Moonboard Grader
completed
Other
monorepo / python · small
258
Files
32,331
LOC
4
Frameworks
11
Languages
Pipeline State
completedRun ID
#186059Phase
doneProgress
0%Started
2026-04-10 15:56:18Finished
2026-04-10 15:56:18LLM tokens
0Partial failures: SYMBOL_EXTRACTION: SymbolRecord.__init__() got an unexpected keyword argument 'tsv'; AI_REASONING: SymbolRecord.__init__() got an unexpected keyword argument 'tsv'
Pipeline Metadata
Stage
SkippedDecision
skip_scaffold_dupNovelty
54.87Framework unique
—Isolation
—Last stage change
2026-04-16 18:15:42Deduplication group #48424
All rows scored by the Repobility analyzer (https://repobility.com)
AI Prompt
Create a full-stack machine learning system to predict the difficulty grade of Moonboard climbing problems. The system needs a React/TypeScript frontend using Vite for visualization, a FastAPI backend to serve predictions, and a core classifier trained with PyTorch. Additionally, include a Generator component that uses a Variational Autoencoder to create synthetic problems, and an Aspire App layer using .NET Aspire/C# to orchestrate everything. I also need the Beta Solver and Beta Classifier components for advanced analysis.
python react typescript fastapi pytorch machine-learning deep-learning web-app dotnet ai
Generated by gemma4:latest
Catalog Information
Create a full-stack machine learning system to predict the difficulty grade of Moonboard climbing problems. The system needs a React/TypeScript frontend using Vite for visualization, a FastAPI backend to serve predictions, and a core classifier trained with PyTorch. Additionally, include a Generator component that uses a Variational Autoencoder to create synthetic problems, and an Aspire App layer using .NET Aspire/C# to orchestrate everything. I also need the Beta Solver and Beta Classifier com
Tags
python react typescript fastapi pytorch machine-learning deep-learning web-app dotnet ai
Security & Health
272
Vulnerabilities
24
Critical CVEs
122.7h
Tech Debt (D)
High
DORA Rating
C
OWASP (70%)
Open data scored by Repobility · https://repobility.com
FAIL
Quality Gate
2.5%
Duplication
Languages
Frameworks
FastAPI React pytest Vite
Symbols
variable349
function243
method170
class56
interface54
constant45
property8
type_alias7
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BinComp Dependency Hardening
All packages →8 of this repo's dependencies have been scanned for binary hardening. Grade reflects RELRO / stack canary / FORTIFY / PIE coverage.
Ftorch2.11.0 · 1,257 gadgets · risk 5116.6Nfastapi0.135.3 · 0 gadgets · risk 0.0Cmatplotlib3.10.8 · 2,481 gadgets · risk 0.0Fnumpy2.4.4 · 6,596 gadgets · risk 0.0Npydantic2.12.5 · 0 gadgets · risk 0.0Fscipy1.17.1 · 21,805 gadgets · risk 0.0Ntqdm4.67.3 · 0 gadgets · risk 0.0Nuvicorn0.44.0 · 0 gadgets · risk 0.0