Request for Architecture and Code Review

[swagatobauri]

Hi @MishraShardendu22,

As discussed, I am opening this issue to track the architecture and code review for the Python Playground project.

Current Build Status

We are currently in the early implementation phase. Getting your eyes on the architecture now will ensure we are aligned before building out the rest of the evaluators. Here is the current checklist:

• Core Foundation: Repo scaffold, Shared Zod schemas, & status enums
• Rubrics & Scoring: Rubric store (with SQL rubrics) and pure scoring function
• Approach Evaluation: LLM adapter, Approach evaluator, and POST /approach API
• Defence Evaluation: Defence evaluator and POST /defence API
• Failure Handling: Corrective tags, debrief builder, and comprehensive failure handling/retries
• Python Port: Python playground (5 rubrics + reuse proof)
• Benchmarking: Benchmark harness testing against the real LLM
• Documentation: Technical README and Architecture Overview

Updates for Review

• I have updated the Architecture Overview in the README.md to outline the current design, data flow, and trust boundaries.

Next Steps

• Asynchronous Review: Please feel free to review the updated README.md and the initial core schemas.
• Live Sync: I would like to schedule a live review today to go over the architecture together and gather your feedback before I proceed with the next checklist items. (Note: I am available anytime after 10:30 PM, following my 9:30 PM standup).

Looking forward to your guidance and suggestions!

[MishraShardendu22]

I'd suggest is, make a proper design doc first, something like this - Link for schema and then a document telling how you handle cases.

For example, what happens when a llm call fails, the 1st one fails or the 3rd one fails then what.

This is too basic to review rn, I read the md, it can't be judged like this.
Most probably you will face errors once you like build, but that is still in-efficient.

Most of the cases should noted and documented, coding will take like 5-6 prompts.

Also there is no deep-dive,for example, what is the criteria for the rubriks you want to set.
Why is a certain query measure on that specific point.

Converse with gpt, currently this is just an idea, you will implement this and it will cause tech debt.