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▲ 23 r/codereview+2 crossposts

What Grows Native Here

I made a website for United States native plants broken down by county.

Github

Using data from USDA Plants Database and their website, I've scraped county locations for all plants deemed native to the area by USDA, allowing for quick filtering on the info they provide. Images for each of the associated plants are pulled (when possible) from iNaturalist and its Open API collab with Amazon.

I still plan to add more filters for plants, as well as trying to expand on the information that USDA plants database sometimes lacks, such as foliage color, information about water / shade tolerance, and other related gardening/growing aspects of plants.

This is just my hobby project and foray into Angular SSR / Partial Hydration and experimental Angular/Aria. Hopefully you find it accessible via keyboard nav / mobile / desktop.

I do hope at least some of you find it as a helpful jumping off point for trying to create native gardens, as I also include links to the iNaturalist and USDA page for each plant species (where I can)

:)

whatgrowsnativehere.us.com
u/Slimpleton1113 — 6 days ago
▲ 1 r/codereview+1 crossposts

Code review

Do you guys can share your thoughts on how do you get ai written code reviewed? Im using octopus review https://www.octopus-review.ai and sort of happy with it but Id like to know if there is better alternative and why?

thanks

u/csisman — 6 days ago
▲ 4 r/codereview+2 crossposts

We vibe code. We speak things into existence. But sometimes the robot gets a little too excited and gives us a 500-line monster file, a function that does literally everything, and ten // TODO: implement this comments sprinkled around like confetti.

Got tired of negotiating. So I built a tiny ESLint plugin called eslint-plugin-ai-guardrails that just tells the AI assistant to chill out. Four rules: max file lines (300), max function lines (50), no orphan TODOs without a deadline, and no comments that just repeat the code like // set x to 5 right above const x = 5.

Now my robot and I have a better relationship. It still generates code, but the guardrails keep things tidy. One command setup: npx eslint-plugin-ai-guardrails init

npm: npmjs.com/package/eslint-plugin-ai-guardrails
GitHub: github.com/isaacnewton123/eslint-plugin-ai-guardrails

Anyone else build tools just to keep the AI in check? Share your "negotiation" stories!

u/Hot-Pea4514 — 10 days ago
▲ 0 r/codereview+1 crossposts

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 😭

reddit.com
u/ThinMeasurement2195 — 14 days ago