Alf

C 65 completed
Framework
unknown / python · tiny
28
Files
4,796
LOC
1
Frameworks
4
Languages

Pipeline State

completed
Run ID
#356765
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Cataloged
Decision
proceed
Novelty
52.24
Framework unique
Isolation
Last stage change
2026-05-10 03:35:28
Deduplication group #51649
Member of a group with 14 similar repo(s) — canonical #89506 view group →
Top concepts (2)
Project DescriptionTesting
All rows above produced by Repobility · https://repobility.com

AI Prompt

I want to build a project using Python that implements active inference and learning models. Since this is a JAX-native framework, please structure the code to support these advanced machine learning concepts. The project should be testable, so please include setup for pytest. I'm working with configuration files, so ensure support for reading from TOML files, and the documentation should be clear, perhaps using Markdown for explanations.
python jax machine-learning active-inference pytest scientific-computing
Generated by gemma4:latest

Catalog Information

A JAX-native framework for implementing active inference and learning models.

Description

This library provides a complete, JAX‑based environment for building and training active inference agents. It offers modular components for defining generative models, policies, and inference engines, all optimized for GPU acceleration. Users can experiment with Bayesian learning, decision‑making under uncertainty, and hierarchical state estimation in a single, cohesive API. The framework is designed for researchers and developers who need a flexible, high‑performance tool to prototype and evaluate active inference algorithms. It bridges the gap between theoretical models and practical implementation, enabling rapid iteration and reproducibility.

الوصف

يقدم هذا الإطار بيئة متكاملة تعتمد على JAX لبناء وتدريب وكلاء الاستدلال النشط. يتضمن مكونات معيارية لتحديد النماذج التوليدية، السياسات، ومحركات الاستدلال، مع تحسينات لتسريع الأداء على وحدات معالجة الرسوميات. يتيح للمستخدمين تجربة التعلم البايزي واتخاذ القرار في ظل عدم اليقين وتقدير الحالات الهرمية ضمن واجهة برمجة تطبيقات موحدة. صُمم لتلبية احتياجات الباحثين والمطورين الذين يحتاجون أداة مرنة وعالية الأداء لتصميم وتقييم خوارزميات الاستدلال النشط بسرعة. يربط بين النماذج النظرية والتنفيذ العملي، مما يحقق تكرار التجارب وإمكانية إعادة إنتاج النتائج بسهولة.

Novelty

8/10

Tags

active-inference probabilistic-modeling bayesian-learning decision-making reinforcement-learning simulation inference-engine computational-neuroscience

Technologies

jax numpy

Claude Models

claude-opus-4.6

Quality Score

C
65.0/100
Structure
64
Code Quality
65
Documentation
35
Testing
70
Practices
68
Security
100
Dependencies
60

Strengths

  • Good test coverage (54% test-to-source ratio)
  • Code linting configured (ruff (possible))
  • Consistent naming conventions (snake_case)
  • Good security practices \u2014 no major issues detected
  • Properly licensed project

Weaknesses

  • Missing README file \u2014 critical for project understanding
  • No CI/CD configuration \u2014 manual testing and deployment
  • 308 duplicate lines detected \u2014 consider DRY refactoring

Recommendations

  • Add a comprehensive README.md explaining purpose, setup, usage, and architecture
  • Set up CI/CD (GitHub Actions recommended) to automate testing and deployment

Security & Health

4.1h
Tech Debt (C)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (2)
Methodology: Repobility · https://repobility.com/research/state-of-ai-code-2026/
Apache-2.0
License
4.7%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

python
97.7%
toml
0.9%
text
0.8%
markdown
0.6%

Frameworks

pytest

Concepts (2)

Repobility (https://repobility.com) — every score reproducible
CategoryNameDescriptionConfidence
Repobility · code-quality intelligence platform · https://repobility.com
auto_descriptionProject DescriptionActive inference/Learning Framework — standalone JAX-native active inference80%
auto_categoryTestingtesting70%

Quality Timeline

1 quality score recorded.

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