My Secret to Reliable LLM Log Parsing: No More Hallucinating API Params

Description and use

LLM uses a strict JSON schema to extract parameters from microservice logs, and Pydantic validates the output, ensuring reliable automation.

Problem

Automated extraction of API parameters from noisy microservice logs was unreliable due to LLM hallucinations and inconsistent output formats.

Outcome

Consistent, reliable extraction of userId, orderId, productId, and requestMethod from logs, reducing manual troubleshooting effort.

Workflow

• 1. Send log snippet to LLM with prompt enforcing strict JSON schema and null handling.
• 2. Receive LLM JSON output.
• 3. Validate output with Pydantic ApiParams model.
• 4. If validation passes, use extracted parameters; if not, trigger human review.

Evidence

The real breakthrough came when I realized I wasn’t being strict enough about the output format.

Source

I use pydantic for this, because it’s super clean for defining schemas and validating data:

Source