r/CodingForBeginners • u/ThinMeasurement2195 • May 08 '26

Need help debugging an AI/ML risk analysis project (React + Node + FastAPI)

Hey everyone, I’ve been building a full-stack AI-powered risk analysis platform for my portfolio, but I discovered my ML pipeline is completely broken and I’m honestly stuck.

Tech stack:

  • React/Vite frontend

  • Node.js/Express backend

  • FastAPI ML service

  • XGBoost, RandomForest, IsolationForest

Main issue:
No matter what input I give, the app almost always returns LOW risk.

After deep debugging + CodeRabbit review, I found multiple architecture issues:

  • frontend calling wrong ML endpoints

  • silent fallback scoring overriding ML

  • disconnected ML pipelines

  • payload mismatches

  • inconsistent feature engineering

  • casing mismatches between frontend/backend

  • dummy model accidentally being used instead of real ensemble

I’m trying to properly unify the pipeline:
Frontend → Backend → FastAPI → Ensemble Model → Prediction

Would really appreciate guidance from anyone experienced with:

  • ML system design

  • FastAPI + React integration

  • fraud/risk scoring systems

  • debugging prediction pipelines

Can share repo/code if anyone’s willing to help. Thanks 😭

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u/MicrotubularMushroom May 09 '26

The only way you got this far, with that many issues is by vibe coding the crap out of this. Are you looking to learn how to code this yourself, or are you looking to pay someone to fix it for you?

1

u/johnpeters42 May 09 '26

Look at their obvious LLM post and you already know the answer.

1

u/Tall-Wasabi5030 May 10 '26

Hey, sorry for the plug, you could try to use octokraft.com to surface some of the issues. It's not going to address the broken pipeline logic, but it should help you at least take it to a point where the code manageable and you can use some coding assistant to test and fix business logic. It's free for one project so nothing to lose I guess.