per call
- Speed: Two second delay
This works for:
- Invoice line items
- Meeting minutes
- Customer feedback
Tips for you:
- Use a strict schema
- Provide context like today's date
- Validate your output
Stop debugging regex. Use LLM function calling.