Validation Gate: Guardrails, Auditing, and Production Stability

The Validation Gate: Guardrails, Auditing, and Production Stability

Pydantic as a Post-Guardrail:Trustworthy SQL

In a produciton system we have to assume that the LLM will occasionally hullucinate or generate unsafe commands. The validation gate’s primary defense is the use of Pydantic to enforce the output’s structure and safety.

• The Problem
  • The raw text output from an LLM is unpredictable and can contain syntatical errors, malformed JSON, or destructive SQL
• The Solution
  • We implemented a second Pydnatic model(SqlResponse) desinged specifically to parse and validate the LLM’s output. THis forces the unstructured text into a reliable, defined structure
• Operational Integrity
  • The validation logic explicitly checks the query_type indicator. FOr the Semantrino-API, we explicitly forbid desructive commands by raising a validaiton error if anything other than SELECT or EXPLAIN is detected. THis robust guardrail stops corrupted or malicious commands from ever reaching the Trino execution engine

Resource Saftey in Trino: Guaranteed Cleanup

Operational Stability depends on preventing resource exhaustion. Since Trino uses curors and network connections, we have to guarantee resources are released

• The flawo of Naive Closures
  • Simply calling .close() isn’t neough becaeuse it doesn’t handle if the code throws an exception mid-execution
• Solution
  • We implemented the try…except…finally pattern within the Trino Data Access Object implementation. The code to close the Database cursor and connection must reside in the finally block. This guarantees resource cleanup, preventing connection leaks and stopping the tirno cluster from running out of available resources.

Audit Trail and Failure Modes (Transparent Debugging)

A production system has to be auditable. Our API is designed to fail predictably and informatively.

• Clean Failure Modes
  • We avoid returing generic messages like 500 Internal Server Error. Instead, if a Pydantic validation or logic check fails, the API returns a precise 400 HTPException with a lcear, actionable error message. This clean failure mode gives the end-user or dwownstream client immediate, useful feedback, which is crucial for operational stability

This architecture focuses on making sure the API returns the validated SQL but doesn’t run it itself. This allows it to function as a secure SQL Gateway and the ensures that the execution remains transparent and auditable by the end-user. Thanks for reading and I’ll see you in the fourth part of this series!